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Accelerating AWS Network Firewall troubleshooting with AWS DevOps Agent

Post Syndicated from Salman Ahmed original https://aws.amazon.com/blogs/security/accelerating-aws-network-firewall-troubleshooting-with-aws-devops-agent/

When an administrator introduces a rule change in AWS Network Firewall and network connectivity is disrupted, pinpointing the cause requires inspecting multiple points in the traffic path. The firewall gives you stateless and stateful rule engines, domain rules, and routing to the firewall endpoint inside your Amazon Virtual Private Cloud (Amazon VPC). A network drop looks the same from the workload no matter where it started. Isolating the cause means correlating the alert and flow logs with the firewall configuration, route tables, and recent API calls in AWS CloudTrail that might have changed them. That manual correlation is exactly where AWS DevOps Agent helps, accelerating root cause analysis so you can restore connectivity in minutes instead of hours.

AWS DevOps Agent does that correlation for you. As your always-available operations teammate, it resolves and proactively prevents operational issues across AWS, multicloud, and on-premises environments. When an Amazon CloudWatch alarm triggers, it reaches the agent through a webhook. The agent then reads the firewall configuration and logs through AWS APIs, ties the drop to recent API activity, and returns a root cause with a mitigation plan you review before you apply it.

This post connects CloudWatch monitoring to DevOps Agent. It walks through three Network Firewall failures from end to end. The first is a domain deny list blocking a legitimate endpoint. The second is a stateless rule priority misconfiguration. The third is an asymmetric cross Availability Zone (AZ) routing drop. Each maps to a different layer, so each leads down a different investigation path. An AWS Cloud Development Kit (AWS CDK) app deploys the whole environment in your own account so you can reproduce each failure and follow along.

The sample workload

As part of this blog post, we provide a CDK stack that deploys both the AWS DevOps Agent Space and a sample workload used to walk through three separate troubleshooting scenarios. A single t3.micro instance in a protected subnet checks its connectivity to a test endpoint on a continuous loop and publishes results to CloudWatch. Traffic takes the internet egress path through Network Firewall, the NAT gateway, and the internet gateway, so the firewall can intercept or drop it. After completing the walkthrough, you can apply the same troubleshooting techniques with DevOps Agent against your own Network Firewall deployments.

The test endpoint runs in a separate VPC deployed by the same CDK app. It serves HTTPS on port 443 and TCP on port 9142, giving each scenario a different protocol layer to exercise: Scenario 1 targets a TLS connection on 443 (matched by Server Name Indication), Scenario 2 targets a TCP connection on 9142, and Scenario 3 exercises the whole egress path.

A live status page shows one card per scenario plus the network topology. The whole stack deploys from a single CDK app across two Availability Zones, each with a firewall endpoint and NAT gateway, which is what makes Scenario 3 possible.

As shown in the following figure, the egress data path runs from the workload through Network Firewall and the NAT and internet gateways to the test endpoint. The alarm pipeline runs from CloudWatch through Amazon Simple Notification Service (Amazon SNS) and the webhook AWS Lambda function to DevOps Agent.

Figure 1: The sample workload

Figure 1: The sample workload

To use this with your own workload, you need a CloudWatch alarm that detects the connectivity problem and the webhook pipeline (SNS topic and Lambda function) that delivers it to DevOps Agent. The agent reads your firewall configuration, logs, and CloudTrail through AWS APIs, so no additional instrumentation is needed on the firewall side.

Prerequisites

To follow along with this post, you need:

Deploy the sample workload

Clone the project and deploy it into us-east-1 with one command (set awsRegion to use another AWS Region).

git clone https://github.com/aws-samples/sample-accelerating-aws-network-firewall-troubleshooting-with-aws-devops-agent.git
cd sample-accelerating-aws-network-firewall-troubleshooting-with-aws-devops-agent
bash scripts/deploy.sh

The script checks prerequisites, installs dependencies, compiles and tests, and bootstraps the CDK if needed. It then deploys all the stacks from a clean baseline and prints the outputs, including the status-page URL and sign-in details.

  1. Open the status-page link (an https://<random-id>.cloudfront.net address).
  2. Sign in using the username and password provided from the CDK output and confirm all three cards show the green Healthy status.
  3. Keep the page open while you run the scenarios.

Connect AWS DevOps Agent

To connect AWS DevOps Agent to the alarm pipeline

  1. In the AWS DevOps Agent console, open the nf-devops-agent-space Agent Space created by the CDK deployment.
  2. Configure the DevOps Agent webhook and download the CSV file with the webhook URL and signing secret.
  3. On the status page, choose Configure webhook, paste the URL and signing secret, and save. The page writes them to the nf-devops-agent-webhook-credentials AWS Secrets Manager secret, so there is no AWS CLI or console step. Until you set it, the bridge Lambda function sees a placeholder and skips delivery.
  4. Verify the path before you run a scenario. In the Lambda console, open nf-devops-agent-webhook and use the Test tab with this event.
    {
      "Records": [
        {
          "Sns": {
            "Message": "{\"AlarmName\":\"TEST-webhook-verification\",\"AlarmDescription\":\"[TEST] Webhook integration test - not a real alarm.\",\"NewStateValue\":\"ALARM\",\"NewStateReason\":\"[TEST] Manual webhook connectivity test. Safe to ignore.\",\"Region\":\"us-east-1\"}"
          }
        }
      ]
    }

  5. A 200 response confirms the path, and a test investigation appears in the DevOps Agent Operator Web App view.

How the alarm pipeline works

Every scenario reaches DevOps Agent the same way. A CloudWatch alarm moves to ALARM and notifies the SNS topic. Amazon SNS invokes a Lambda function. The function reads the webhook URL and signing secret from Secrets Manager, signs an alarm payload, and POSTs it to the DevOps Agent webhook (as shown in Figure 1). Amazon SNS also provides delivery retries, fan-out to other subscribers, and cross-account publishing.

  • Prebuilt Network Firewall metric (Scenario 1) Alarm-1 watches the DroppedPackets metric, summed across the stateful streams, and triggers when drops rise above a baseline threshold. This requires no workload or custom metric and works on an already-deployed firewall. However, it only tells you that the firewall is dropping packets, not which rule is responsible.
  • Application health metric (Scenarios 2 and 3) Alarm-2 and Alarm-3 watch a custom metric from a connectivity check. Use this for an alarm tied to user-facing impact or to tell one traffic path from another, which requires running a component that emits the metric.
Alarm Source Triggers when
Alarm-1 Native AWS/NetworkFirewall DroppedPackets The firewall’s dropped-packet count rises above the baseline
Alarm-2 Custom application health metric The port 9142 (TCP) connectivity check to the test endpoint is being dropped
Alarm-3 Custom application health metric The cross Availability Zone connectivity check is being dropped

Run the scenarios

Work through each of the scenarios one at a time, following the same cycle. Interrupt network connectivity, watch the alarm trigger, let DevOps Agent investigate, apply the recommended fix, and confirm recovery before moving on.

The status-page cards follow the live CloudWatch alarm state. A card shows a green dot and the word Healthy when its alarm is clear, and a red dot and the word DROPPED when its alarm triggers. In the DROPPED state the card also adds a Condition: line describing what’s being dropped, which isn’t shown when the card is healthy. Network Firewall applies changes to new flows, so a change shows within a minute or two. Recovery comes from the mitigation DevOps Agent recommends, which you review and apply.

Scenario 1. Domain deny list blocking a legitimate endpoint

At baseline, the rg-domain Suricata domain rule group denies only an unused placeholder, so the test endpoint stays reachable. The rule group inspects the TLS Server Name Indication (SNI) on each outbound connection and drops any that matches a denied domain. The exact rule syntax and console steps follow.

To add the domain deny rule

  1. Go to the Amazon VPC console.
  2. In the navigation pane, under Network Firewall, choose Network Firewall rule groups.
  3. Choose the rg-domain rule group to open its details page.
  4. In the Rules section, choose Edit.
  5. The rules box already contains two baseline placeholder rules (they match blocked.placeholder.invalid, so nothing real is denied). Leave those in place. Find the <app-endpoint-dns> value for Scenario 1 in the deployment script output (a Nework Load Balancer (NLB) DNS name such as NfTest-AppNl-a1b2C3dEf4G5-1234abcd5678efgh.elb.us-east-1.amazonaws.com). On a new line below the existing rules, add a drop rule that matches that DNS name on the TLS SNI, then choose Save.
    drop tls $HOME_NET any -> $EXTERNAL_NET any (ssl_state:client_hello; tls.sni; content:"<app-endpoint-dns>"; startswith; nocase; endswith; msg:"S1 domain denylist"; flow:to_server, established; sid:2000002; rev:1;)

  6. After saving, the rules box holds all three lines. The two placeholders remain, plus the new drop rule for the endpoint DNS name (note the distinct sid 2000002).
Figure 2: Scenario 1 – Firewall rule change blocking the connection

Figure 2: Scenario 1 – Firewall rule change blocking the connection

What happens. The workload’s HTTPS check to the test endpoint times out, the “AWS/NetworkFirewall DroppedPackets metric climbs above baseline, and Alarm-1 moves to ALARM. The Scenario 1 card reads DROPPED (with the condition Firewall dropping the monitored domain on its allow/deny rules), while the Scenario 2 and Scenario 3 cards stay Healthy (Figure 3). On the topology, the alarm pipeline from CloudWatch through Amazon SNS and Lambda to DevOps Agent and the workload-to-firewall inspect lines both turn amber, which the legend defines as collateral / alarm active, because the packets are now dropped at the firewall. To demonstrate the resulting failure, the HTTPS · SNI line from the internet gateway to the test endpoint is shown in red, which the legend defines as dropped (root cause).

Figure 3: Scenario 1 active – Traffic blocked at the firewall

Figure 3: Scenario 1 active – Traffic blocked at the firewall

Let DevOps Agent investigate. The agent runs several lines of investigation in parallel and correlates them:

  1. Reads the DroppedPackets metric and correlates the spike with a simultaneous drop in passed packets, confirming the firewall is actively blocking traffic.
  2. Reads the ALERT log and finds the workload’s TLS connections to the test endpoint blocked by the S1 domain denylist rule.
  3. Compares the current state against a baseline window, where the same endpoint was reachable with no alerts, which shows the block is new.
  4. Searches CloudTrail and surfaces the UpdateRuleGroup call that added the deny rule, identifying the user, role, and timestamp approximately one minute before the drops began.
  5. Reports the root cause as that manual rule-group change. Recommends removing the deny entry or adding an allow exception and enabling FirewallPolicyChangeProtection to prevent unauthorized changes.
  6. Presents this as a plan you review and apply, not an automatic change.

In the DevOps Agent Operator Web App view, the agent first restates the Alarm-1 trigger and confirms the firewall is dropping packets above the threshold (Figure 4).

Figure 4: Scenario 1 – The symptom

Figure 4: Scenario 1 – The symptom

Next, the agent identifies the root cause: a manual update to the rg-domain rule group that added a domain deny rule (SID 2000002) shortly before the alarm fired, blocking TLS connections to the ELB endpoint (Figure 5).

Figure 5: Scenario 1 – The root cause

Figure 5: Scenario 1 – The root cause

Finally, the agent presents a mitigation plan, recommending you remove the problematic deny rule (SID 2000002) to restore connectivity (Figure 6).

Figure 6: Scenario 1 – The mitigation plan

Figure 6: Scenario 1 – The mitigation plan

Note: In a real-world environment, this type of rule typically exists for a reason. Before removing it, verify whether it was intentional but scoped too broadly. If so, refine the rule to block only unauthorized endpoints rather than removing it entirely.

Confirm recovery. Apply the change the agent recommends. After the deny entry is gone, DroppedPackets falls back to baseline, Alarm-1 clears, and the card returns to green. Move on to Scenario 2.

Scenario 2. Stateless rule priority misconfiguration

At baseline, the rg-stateless-priority stateless rule group keeps the allow rule at priority 100 and the drop rule at 200 for the test class, TCP destination port 9142. The workload opens a TCP connection to the test endpoint on this port. Lower priority numbers evaluate first, so the allow rule wins. This scenario uses port 9142 instead of 443 to demonstrate a stateless rule, which matches on the packet’s 5-tuple (protocol, ports, addresses) rather than application content.

Introduce the change. Invert the two rule priorities so the drop rule evaluates before the allow rule. This is the kind of change a rushed rule edit can introduce.

To invert the stateless rule priorities

  1. Go to the Amazon VPC console.
  2. In the navigation pane, under Network Firewall, choose Network Firewall rule groups.
  3. Choose the rg-stateless-priority rule group to open its details page.
  4. In the Rules section, choose Edit.
  5. Raise the (Action: Pass) rule’s priority number so it sits after the (Action: Drop) rule, then choose Save. For example, change the (Action: Pass) rule from 100 to 300 (any number higher than the drop rule’s 200 works). You only need to move one rule, and using 300 avoids a clash with the drop rule that already sits at 200. Network Firewall evaluates the lowest priority number first, so the (Action: Drop) rule at 200 now wins for this traffic class, ahead of the (Action: Pass) rule at 300.
Figure 7: Scenario 2 – Rule priority change blocking the traffic class

Figure 7: Scenario 2 – Rule priority change blocking the traffic class

What happens. The drop rule now wins, the TCP connection to the test endpoint on port 9142 times out, the StatelessRuleFailures metric climbs above baseline, and Alarm-2 moves to ALARM. The Scenario 2 card reads DROPPED (with the condition Stateless rules dropping the monitored traffic class), while the Scenario 1 and Scenario 3 cards stay Healthy (Figure 8). On the topology, the alarm pipeline from CloudWatch through Amazon SNS and Lambda to DevOps Agent and the workload-to-firewall inspect lines both turn amber, which the legend defines as collateral / alarm active, because the packets are now dropped at the firewall. To demonstrate the resulting failure, the TLS :9142 line from the internet gateway to the test endpoint is shown in red, which the legend defines as dropped (root cause).

Figure 8: Scenario 2 active

Figure 8: Scenario 2 active

Let DevOps Agent investigate. A stateless drop happens before traffic reaches the stateful inspection engine, so it produces no ALERT log entries. The agent turns to configuration and flow logs instead:

  1. Reads the stateless rule group state and finds the drop rule at the lower priority number, ahead of the pass rule, so the drop evaluates first.
  2. Reads the flow logs and sees passed packets drop to zero within a minute of the change.
  3. Searches CloudTrail and surfaces the UpdateRuleGroup call that inverted the priorities, identifying the user, role, and timestamp about a minute before the alarm.
  4. Reports the root cause as that priority inversion. Recommends removing the redundant drop rule and managing the rule group through infrastructure-as-code (IaC) to prevent manual misconfigurations.
  5. Presents this as a plan you review and apply, not an automatic change.

In the DevOps Agent Operator Web App view, the agent first restates the Alarm-2 trigger and confirms that a workload connectivity health check is failing because the firewall’s stateless rules are dropping egress (Figure 9).

Figure 9: Scenario 2 – The symptom

Figure 9: Scenario 2 – The symptom

Next, the agent identifies the root cause, using the rule-group state and CloudTrail to pinpoint the conflicting DROP/PASS rules, where the new DROP rule’s lower priority number makes it match first (Figure 10).

Figure 10: Scenario 2 – The root cause

Figure 10: Scenario 2 – The root cause

Finally, the agent presents a mitigation plan, recommending you remove the conflicting DROP rule at priority 200 to restore traffic flow (Figure 11).

Figure 11: Scenario 2 – The mitigation plan

Figure 11: Scenario 2 – The mitigation plan

Confirm recovery. Apply the change the agent recommends. After the allow rule is ahead of the drop rule again, Alarm-2 clears and the card returns to green. Move on to Scenario 3.

Scenario 3. Asymmetric cross Availability Zone routing drop

At baseline, the protected subnet in each Availability Zone routes its egress through the firewall endpoint in that same Availability Zone , and the matching return route uses that same endpoint. One endpoint sees both directions of the flow, so the stateful engine completes the handshake. The workload runs in the protected subnet in us-east-1a (CIDR 10.0.4.0/24), so at baseline its egress and its return both use the us-east-1a firewall endpoint.

Introduce the change. Make the flow asymmetric by sending egress out one Availability Zone endpoint while the return comes back through the other. This takes two route edits, and both are required. With only the first edit the flow can still complete, so the alarm will not trigger until both are saved. It makes no firewall-policy change, mirroring a real multi-Availability-Zone routing mistake.

To create asymmetric cross Availability Zone routing

  1. Go to the Amazon VPC console and choose Route tables in the navigation pane.
  2. Flip the egress. Select the NfNetworkStack/SampleVpc/protectedSubnet1 route table (the us-east-1a protected subnet, where the workload runs). On the Routes tab, choose Edit routes. Its 0.0.0.0/0 route currently targets the us-east-1a firewall endpoint. For the target, choose Gateway Load Balancer Endpoint and select the us-east-1b firewall endpoint, then choose Save changes.
  3. Move the return. Select the NfNetworkStack/SampleVpc/publicSubnet2 route table (the us-east-1b public subnet, where egress now exits). Choose Edit routes, then Add route. For the destination enter the workload CIDR 10.0.4.0/24. For the target, choose Gateway Load Balancer Endpoint and select the us-east-1a firewall endpoint. Choose Save changes.

After both edits, a flow’s egress leaves through the us-east-1b endpoint while its return is directed to the us-east-1a endpoint. Neither endpoint sees the whole flow.

Figure 12: Scenario 3 routing change breaking the flow’s symmetry

Figure 12: Scenario 3 routing change breaking the flow’s symmetry

What happens. A new connection leaves through one endpoint. Its return arrives at the other endpoint, which never saw the connection open, so the handshake fails. Unlike Scenarios 1 and 2, this affects the whole subnet, so all egress stops and Alarm-2 and Alarm-3 both move to ALARM. The AWS/NetworkFirewall DroppedPackets alarm (Alarm-1) stays quiet because no endpoint is making a drop decision. The flow is lost to asymmetric routing rather than counted as a firewall drop. This is why monitoring application connectivity matters. A routing fault is invisible to the firewall’s own drop counter. On the status page, the Scenario 2 card reads DROPPED (with the condition “Stateless rules dropping the monitored traffic class”) and the Scenario 3 card reads DROPPED (with the condition Return traffic dropped by asymmetric cross-Availability-Zone routing), while the Scenario 1 card stays Healthy (Figure 13). On the topology, the alarm pipeline from CloudWatch through Amazon SNS and Lambda to DevOps Agent and the workload-to-firewall inspect lines both turn amber, which the legend defines as collateral / alarm active, while the egress path from the firewall through the NAT gateway and the TLS :9142 and HTTPS · routing lines to the test endpoint turn red, which the legend defines as dropped (root cause).

Figure 13: Scenario 3 – The status page during a path-wide outage

Figure 13: Scenario 3 – The status page during a path-wide outage

Let DevOps Agent investigate. Both Alarm-2 and Alarm-3 fire in the same datapoint. DevOps Agent recognizes them as linked and merges them into a single investigation:

  1. Reads the flow logs and sees bidirectional TLS connections stop abruptly, with only one-way traffic remaining and no flows reaching the established state.
  2. Reads the firewall metrics and sees received and passed packets shift from one Availability Zone to the other at the moment of the change.
  3. Calls DescribeRouteTables and finds the egress route pointing at one Availability Zone firewall endpoint while the return route points at the other.
  4. Searches CloudTrail and surfaces the ReplaceRoute and CreateRoute calls by the same user, about a minute before both alarms fired.
  5. Reports the root cause as that asymmetric routing change. Recommends restoring symmetric same-Availability-Zone routing so egress and return traverse the same endpoint.
  6. Presents this as a plan you review and apply, not an automatic change.

A mitigation plan is a recommendation you review, not an automatic change, and the right fix depends on the intended design. Restoring symmetric routing can mean sending the workload subnet’s egress back through its own-Availability-Zone firewall endpoint (this sample’s architecture) or, in a design that doesn’t inspect this path, back through a NAT gateway. The agent infers a plausible target from what it can observe, so review the specific route it proposes against your intended topology before you apply it. (Connecting your pipeline or infrastructure-as-code, covered in the next section, lets the agent recommend the target that matches your design.)

In the DevOps Agent Operator Web App view, the agent restates the Alarm-3 (AsymmetricFlowFailures) trigger and confirms the workload’s egress to a monitored endpoint is being blocked by the Network Firewall (Figure 14).

Figure 14: Scenario 3 – The symptom

Figure 14: Scenario 3 – The symptom

Next, the agent identifies the root cause: manual route table changes that created cross-AZ asymmetric routing through the network firewall, breaking its symmetric routing requirement (Figure 15)

Figure 15: Scenario 3 – The root cause

Figure 15: Scenario 3 – The root cause

Finally, the agent presents a mitigation plan, recommending you restore symmetric routing by pointing protectedSubnet1‘s default route back to the same Availability Zone firewall endpoint, so one endpoint sees both directions of the flow again (Figure 16).

Figure 16: Scenario 3 – The mitigation plan

Figure 16: Scenario 3 – The mitigation plan

Confirm recovery. Apply the change the agent recommends, after checking the route target matches your intended design. After the workload subnet’s egress and return use the same Availability Zone firewall endpoint again, the control probe recovers, the alarms clear, and every card returns to green.

Further considerations

In production a single change can trigger several alarms at the same time, as Scenario 3 shows. DevOps Agent links related investigations and works them as one, so you review a single root cause. You can validate the linked findings or unlink an alarm to investigate it independently. If you would rather collapse alarms before they reach the agent, you can add correlation logic in the bridge Lambda function, buffering and grouping by firewall. You can also add email, Amazon Simple Queue Service (Amazon SQS), or HTTP subscribers to the SNS topic, or add the webhook Lambda function to a topic you already run. DevOps Agent produces a mitigation plan but does not change your environment on its own.

You can also give the agent more to work with. DevOps Agent connects to source repositories and CI/CD pipelines, integrating with GitHub (including GitHub Enterprise Server and GitLab Self-Managed through a private connection). It can associate AWS resources with deployments of AWS CloudFormation, AWS CDK, Amazon Elastic Container Registry (Amazon ECR) images, and Terraform. With deployed configuration and recent deployment events in view, the agent correlates the disruption against the change that introduced it and recommends a fix matching your intended design. For this sample, that means recommending the workload subnet’s own Availability Zone firewall endpoint rather than a generic symmetric path.

DevOps Agent also supports proactive incident prevention. It analyzes patterns across past investigations and delivers recommendations to prevent similar issues from recurring, including governance recommendations that strengthen deployment processes and pipeline controls. For Network Firewall rule changes, this means the agent can recommend guardrails for your CI/CD pipeline based on the classes of misconfigurations it has already resolved. You can access these recommendations through the Improvements page in the DevOps Agent Operator Web App.

Clean up

Clean up the environment with one command.

bash scripts/destroy.sh

It reverts any active scenario, runs cdk destroy for all stacks, and sweeps for stragglers by the Project = nf-devops-agent tag. The main cost drivers are the two Network Firewall endpoints, the NAT gateways (one in the main VPC for each Availability Zone, one in the test-endpoint VPC), and the test endpoint’s load balancers. Each of these bills at an hourly rate for as long as it’s provisioned, whether or not traffic is flowing, so a stack left running continues to accrue charges around the clock even while idle. Running the scenarios and tearing the stack down the same day limits the cost to a few active hours rather than days of idle hourly charges.

Conclusion

In this post, we showed you how AWS DevOps Agent accelerates troubleshooting for three common network firewall connectivity issues. The first was a domain deny list. The second was a stateless priority inversion. The third was an asymmetric cross-AZ routing drop. For each one, DevOps Agent investigated the drop and returned a root cause with a mitigation plan you approve before applying. The first scenario triggered on a prebuilt Network Firewall metric, and the other two on application health metrics. That shows both ways to alarm on a firewall problem through one pipeline.

The pattern isn’t specific to Network Firewall. The same flow fits any service that emits CloudWatch metrics and logs, such as AWS WAF, security groups, and network ACLs. Clone the sample repository to explore the solution, then apply what you learn to your own firewall, application, and alarms. For more details, see the AWS Network Firewall Developer Guide and the AWS Network Firewall pricing page. Start with the Getting Started with AWS DevOps Agent guide to connect your first webhook.

Salman Ahmed

Salman is a Senior Technical Account Manager at AWS, specializing in helping customers design, implement, and optimize their AWS environments. He combines deep networking expertise with a passion for exploring emerging technologies to help organizations get the most out of their cloud investments. Outside of work, he enjoys photography, traveling, and watching his favorite sports teams.

How bitdrift scaled to 121 million concurrent gRPC connections on Amazon CloudFront for live telemetry sporting events

Post Syndicated from Raghuram Gururajan original https://aws.amazon.com/blogs/architecture/how-bitdrift-scaled-to-121-million-concurrent-grpc-connections-on-amazon-cloudfront-for-live-telemetry-sporting-events/

When 121 million mobile devices establish persistent gRPC connections to your origin infrastructure within seconds of a live broadcast, the routing policy behind your DNS records matters far more than it does at normal traffic levels. The wrong policy can concentrate all your connections onto a single origin endpoint, turning a scaling success into an outage. bitdrift, a mobile observability platform founded by former Lyft infrastructure engineers, learned this firsthand while delivering real-time telemetry for a major customer during the T20 World Cup cricket series. As matches kicked off, Amazon CloudFront absorbed traffic surging from near-zero to 110K+ peak requests per second.

bitdrift and the AWS account team diagnosed a connection concentration pattern under production pressure. The fix was a single DNS concentration change: migrating from weighted to multi-value answer routing. This change made bitdrift’s multi-Network Load Balancer (NLB’s) architecture distribute load, and they served 121 million devices with zero server-side errors.

bitdrift is a mobile observability platform (founded by ex-Lyft engineers) whose lightweight Capture performance-centric SDK provides real-time telemetry from millions of mobile devices. When bitdrift onboarded a major customer whose app serves live T20 World Cup cricket matches, they hit a scaling problem they hadn’t seen before: traffic surging from near-zero to tens of millions of concurrent gRPC connections within seconds of match start.

The DNS resolution imbalance

During early events in late February 2026, bitdrift experienced errors between CloudFront and their NLB origins under peak load. The AWS account team (SA, AM, TAM, CloudFront service team, and Amazon Route 53 specialists) identified the root cause: Route 53 Weighted routing was returning a single IP per DNS response. This caused all CloudFront cache hosts to resolve to the same origin for the duration of the TTL, creating a thundering herd effect that overwhelmed individual NLBs.

The TTL-driven traffic concentration

When you use weighted routing in Route 53, each DNS query returns a single IP address. At CloudFront’s scale, this means all edge nodes resolve your origin to the same load balancer for the duration of the DNS TTL. This creates a concentration effect where one NLB absorbs all traffic until the TTL expires and a new resolution occurs. Even after the customer scaled from 2 to 6 NLB IPs, the problem persisted because weighted routing returned a single IP per response. All CloudFront edge nodes resolved to the same origin for the duration of the TTL, making it appear that adding more origins had no effect.

Why persistent connections amplify this problem

Unlike short-lived HTTP requests, gRPC connections are long-lived and accumulate on whichever origin was resolved at connection time. This meant that a DNS configuration producing mild unevenness with stateless traffic caused catastrophic overload with persistent connections. Even after the customer scaled from 2 to 6 NLB IPs, the problem persisted. Weighted routing returned a single IP per response, and all CloudFront edge nodes resolved to the same origin for the duration of the TTL. This made it appear that adding more origins had no effect.

Architecture diagram

The following diagram shows the end-to-end architecture, from CloudFront edge nodes through Route 53 to the multi-region NLB fleet.

Figure 1. Amazon Route 53 is the origin-facing DNS routing layer between CloudFront and the multi-AZ Network Load Balancer (NLB) fleet. When CloudFront edge nodes need to reach the origin, they resolve the origin domain through Route 53, which directs traffic to the appropriate NLB across AZ-1, AZ-2, and AZ-3. Each NLB then forwards connections to its corresponding Amazon Elastic Kubernetes Service (Amazon EKS) workloads running within a virtual private cloud (VPC). Under Weighted routing, Route 53 returns only a single IP per DNS query, causing all edge nodes to converge on one NLB per TTL window, creating the thundering herd effect.

The fix: multi-value answer routing

Multi-Value Answer routing returns up to 8 IP addresses per DNS query, with built-in health checks per record. CloudFront edge nodes can immediately spread connections across multiple origins from the first DNS resolution, eliminating the single-origin bottleneck.

The customer-side change was straightforward:

  • bitdrift switched from Weighted to Multi-Value Answer routing, which returns up to 8 IPs per DNS response with built-in health checks spreading origin connections across multiple NLBs immediately.

The customer didn’t need to change any code or redesign their architecture. A DNS configuration update was all it took to handle 121 million concurrent devices with zero errors.

Graph showing traffic patterns during the T20 World Cup cricket series

Before vs. after comparison

Aspect Before (Weighted Routing) After (Multi-Value Routing)
IPs returned per DNS query 1 8
Origin load distribution All traffic to single NLB per TTL window Traffic spread across multiple NLBs immediately
Behavior under surge Thundering herd single NLB overwhelmed Even distribution no single point of overload
Errors at peak load Origin errors between CloudFront and NLB Zero server-side errors
Customer-side change required DNS configuration update only

Results and key metrics

Before the fix, CloudFront cache hosts resolved the origin domain to a single NLB IP per DNS TTL window (60 seconds). During traffic surges, this funneled all origin connections through a single load balancer, overwhelming its capacity.

On the February 27th event (14 million concurrent connections), approximately 80% of requests failed with HTTP 500 errors. The issue recurred on March 1st despite scaling to 4 NLB IPs. Weighted routing still returned only one IP per DNS response, so adding more origins had no effect until the routing policy was changed.

After switching to Multi-Value Answer routing on March 4th, CloudFront cache hosts immediately began resolving all 6 origin IPs simultaneously. During the next peak event, there were zero origin connection errors. By the final match on March 8th, bitdrift handled 121 million unique devices and 110K+ peak requests per second with zero server-side errors.

Key metrics

  • 121M unique devices during a single live sporting event.
  • 110K+ peak requests per second.
  • 100x traffic surge handled (near-zero to peak in seconds).
  • Zero server-side errors.
  • Minimal customer change: DNS configuration update only.

Performance before vs. after

Performance comparison chart showing error rates before and after switching to multi-value answer routing

Improvement summary

Metric Before (Mar 1–2) After (Mar 7–9) Improvement
Peak 5xx Error Rate 79.80% 0.033% 99.96% reduction (2,418× better)
Avg 5xx Error Rate 1.87% 0.003% 99.84% reduction (623× better)
Peak 5-min Requests 169M 49.3M Different event scale
Peak Requests/sec 563K 164K Different event scale
Avg 4xx Error Rate 0.014% 0.007% 50% reduction
Server-Side Outages Multiple origin failures Zero 100% elimination
Unique Devices (Mar 8) 121 million 121 million Zero server-side errors

Technical walk-through

To switch your Route 53 origin records from weighted routing to multi-value answer routing, follow these steps. If you’re using CloudFront with multiple origin load balancers, this configuration ensures traffic is distributed evenly across all of them from the first request.

Prerequisites

Before you begin, make sure you have:

  • An AWS account with access to Route 53 and CloudFront.
  • A hosted zone in Route 53 for your domain.
  • Two or more NLB’s serving as CloudFront origins.
  • A CloudFront distribution configured with your origin domain.
  • AWS Command Line Interface (AWS CLI) installed (optional, for CLI steps).

Step 1: Identify your current origin records

First, check what records currently exist for your origin domain.

In the console:

  1. Open the Route 53 console.
  2. Choose Hosted zones in the left navigation.
  3. Select your hosted zone (for example, origin.example.com).
  4. Find the records for your origin domain (for example, origin.example.com).
  5. Note the routing policy. If it says Weighted, this guide applies to you.

Using the CLI:

aws route53 list-resource-record-sets \
  --hosted-zone-id Z1234567890ABC \
  --query "ResourceRecordSets[?Name=='origin.example.com.']"

You’ll see something like:

[
  {
    "Name": "origin.example.com.",
    "Type": "A",
    "SetIdentifier": "nlb-1",
    "Weight": 50,
    "AliasTarget": {
      "DNSName": "nlb-1-abcdef.elb.us-east-1.amazonaws.com.",
      "HostedZoneId": "Z26RNL4JYFTOTI",
      "EvaluateTargetHealth": true
    }
  },
  {
    "Name": "origin.example.com.",
    "Type": "A",
    "SetIdentifier": "nlb-2",
    "Weight": 50,
    "AliasTarget": {
      "DNSName": "nlb-2-ghijkl.elb.us-east-1.amazonaws.com.",
      "HostedZoneId": "Z26RNL4JYFTOTI",
      "EvaluateTargetHealth": true
    }
  }
]

Step 2: Create health checks for each origin

Multi-Value Answer routing requires a health check attached to each record. The main advantage here is that unhealthy origins are automatically removed from the DNS responses.

In the console:

  1. In Route 53, choose Health checks in the left navigation.
  2. Choose Create health check.
  3. Configure:
  • Name: nlb-1-health-check.
  • What to monitor: Endpoint.
  • Specify endpoint by: Domain name.
  • Protocol: TCP (or HTTP/HTTPS if your origin supports it).
  • Domain name: nlb-1-abcdef.elb.us-east-1.amazonaws.com.
  • Port: Your origin port (for example, 443).
  • Request interval: 10 seconds (Fast) recommended for burst traffic patterns.
  • Failure threshold: 3.
  1. Choose Create health check.
  2. Repeat for each NLB.

Using the CLI:

aws route53 create-health-check \
  --caller-reference "nlb-1-health-$(date +%s)" \
  --health-check-config '{
    "Type": "TCP",
    "FullyQualifiedDomainName": "nlb-1-abcdef.elb.us-east-1.amazonaws.com",
    "Port": 443,
    "RequestInterval": 10,
    "FailureThreshold": 3
  }'

Step 3: Create multi-value answer records

Note: Multi-Value Answer routing requires IP address records, not Alias records. Assign Elastic IP addresses to each NLB Availability Zone before proceeding — Application Load Balancers are not compatible with this pattern because they do not support static IP addresses.

Now create the new records with Multi-Value Answer routing.

In the console:

  1. Choose Create record.
  2. Configure:
  • Record name: origin (or your subdomain)
  • Record type: A.
  • Routing policy: Multi-Value Answer.
  • Value/Route traffic to: Enter the IP address of your first NLB (or use the NLB’s static IP).
  • Health check: Select the health check you created for this NLB.
  • Record ID: nlb-1 (a unique ID for this record)
  • TTL: 60 seconds (keep it low for faster failover).
  1. Choose Create records.
  2. Repeat for each NLB.

Using the CLI:

aws route53 change-resource-record-sets \
  --hosted-zone-id Z1234567890ABC \
  --change-batch '{
    "Changes": [
      {
        "Action": "CREATE",
        "ResourceRecordSet": {
          "Name": "origin.example.com.",
          "Type": "A",
          "SetIdentifier": "nlb-1",
          "MultiValueAnswer": true,
          "TTL": 60,
          "ResourceRecords": [{"Value": "10.0.1.100"}],
          "HealthCheckId": "abcd1234-5678-90ab-cdef-EXAMPLE1"
        }
      },
      {
        "Action": "CREATE",
        "ResourceRecordSet": {
          "Name": "origin.example.com.",
          "Type": "A",
          "SetIdentifier": "nlb-2",
          "MultiValueAnswer": true,
          "TTL": 60,
          "ResourceRecords": [{"Value": "10.0.2.100"}],
          "HealthCheckId": "abcd1234-5678-90ab-cdef-EXAMPLE2"
        }
      }
    ]
  }'

Step 4: Delete the old weighted records

Once you’ve verified the Multi-Value Answer records are returning correctly (Step 5), delete the original Weighted routing records. Route 53 does not allow mixed routing policies for the same record name. The old Weighted records must be removed.

Step 5: Verify the configuration

dig origin.example.com +short

You should see multiple IPs returned simultaneously:

10.0.1.100
10.0.2.100
10.0.3.100

Summary of challenges

Resolving the issue under production pressure presented several challenges:

  • Diagnosing under fire: The initial outage occurred during a live T20 World Cup match with 14 million concurrent connections. Root cause analysis had to happen in real-time while the customer’s production traffic was failing.
  • Persistent connections amplify DNS routing issues: Unlike short-lived HTTP requests, gRPC connections are long-lived and accumulate on whichever origin was resolved at connection time. This meant that a DNS configuration producing mild unevenness with stateless traffic caused catastrophic overload with persistent connections.
  • DNS caching obscured the real bottleneck: Even after the customer scaled from 2 to 6 NLB IPs, the problem persisted. Because Weighted routing returned a single IP per response, all CloudFront edge nodes resolved to the same origin for the duration of the TTL. This made it appear that adding more origins had no effect.
  • Customer coordination under time pressure: The customer was initially reluctant to change their Route 53 configuration ahead of the next match. Working with the AWS account team to build confidence in the DNS change while a live event was days away required clear communication of the root cause and expected impact.

Conclusion

This case demonstrates that at extreme scale, infrastructure decisions that seem routine can become the difference between a flawless event and a production outage. Choosing a DNS routing policy is one such decision. bitdrift’s architecture was sound: CloudFront at the edge, NLBs at the origin, gRPC for efficient persistent connections. But Weighted routing’s single-IP-per-response behavior created a thundering herd that no amount of origin scaling could overcome.

The fix was purely configuration: switching from weighted to multi-value answer routing in Route 53. After that change, bitdrift handled 121 million concurrent devices with zero errors.

If you’re running CloudFront with multiple origin load balancers, especially with persistent connection protocols like gRPC or WebSocket, review your Route 53 routing policy. Multi-Value Answer routing ensures that CloudFront edge nodes distribute origin connections across all available endpoints from the first DNS resolution. This eliminates the single-origin bottleneck that Weighted routing can create under surge conditions.

For pre-event capacity planning or to discuss your architecture with an AWS specialist, contact your AWS account team or reach out through AWS Support.

Key takeaways

  1. DNS routing policy selection matters at extreme scale. Weighted vs. Multi-Value Answer has significant implications for origin load distribution behind CloudFront.
  2. Persistent connections (gRPC, WebSocket) amplify DNS routing problems. Unlike stateless HTTP where connections are short-lived, persistent connections accumulate on whichever origin was resolved at connection time. A DNS misconfiguration that causes mild unevenness with HTTP traffic can cause catastrophic overload with persistent connections.
  3. Engaging AWS service teams early for pre-event capacity reviews prevents day-of failures.
  4. A DNS configuration change can improve scale without requiring any architectural changes.

About the authors

Regional routing for AWS access portals: Implementing custom vanity domains for IAM Identity Center

Post Syndicated from Georgi Baghdasaryan original https://aws.amazon.com/blogs/security/regional-routing-for-aws-access-portals-implementing-custom-vanity-domains-for-iam-identity-center/

AWS IAM Identity Center provides a web-based access portal that gives your workforce a single place to view their AWS accounts and applications. With the recent launch of IAM Identity Center multi-Region replication, customers can replicate their IAM Identity Center instance across multiple AWS Regions to improve resilience and reduce latency for a globally distributed workforce. As a result, users have a dedicated access portal URL in each Region where Identity Center is replicated, and where administrators need a consistent way to manage these portals to ensure that each user reaches the right one.

This post walks you through building a custom vanity domain (for example, aws.mycompany.com) that serves as a single, memorable entry point for access to IAM Identity Center through the AWS Management Console. The solution uses latency-based routing to automatically redirect users to their nearest healthy access portal endpoint and provides a mechanism to trigger failovers when a Regional Identity Center instance, or the broader AWS Region, is impaired. Because this solution operates outside of Identity Center—at the DNS and load balancer layer—users are transparently redirected to the appropriate Regional access portal URL. Note that the vanity domain itself will not appear in the browser’s address bar.

This guide is structured in three progressive phases: a single-Region redirect, multi-Region latency routing, and automatic health-based failover. You can adopt each phase independently, depending on your organization’s needs.

Note: While this guide focuses on IAM Identity Center access portal endpoints, the same approach using Amazon Route 53 latency-based routing, Application Load Balancer (ALB) redirects, and Amazon Application Recovery Controller (ARC) Region switch can be applied to build a custom vanity domain and intelligent routing layer for any other HTTP endpoint type.

Background

IAM Identity Center supports multiple access portal URL formats that resolve to the same web portal. The following table summarizes the supported formats in the standard AWS (classic) partition, along with their capabilities:

Format IPv4 Dual-stack Multi-Region* Example
https://{directoryId}.awsapps.com/start Yes No No https://d-1234567890.awsapps.com/start
https://{alias}.awsapps.com/start Yes No No https://mycompany.awsapps.com/start
https://{idcInstanceId}.{region}.portal.amazonaws.com Yes No Yes https://ssoins-1234567890.us-west-2.portal.amazonaws.com
https://{idcInstanceId}.portal.{region}.app.aws ★ Yes Yes Yes https://ssoins-1234567890.portal.us-west-2.app.aws

* Each Regional URL resolves only to its own Region’s portal instance and doesn’t fail over to another Region. Multi-Region here means the URL format is available in every Region where IAM Identity Center is replicated. To route users across Regions dynamically, use the vanity domain approach described in this post.

Note: The ★ highlighted row (https://{idcInstanceId}.portal.{region}.app.aws) is the recommended URL format. It supports both dual-stack (IPv4 and IPv6) and IAM Identity Center multi-Region replication. The awsapps.com formats aren’t always available in newer Regions and don’t support multi-Region capabilities. In additional replicated Regions, the custom alias isn’t supported, and the awsapps.com parent domain isn’t available.

Working with multiple Regional endpoints

As you expand your IAM Identity Center footprint through multi-Region replication, each replicated Region provides a dedicated access portal URL—directing your users to the low-latency entry point closest to their location. A user connecting from Europe and one connecting from Asia Pacific each benefit from their respective Regional endpoint. To deliver the best experience, organizations need a consistent, centrally managed way to direct users to the correct Regional destination; there are a few common approaches you can use to achieve this.

Customers typically start with a single Regional endpoint, which is straightforward to configure, but users in distant Regions experience higher latency, and a Regional incident can affect all users regardless of location. Others maintain per-Region bookmarks or configuration, which gives each user population the right endpoint but requires ongoing IT coordination and clear communication to users.

Custom vanity domains give you full control over DNS routing, health checks, and failover of your access portal connections; all behind a single, brand-aligned domain name (for example, aws.mycompany.com) that users access. A vanity domain makes this start URL memorable and consistent for users, regardless of the underlying IAM Identity Center configuration – a single address to remember and share, compared to maintaining a separate bookmark for each Regional endpoint or managing a growing list of application tiles in your external identity provider. The rest of this guide walks you through how to deploy this solution step by step.

Solution overview

The solution builds a lightweight routing and redirect layer in front of the IAM Identity Center access portal Regional endpoints. The architecture has the following components:

  • AWS IAM Identity Center – Your existing Identity Center instance
  • Amazon Route 53 – Manages your vanity domain’s hosted zone, latency-based routing policy, and health checks
  • AWS Certificate Manager (ACM) – Issues and automatically renews TLS certificates for your vanity domain in each Region
  • Application Load Balancer (ALB) – Handles HTTP and HTTPS traffic, issuing 302 redirects to the appropriate Regional access portal endpoint
  • Amazon Application Recovery Controller (ARC) Region switch – Orchestrates Regional failovers by controlling Route 53 health check states, so traffic is automatically shifted away from an unhealthy Region

This guide is structured in three progressive phases. You can adopt each phase incrementally based on your needs:

  • Phase 1: Sets up the vanity domain with a redirect to a single Regional access portal endpoint. Suitable for organizations with a single-Region Identity Center deployment.
  • Phase 2: Extends Phase 1 across multiple Regions with latency-based routing, so users are automatically directed to the nearest Regional endpoint. Requires IAM Identity Center multi-Region replication.
  • Phase 3: Adds an ARC Region switch for managed Regional failover. Without Phase 3, a Regional impairment requires manual DNS updates to redirect traffic. ARC automates this with rehearsable, controlled failover plans.

Figure 1: Solution architecture for custom vanity domain routing with IAM Identity Center.

When a user navigates to aws.mycompany.com, the following happens:

  1. Route 53 evaluates the latency records and routes traffic to the ALB in the lowest-latency healthy Region.
  2. The ALB terminates TLS using an ACM-managed certificate and issues a 302 redirect to the corresponding Regional Identity Center access portal URL.
  3. The user’s browser follows the redirect and loads the access portal directly. Subsequent authentication traffic flows between the browser and AWS—the ALB isn’t in the path.

If you’ve implemented Phase 3, ARC controls Route 53 health check states for each Region. With this configuration, you can stop routing traffic to any Region considered unhealthy.

Prerequisites

Before you begin to build the solution, ensure you have the following in place:

  1. An existing top-level domain (TLD) (for example, mycompany.com).
  2. An AWS IAM Identity Center organization instance configured.
  3. For Phases 2 and 3, you need IAM Identity Center multi-Region replication configured with at least two Regions. See Setting up IAM Identity Center multi-Region replication for instructions.
  4. AWS Identity and Access Management (IAM) permissions on a dedicated networking or shared services account in your organization to manage Route 53, ACM, Amazon Elastic Compute Cloud (Amazon EC2), ALB (phase 1 and 2), and ARC (phase 3).

Phase 1: Redirect to a single predefined access portal endpoint

In this phase, you create the foundational infrastructure: a Route 53 hosted zone, an ACM-managed TLS certificate, and an internet-facing ALB that issues a 302 redirect to your Regional access portal URL. By the end, users who navigate to aws.mycompany.com will be seamlessly redirected to your Identity Center portal.

Create a Route 53 hosted zone for your vanity domain

The hosted zone holds the DNS records that control how aws.mycompany.com resolves. If your top-level domain (mycompany.com) is already registered in Route 53, you create a subdomain hosted zone. If it’s registered with another registrar, you create a public hosted zone and configure name server (NS) delegation manually.

  1. In the AWS Management Console, navigate to Route 53 and choose Hosted zones, then Create hosted zone.
  2. Enter your vanity domain in the Domain name field (for example, aws.mycompany.com).
  3. Select Public hosted zone as the type, then choose Create hosted zone.
  4. Note the four NS records that Route 53 creates for the new hosted zone. You will need these in the next step.

Figure 2: Route 53 hosted zone details

Delegate your subdomain from the parent domain

To make Route 53 authoritative for aws.mycompany.com, you must add an NS record in the parent zone (mycompany.com) pointing to the name servers of the new hosted zone.

  • If mycompany.com is hosted in Route 53: Open the mycompany.com hosted zone, choose Create record, set the record name to aws, the type to NS, and paste the four NS values from the previous step. Choose Create records.
  • If mycompany.com is hosted elsewhere: Sign in to your registrar’s DNS management console and add an NS record for aws.mycompany.com using the four name server values from the previous step.

Note: DNS propagation for NS delegation can take up to 48 hours, though it typically completes within a few minutes for Route 53-to-Route 53 delegation.

Figure 3: Create a NS record type to delegate your subdomain from the parent domain

Request an ACM certificate

Your ALB requires a TLS certificate for aws.mycompany.com to serve HTTPS traffic. ACM provides free public certificates with automatic renewal.

  1. Go to the Certificate Manager console in the primary Region of IAM Identity Center (for example, us-east-2) and choose Request a certificate.
  2. Select Request a public certificate and choose Next.
  3. Enter your domain name (for example, aws.mycompany.com). Choose Add another name to this certificate and enter your Regional sub-domain (for example, us-east-2.aws.mycompany.com).
  4. Leave other options as defaults (Disable export, DNS validation – recommended, and key algorithm – RSA 2048) and choose Request.
  5. In the certificate details page, choose Create records in Route 53. ACM will automatically add the validation CNAME records to your hosted zone. The certificate status changes to Issued within a few minutes.

Figure 4: Request an ACM certificate for your domain

Create a security group for Identity Center ALB

The security group needs to allow inbound HTTP and HTTPS traffic for both IPv4 and IPv6 from the public internet to make the load balancer reachable.

  1. Go to the Amazon EC2 console, navigate to Security Groups, and choose Create security group.
  2. Enter a Name (for example, identitycenter-global-domain-alb-sg-us-east-2) and Description. Add four rules by choosing Add Rule under Inbound Rules.
    1. Set Type to HTTP, and Source to Anywhere-IPv4 (0.0.0.0/0) and to Anywhere-IPv6 (::/0).
    2. Set Type to HTTPS, and Source to Anywhere-IPv4 (0.0.0.0/0) and to Anywhere-IPv6 (::/0).
  3. Choose Add Rule under Outbound Rules and set Type to All traffic and Source to Anywhere-IPv6 (::/0).
  4. Choose Create security group.

Figure 5: ALB security group rules

Create an ALB with an HTTP and HTTPS redirect rule

The ALB is the component that performs the actual redirect to your IAM Identity Center access portal URL. The ALB listener accepts HTTPS requests on port 443 and responds with a 302 redirect to the appropriate Regional Identity Center access portal endpoint.

  1. Go to the Amazon EC2 console, navigate to Load Balancers, and choose Create load balancer. Select Application Load Balancer.
  2. Enter a name for your ALB (for example, identitycenter-redirect-alb).
  3. Configure basic settings: Set the scheme to Internet-facing, IP address type to Dualstack (or IPv4 if IPv6 isn’t supported by your virtual private cloud (VPC)), and select at least two Availability Zones. Ensure that the load balancer is operating in a VPC and subnets that are internet-facing.
  4. Under Security Groups choose the Security Group created in the previous step.
  5. Configure an HTTP listener: Add a listener on port 80 (HTTP) with Redirect to URL option. Choose URL parts and set Protocol to HTTPS, Port to 443, and status code to 302 (Found).

    Figure 6: Add an HTTP listener during ALB creation

  6. Configure an HTTPS listener: Add a listener on port 443 (HTTPS) with No pre-routing action (default) and Redirect to URL options. Choose Full URL and set the URL to your Regional Identity Center access portal endpoint (For example, https://ssoins-1234567890.portal.<your-region>.app.aws, for this blog the region is us-east-1). Set status code to 302 (Found).

    Figure 7: Add an HTTPS listener

  7. Under Default SSL/TLS certificate, select the ACM certificate you created in Step 3.

    Note: Make sure to select 302 – Found as the Status code. Selecting 301 – Permanently moved will result in browser caching the redirect URL which will prevent failovers from working correctly until the cache expires.

Create Regional Route 53 records pointing to your ALB

Create a DNS record in your hosted zone that resolves <your-region>.aws.mycompany.com to your ALB.

  1. Open your Route 53 hosted zone for aws.mycompany.com and choose Create record.
  2. Set the record name to the AWS Region name (For example: us-east-2) and the record type to A.
  3. Toggle Alias and in the drop down menu Route traffic to, select the alias target to Alias to Application and Classic Load Balancer, select your Region (For example:us-east-2), and select your ALB from the dropdown list.
  4. Leave routing policy as Simple routing, and select the Region (For example:us-east-2) and choose Create records.
  5. Repeat steps 1 through 4 to create AAAA record types.

Figure 8: Route 53 record with simple routing policy

Add latency-based routing configurations

Finally, create a DNS record in your hosted zone that resolves aws.mycompany.com to your Regional Route 53 record.

  1. Open your Route 53 hosted zone for aws.mycompany.com and choose Create record.
  2. Keep the subdomain name for this record as empty, so aws.mycompany.com is the fully qualified record and set the record type to A.
  3. Enable alias: Set the Route traffic to Alias to another record in this hosted zone, and select the hosted zone you created earlier (us-east-2.aws.mycompany.com).
  4. Set Routing Policy to Latency and select the corresponding Region (us-east-2 in this example).
  5. Add a clear name for the Record ID, such as us-east-2--ipv4 as a differentiator and choose Create records.
  6. Repeat the steps 1 through 5 to create AAAA record types with us-east-2--ipv6 as the record ID.
Figure 9: Route 53 record with latency-based routing

Figure 9: Route 53 record with latency-based routing

Test the configuration by navigating to https://aws.mycompany.com in a browser. You should be redirected to your Identity Center access portal. You can also validate using:
curl -I https://aws.mycompany.com

Expected response:

HTTP/2 302

location: https://ssoins-1234567890.portal.<your-region>.app.aws

Tip: To deploy Phase 1 automatically, download the CloudFormation template from the Deploying with CloudFormation section below.

Phase 2: Automatically route to the nearest Regional access portal endpoint

Phase 2 extends the solution to support IAM Identity Center multi-Region replication by deploying an ALB in each replicated Region and configuring Route 53 latency-based routing. Users are automatically directed to the access portal in the Region that has the lowest network latency from their location, which matches the active-active behavior of the Identity Center access portal itself.

Request ACM certificates in each additional Region

Repeat the steps from Request an ACM Certificate for each additional Region (for example, us-west-2) where you’ve replicated IAM Identity Center.

Create a security group and an ALB in each additional Region

Repeat the steps from Create a security group for Identity Center ALB and Create an ALB with an HTTP and HTTPS redirect rule in each additional Region. In each ALB’s redirect rule, set the target URL to the access portal endpoint for that specific Region. For example:

  • us-east-2 ALB redirects to https://ssoins-1234567890.portal.us-east-2.app.aws
  • us-west-2 ALB redirects to https://ssoins-1234567890.portal.us.west-2.app.aws

Create Regional and latency Route 53 records for the additional Region

For each additional Region where you’ve deployed an ALB and replicated Identity Center, create Regional and latency A and AAAA records as outlined in Create Regional Route 53 records pointing to your ALB and Add latency-based routing configurations.

Tip: To deploy Phase 2 automatically, download the CloudFormation template from the following Deploying with CloudFormation section.

Phase 3: Regional failover using ARC Region switch

Phase 3 introduces Amazon Application Recovery Controller (ARC) Region switch, a fully managed capability that you can use to plan, practice, and orchestrate Regional failovers with confidence. ARC Region switch vends Route 53 health checks directly as part of a Region switch plan. You attach these generated health checks to your Route 53 latency records, and ARC controls their healthy or unhealthy state during plan execution. You can further extend the solution to include custom automation triggered by Amazon CloudWatch alarms or synthetic canaries to update routing control state.

We recommend creating your ARC Region switch plan in the primary Region of your IAM Identity Center for ease of discovery.

Create an active-active instance of ARC Region switch plan

Create an ARC Region switch plan that will orchestrate failovers between your IAM Identity Center Regions and auto-generate the Route 53 health checks you will reference in the next step.

  1. Open the Application Recovery Controller console and choose Region switch in the navigation pane. Select Create Region Switch Plan.
  2. Enter a Plan name (for example, idc-access-portal-failover) and an optional description. Choose Active/Active for Multi-Region recovery approach. Select the Regions where IAM Identity Center is replicated ,including the primary Region.
  3. In the Execution Permission section, enter the Amazon Resource Name (ARN) of the IAM role that ARC will use to update Route 53 health check states during plan execution. If you don’t have an existing role, choose Create a new role to have ARC create one automatically. See AWS Managed Policy: AmazonApplicationRecoveryControllerRegionSwitchPlanExecutionPolicy for information about required permissions.
  4. Choose Create Plan and proceed to Build workflows. Enter optional descriptions and choose Save and continue.

    Figure 10: Region switch plan

  5. Set the Workflow type to Activate and set the Region to the corresponding Region (us-east-2 or us-west-2). Within each workflow, choose Add step/Run in Sequence. Choose an execution block to Amazon Route 53 health check execution blog under Networking.
  6. Choose Add and edit. Enter a Step name (for example, Activate Route53 Record Set).
  7. Set the Hosted zone to the hosted zone ID for your aws.mycompany.com domain, and set the Record name to aws.mycompany.com.
  8. Expand Record set identifiers. Choose Add record set identifier and enter a unique identifier for the record set (for example, us-east-2--ipv4 and us-east2--ipv6) and select your Region. Add two record set identifiers (A and AAAA records) for each of your Regions.
  9. Choose Save step.
  10. Repeat steps 5 and 6 for Deactivate and choose Save the plan.

    Figure 11: Workflow builder

  11. Choose Save workflows.
  12. Select the newly created plan and choose the Monitoring tab. Note the IDs of the health checks created.

    Figure 12: IAM Identity Center access portal plan

Update Route 53 record sets to reference ARC-managed health checks

Associate the ARC-generated health check IDs with the latency-based A and AAAA records you created in Phase 1 and 2. Route 53 uses these health checks—which are now controlled by ARC—to determine which Regions are eligible for DNS resolution. Route 53 still uses latency to choose from the healthy Regions.

    1. Go to the Route 53 console and choose Hosted zones.
    2. Select the hosted zone for aws.mycompany.com.
    3. Find the latency-based A record for us-east-2 that you created in Phase 2, and choose Edit record.
    4. In the Health check section, enable Associate with a health check. In the Health check ID dropdown, select the ARC-generated health check for us-east-2 that you noted at the end of the preceding procedure. Note: Ignore the warning This health check ID doesn’t belong to this AWS account. Make sure you have copied it accurately to use it.
    5. Choose Save changes.
    6. Repeat steps 3, 4, and 5 for A and AAAA records for each of your IAM Identity Center Regions.

Figure 13: Update Route53 record sets

Validate the setup by performing a failover

Validate the end-to-end configuration by executing a controlled failover. Because latency-based routing will always resolve aws.mycompany.com to us-east-2 for users in the primary geography, deactivating us-east-2 is the most direct way to confirm that Route 53 correctly fails over to us-west-2.

    1. Before executing the failover, confirm that aws.mycompany.com is resolving to the us-east-2:
      curl -I https://aws.mycompany.com
      Expected: A record pointing to the us-east-2 access portal URL (for example, https://ssoins-1234567890.portal.us-east-2.app.aws:443/).
    2. Go to the Amazon Application Recovery Controller console. In the left navigation pane, choose Region switch.
    3. Select your Region switch plan (idc-access-portal-failover) to open the plan details page.
    4. Choose Execute recovery.
    5. On the Execute plan page, select us-east-2 as the Region to fail out of.
    6. Select the Deactivate action and choose Start execution. ARC sets the us-east-2 health check to unhealthy. Route 53 stops resolving aws.mycompany.com to the us-east-2 ALB and routes traffic to us-west-2 instead.
    7. After a few seconds, confirm the failover has taken effect:
      curl -I https://aws.mycompany.com
      Expected: 302 redirect to the us-west-2 IAM Identity Center access portal URL
    8. To fail back, choose Execute plan again. Select us-east-2, select the Activate action and choose Start execution. ARC marks the us-east-2 health check healthy and Route 53 resumes routing traffic to that Region.

Tip: To deploy Phase 3 automatically, download the CloudFormation template from the Deploying with CloudFormation section that follows.

Deploying with CloudFormation

As an alternative to the manual console steps described previously, we provide CloudFormation templates that you can download and deploy for each phase. Each template is self-contained and parameterized, so you only need to provide your environment-specific values (such as your vanity domain name, VPC, and subnet IDs). Download the templates from the following links:

To deploy a template, navigate to the AWS CloudFormation console, choose Create stack, select Upload a template file, and upload the downloaded YAML file. Follow the prompts to provide parameter values and create the stack. For Phase 2, deploy the template once in each additional Region.

Deploy all phases with a single scrip

As an alternative to deploying each CloudFormation template individually, you can use the provided deploy.sh bash script to deploy all three phases in sequence. The script automates stack creation across your primary and additional Region. To get started, download the deployment package, then unzip the file into a local directory:

wget https://aws-security-blog-content.s3.us-east-1.amazonaws.com/public/sample/3536-regional-routing-for-aws-access-portals/Vanity-domains-cfn.zip
unzip  Vanity-domains-cfn.zip
cd Vanity-domains-cfn

Before running the script, open the deploy.sh file and update the following required parameters with your environment-specific values:

  • TLD – Your top-level domain (for example, mycompany.com)
  • TLD_HOSTED_ZONE_ID – The Route 53 hosted zone ID for your top-level domain
  • IDC_SUBDOMAIN – The Identity Center subdomain name (for example, aws)
  • IDC_INSTANCE_ID – Your IAM Identity Center instance ID (for example, ssoins-1234567890)
  • PRIMARY_REGION – The primary Region for your Identity Center instance (for example, us-east-2)
  • ADDITIONAL_REGIONS – The additional Region for multi-Region replication (for example, us-west-2)

After updating the configuration, run the deployment script:

./deploy.sh

The script deploys Phase 1 (single-Region redirect), Phase 2 (multi-Region latency-based routing), and Phase 3 (ARC Region switch failover) in order. Monitor the terminal output for stack creation progress and any errors.

After completing the setup, you can integrate the vanity URL (for example, aws.mycompany.com) directly into your identity provider, such as Okta or Microsoft Entra ID, as a bookmark application or a chiclet URL. By configuring the vanity URL as the bookmark target, users who launch the application from their identity provider dashboard are always redirected to the nearest IAM Identity Center access portal endpoint through latency-based routing. If a Regional impairment occurs and a failover is necessary, administrators can execute an ARC Region switch to deactivate the impaired Region, and users will automatically be redirected to the active Identity Center endpoint without any change to the bookmark URL or end-user experience.

Conclusion

In this post, you learned how to build a custom vanity domain for an AWS IAM Identity Center access portal using Amazon Route 53, AWS Certificate Manager, Application Load Balancer, and an Amazon Application Recovery Controller (ARC) Region switch. The three-phase approach lets you start with a single-Region redirect, progressively add latency-based routing as your IAM Identity Center footprint grows with multi-Region replication, and then introduce an ARC Region switch to gain fully managed, rehearsable Regional failover.

For more information about IAM Identity Center multi-Region replication, see the IAM Identity Center User Guide. For more resilience patterns, visit the AWS Architecture Blog posts about Resilience. If you have feedback about this post, submit comments in the Comments section below. If you have questions about this post, contact AWS Support.

Resources


Georgi Baghdasaryan

Georgi Baghdasaryan

Georgi is a Principal Engineer at Amazon Web Services, where he builds identity systems that help organizations securely manage access and authentication at scale. His broader focus is on reliable, high-impact infrastructure that enables customers to operate confidently in the cloud. Outside of work, Georgi enjoys experimenting with new matcha latte recipes and going on long bike rides.

Sowjanya Rajavaram

Sowjanya Rajavaram

Sowjanya is a Sr Solutions Architect who specializes in Identity and Security in AWS. She works on helping customers of all sizes solve their identity and access management problems. She enjoys traveling and exploring new cultures and food.

Author

Laura Reith

Laura is an Identity Solutions Architect at AWS, where she thrives on helping customers overcome security and identity challenges. In her free time, she enjoys wreck diving and traveling around the world.

AWS Weekly Roundup: Claude Opus 4.7 in Amazon Bedrock, AWS Interconnect GA, and more (April 20, 2026)

Post Syndicated from Sébastien Stormacq original https://aws.amazon.com/blogs/aws/aws-weekly-roundup-claude-opus-4-7-in-amazon-bedrock-aws-interconnect-ga-and-more-april-20-2026/

Last week I had the honor of delivering a commencement speech at the University of Namur (uNamur) for their 2025 graduation ceremony.

uNamur Graduation Ceremony

Standing in front of freshly minted computer science graduates, I talked about the future of software development in the age of AI. My message to them was simple: AI will not make you obsolete. We’ve seen tools evolve over the decades, from punch cards to IDEs to AI-assisted coding, but the work remains yours, not the tool’s. The developers who will thrive are those who stay curious, think in systems, communicate with precision, and take ownership of what they build. The world needs more people with coding skills, not fewer. AI raises the bar on what we can accomplish, and that’s a good thing.

Now, let’s get into this week’s AWS news.

Headlines
Anthropic’s Claude Opus 4.7 is now available in Amazon Bedrock – Anthropic’s most intelligent Opus model is now available in Amazon Bedrock, with improved performance across coding, long-running agents, and professional knowledge work. Claude Opus 4.7 scores 64.3% on SWE-bench Pro and 87.6% on SWE-bench Verified, extending its lead in agentic coding with stronger long-horizon autonomy and complex code reasoning. It also does better on knowledge work tasks like document creation, financial analysis, and multi-step research.

The model runs on Bedrock’s next-generation inference engine with dynamic capacity allocation, adaptive thinking (letting Claude allocate thinking token budgets based on request complexity), and the full 1M token context window. It also adds high-resolution image support for better accuracy on charts, dense documents, and screen UIs. Claude Opus 4.7 is available at launch in US East (N. Virginia), Asia Pacific (Tokyo), Europe (Ireland), and Europe (Stockholm), with up to 10,000 requests per minute per account per Region.

AWS Interconnect is now generally available with a new option to simplify last-mile connectivity – AWS Interconnect brings two managed private connectivity capabilities to general availability. The first, AWS Interconnect – Multicloud, provides Layer 3 private connections between AWS VPCs and other cloud providers (Google Cloud available now, Azure and OCI coming later in 2026). Traffic flows over the AWS global backbone and the partner cloud’s private network, never over the public internet, with built-in MACsec encryption, multi-facility resiliency, and CloudWatch monitoring. AWS published the underlying specification on GitHub under Apache 2.0 so any cloud provider can become an Interconnect partner.

The second capability, AWS Interconnect – Last Mile, simplifies high-speed private connections from branch offices, data centers, and remote locations to AWS through existing network providers. It provisions 4 redundant connections across 2 physical locations automatically, configures BGP routing, activates MACsec encryption and Jumbo Frames by default, and offers bandwidth from 1 Gbps to 100 Gbps adjustable from the console without reprovisioning. Last Mile launches in US East (N. Virginia) with Lumen as the initial partner.

Last week’s launches
Here are some launches and updates from this past week that caught my attention:

  • Amazon ECR pull through cache now supports referrer discovery and sync — ECR’s pull through cache now automatically discovers and syncs OCI referrers (image signatures, SBOMs, attestations) from upstream registries into your private repositories. This means end-to-end image signature verification and SBOM discovery workflows work without client-side workarounds.
  • AWS Transform is now available in Kiro and VS Code — AWS Transform, the agentic migration and modernization factory, is now accessible via Kiro (as a Power) and VS Code (as an extension). You can run custom transformations for common patterns like Java/Python/Node.js version upgrades and AWS SDK migrations directly from your IDE, with job state shared across the web console, CLI, and IDE.
  • Aurora DSQL launches connector for PHP — A new Aurora DSQL Connector for PHP (PDO_PGSQL) simplifies building PHP applications on Aurora DSQL by automatically generating IAM tokens, handling SSL configuration, managing connection pooling, and providing opt-in optimistic concurrency control retry with exponential backoff.
  • Amazon Q supports document-level access controls for Google Drive — Amazon Q now enforces document-level access controls for Google Drive knowledge bases, combining indexed ACL replication for fast pre-retrieval filtering with real-time permission checks against Google Drive at query time.
  • AWS Secrets Manager now supports hybrid post-quantum TLS — Secrets Manager now supports hybrid post-quantum key exchange using ML-KEM to protect secrets against both current and future quantum computing threats. This is automatically enabled in Secrets Manager Agent 2.0.0+, Lambda Extension v19+, and the CSI Driver 2.0.0+.
  • Amazon EC2 C8in and C8ib instances are now generally available — Powered by custom 6th-gen Intel Xeon Scalable processors and 6th-gen AWS Nitro cards, these instances deliver up to 43% higher performance over C6in. C8in offers 600 Gbps network bandwidth (highest among enhanced networking EC2 instances), while C8ib delivers up to 300 Gbps EBS bandwidth (highest among non-accelerated compute instances), scaling up to 384 vCPUs.

For a full list of AWS announcements, be sure to keep an eye on the What’s New with AWS page.

Other AWS news
Here are some additional posts and resources that you might find interesting:

  • Navigating enterprise networking challenges with Amazon EKS Auto Mode — This post explains how EKS Auto Mode automates Kubernetes networking infrastructure including VPC CNI configuration, load balancer provisioning, and DNS management, reducing operational overhead while preserving enterprise security controls.
  • Introducing granular cost attribution for Amazon Bedrock — My colleague Micah talked about this feature last week already, but the blog post came out after last week’s roundup. Amazon Bedrock now automatically attributes inference costs to the specific IAM principal that made each API call, with results flowing into AWS Cost and Usage Reports (CUR 2.0). You can aggregate costs by team, project, or cost center using IAM principal tags and session tags.
  • Accelerate development workflows with Amazon EBS Volume Clones — EBS Volume Clones let you create instant, point-in-time copies of EBS volumes that are immediately usable without waiting for data transfer. The post highlights use cases including dev/test environment refreshes, disaster recovery testing, and CI/CD pipeline acceleration.
  • Modernize VB6 applications at scale with AWS Transform Custom — A walkthrough of using AWS Transform Custom’s agentic AI capabilities to convert legacy Visual Basic 6.0 applications to modern C# ASP.NET Core web applications, addressing challenges like COM dependencies, ADO-to-Entity Framework migration, and VB6 forms-to-Blazor UI conversion.
  • Migrating and decomposing APIs with zero-downtime using CloudFront — A zero-downtime API migration strategy using CloudFront Functions with CloudFront KeyValueStore for intelligent, user-aware traffic routing based on the Strangler Fig pattern. This is similar to what AWS Migration Hub Refactor Spaces offers, but implemented with just CloudFront and edge functions.

Upcoming AWS events
Check your calendar and sign up for upcoming AWS events:

  • AWS Events — Browse upcoming AWS-led in-person and virtual events, startup events, and developer-focused events near you.
  • AWS Power Hour — Weekly live training sessions on Twitch covering various AWS topics.
  • Community.aws — Find community-led events, meetups, and user groups in your area.

That’s all for this week. Check back next Monday for another Weekly Roundup!

— seb

AWS Interconnect is now generally available, with a new option to simplify last-mile connectivity

Post Syndicated from Sébastien Stormacq original https://aws.amazon.com/blogs/aws/aws-interconnect-is-now-generally-available-with-a-new-option-to-simplify-last-mile-connectivity/

Today, we’re announcing the general availability of AWS Interconnect – multicloud, a managed private connectivity service that connects your Amazon Virtual Private Cloud (Amazon VPC) directly to VPCs on other cloud providers. We’re also introducing AWS Interconnect – last mile, a new capability that simplifies how you establish high-speed, private connections to AWS from your branch offices, data centers, and remote locations through your existing network providers.

Large enterprises increasingly run workloads across multiple cloud providers, whether to use specialized services, meet data residency requirements, or support teams that have standardized on different providers. Connecting those environments reliably and securely has historically required significant coordination: managing VPN tunnels, working with colocation facilities, and configuring third-party network fabrics. The result is that your networking team spends time on undifferentiated heavy lifting instead of focusing on the applications that matter to your business.

AWS Interconnect is the answer to these challenges. It is a managed connectivity service that simplifies connectivity into AWS. Interconnect provides you the ability to establish private, high-speed network connections with dedicated bandwidth to and from AWS across hybrid and multicloud environments. You can configure resilient, end-to-end connectivity with ease in a few clicks through the AWS Console by selecting your location, partner, or cloud provider, preferred Region, and bandwidth requirements, removing the friction of discovering partners and the complexity of manual network configurations.

It comes with two capabilities: multicloud connectivity between AWS and other cloud providers, and last-mile connectivity between AWS and your private on-premises networks. Both capabilities are built on the same principle: a fully managed, turnkey experience that removes the infrastructure complexity from your team.

AWS Interconnect – multicloud
AWS Interconnect – multicloud gives you a private, managed Layer 3 connection between your AWS environment and other cloud providers, starting with Google Cloud, and Microsoft Azure coming later in 2026. Traffic flows entirely over the AWS global backbone and the partner cloud’s private network, so it never traverses the public internet. This means you get predictable latency, consistent throughput, and isolation from internet congestion without having to manage any physical infrastructure yourself.

Security is built in by default. Every connection uses IEEE 802.1AE MACsec encryption on the physical links between AWS routers and the partner cloud provider’s routers at the interconnection facilities. You don’t need to configure these separately. Note that each cloud provider manages encryption independently on its own backbone, so you should review the encryption documentation for your specific deployment to verify it meets your compliance requirements. Resiliency is also built in: each connection spans multiple logical links distributed across at least two physical facilities, so a single device or building failure does not interrupt your connectivity.

AWS Interconnect - multicloud - architectureFor monitoring, AWS Interconnect – multicloud integrates with Amazon CloudWatch. You get a Network Synthetic Monitor included with each connection to track round-trip latency and packet loss, and bandwidth utilization metrics to support capacity planning.

AWS has published the underlying specification on GitHub under the Apache 2.0 license, providing any cloud service provider the opportunity to collaborate with AWS Interconnect – multicloud. To become an AWS Interconnect partner, cloud providers must implement the technical specification and meet AWS operational requirements, including resiliency standards, support commitments, and service level agreements.

How it works
Provisioning a connection takes minutes. I create the connection from the AWS Direct Connect console. I start from the AWS Interconnect section and select Google Cloud as the provider. I select my source and destination regions. I specify bandwidth, and provide my Google Cloud project ID. AWS generates an activation key that I use on the Google Cloud side to complete the connection. Routes propagate automatically in both directions, and my workloads can start exchanging data shortly after.

AWS INterconnect - multicloud - provisionningFor this demo, I start with a single VPC and I connect it to a Google Cloud VPC. I use a Direct Connect Gateway. It’s the simplest path: one connection, one attachment, and my workloads on both sides can start talking to each other in minutes.

Step 1: request an interconnect in the AWS Management Console.

I navigate to AWS Direct Connect, AWS Interconnect and I select Create. I first choose the cloud provider I want to connect to. In this example, Google Cloud.

AWS interconnect - 1Then, I choose the AWS Region (eu-central-1) and the Google Cloud Region (europe-west3).

AWS interconnect - 2On step 3, I enter Description,I choose the Bandwidth, the Direct Connect gateway to attach, and the ID of my Google Cloud project.

AWS interconnect - 3

After reviewing and confirming the request, the console gives me an activation key. I will use that key to validate the request on the Google cloud side.

AWS interconnect - 4

Step 2: create the transport and VPC Peering resources on my Google Cloud Platform (GCP) account.

Now that I have the activation key, I continue the process on the GCP side. At the time of this writing, no web-based console was available. I choose to use the GCP command line (CLI) instead. I take note of the CIDR range in the GCP VPC subnet in the europe-west3 region. Then, I open a Terminal and type:

gcloud network-connectivity transports create aws-news-blog \
    --region=europe-west3  \
    --activation-key=${ACTIVATION_KEY} \
    --network=default \
    --advertised-routes=10.156.0.0/20

Create request issued for: [aws-news-blog]
...
peeringNetwork: projects/oxxxp-tp/global/networks/transport-9xxxf-vpc
...
state: PENDING_CONFIG
updateTime: '2026-03-19T09:30:51.103979219Z'

It takes a couple of minutes for the command to complete. Once the command returns, I create a peering between my GCP VPC and the new transport I just created. I can do that in the GCP console or with the gcloud command line. Because I was using the Terminal for the previous command, I continued with the command line:

gcloud compute networks peerings create aws-news-blog \
      --network=default \
      --peer-network=projects/oxxxp-tp/global/networks/transport-9xxxf-vpc \
      --import-custom-routes \
      --export-custom-routes

The network name is the name of my GCP VPC. The peer network is given in the output of the previous command.

Once completed, I can verify the peering in the GCP console.
AWS Interconnect - Peering in the Google console

In the AWS Interconnect console, I verify the status is available.

AWS Interconnect availableIn the AWS Direct Connect console, under Direct Connect gateways, I see the attachment to the new interconnect.

AWS INterconnect attachment

Step 3: associate the new gateway on the AWS side

I select Gateway associations and Associate gateway to attach the Virtual Private Gateway (VGW) that I created before starting this demo (pay attention to use a VGW in the same AWS Region as the interconnect)

AWS Interconnect associate CGW

You don’t need to configure the network routing on the GCP side. On AWS, there is a final step: add a route entry in your VPC Route tables to send all traffic to the GCP IP address range through the Virtual Gateway.

VPC Route to the VGW

Once the network setup is done. I start two compute instances, one on AWS and one on GCP.

On AWS, I verify the Security Group accepts ingress traffic on TCP:8080. I connect to the machine and I start a minimal web server:

python3 -c \
"from http.server import HTTPServer, BaseHTTPRequestHandler 
class H(BaseHTTPRequestHandler):
   def do_GET(self):
      self.send_response(200);self.end_headers()
      self.wfile.write(b'Hello AWS World!\n\n')
HTTPServer(('',8080),H).serve_forever()"

On the GCP side, I open a SSH session to the machine and I call the AWS web server by its private IP address.

AWS Interconnect : curl from GCP to AWS

Et voilà! I have a private network route between my two networks, entirely managed by the two Cloud Service Providers.

Things to know
There are a couple of configuration options that you should keep in mind:

  • When connecting networks, pay attention to the IP addresses range on both sides. The GCP and AWS VPC ranges can’t overlap. For this demo, the default range on AWS was 172.31.0.0/16and the default on GCP was 10.156.0.0/20. I was able to proceed with these default values.
  • You can configure IPV4, IPV6, or both on each side. You must select the same option on both sides.
  • The Maximum Transmission Unit (MTU) must be the same on both VPC. The default values for AWS VPCs and GCP VPCs are not. MTU is the largest packet size, in bytes, that a network interface can transmit without fragmentation. Mismatched MTU sizes between peered VPCs cause packet drops or fragmentation, leading to silent data loss, degraded throughput, and broken connections across the interconnect.
  • For more details, refer to the GCP Partner Cross Cloud Interconnect and the AWS Interconnect User Guide.

Reference architectures
When your deployment grows and you have multiple VPCs in a single region, AWS Transit Gateway gives you a centralized routing hub to connect them all through a single Interconnect attachment. You can segment traffic between environments, apply consistent routing policies, and integrate AWS Network Firewall if you need to inspect what crosses the cloud boundary.

And when you’re operating at global scale, with workloads spread across multiple AWS Regions and multiple Google Cloud environments, AWS Cloud WAN extends that same model across the world. Any region in your network can reach any Interconnect attachment globally, with centralized policy management and segment-based routing that applies consistently everywhere you operate.

My colleagues Alexandra and Santiago documented these reference architectures in their blog post: Build resilient and scalable multicloud connectivity architectures with AWS Interconnect – multicloud.

AWS Interconnect – last mile
Based on the same architecture and design as AWS Interconnect – multicloud, AWS Interconnect – last mile provides the ability to connect your on-premises or remote location to AWS through a participating network provider’s last-mile infrastructure, directly from the AWS Management Console.

The onboarding process mirrors AWS Interconnect – multicloud: you select a provider, authenticate, and specify your connection endpoints and bandwidth. AWS generates an activation key that you provide in the provider console to complete the configuration. AWS Interconnect – last mile automatically provisions four redundant connections across two physical locations, configures BGP routing, and activates MACsec encryption and Jumbo Frames by default. The result is a resilient private connection to AWS that aligns with best practices, without requiring you to manually configure networking components.

AWS Interconnect - lastmile

AWS Interconnect – last mile supports bandwidths from 1 Gbps to 100 Gbps, and you can adjust bandwidth from the console without reprovisioning. The service includes a 99.99% availability SLA up to the Direct Connect port and bundles CloudWatch Network Synthetic Monitor for connection health monitoring. Just like AWS Interconnect – multicloud, AWS Interconnect – last mile attaches to a Direct Connect Gateway, which connects to your Virtual Private Gateway, Transit Gateway, or AWS Cloud WAN deployment. For more details, refer to the AWS Interconnect User Guide.

Scott Yow, SVP Product at Lumen Technologies, wrote:

By combining AWS Interconnect – last mile with Lumen fiber network and Cloud Interconnect, we simplify the last-mile complexity that often slows cloud adoption and enable a faster, and more resilient path to AWS for customers.

Pricing and availability
AWS Interconnect – multicloud and AWS Interconnect – last mile pricing is based on a flat hourly rate for the capacity you request, billed prorata by the hour. You select the bandwidth tier that fits your workload needs.

AWS Interconnect – multicloud pricing varies by region pair: a connection between US East (N. Virginia) and Google Cloud N. Virginia is priced differently from a connection between US East (N. Virginia) and a more distant region. When you use AWS Cloud WAN, the global any-to-any routing model means traffic can traverse multiple regions, which affects the total cost of your deployment. I recommend reviewing the AWS Interconnect pricing page for the full rate card by region pair and capacity tier before sizing your connection.

AWS Interconnect – multicloud is available today in five region pairs: US East (N. Virginia) to Google Cloud N. Virginia, US West (N. California) to Google Cloud Los Angeles, US West (Oregon) to Google Cloud Oregon, Europe (London) to Google Cloud London, and Europe (Frankfurt) to Google Cloud Frankfurt. Microsoft Azure support is coming later in 2026.

AWS Interconnect – last mile is launching in US East (N. Virginia) with Lumen as the initial partner. Additional partners, including AT&T and Megaport, are in progress, and additional regions are planned.

To get started with AWS Interconnect, visit the AWS Direct Connect console and select AWS Interconnect from the navigation menu.

I’d love to hear how you’re using AWS Interconnect in your environment. Leave a comment below or reach out through the AWS re:Post community.

— seb

Enhance email security using VPC endpoints with Amazon SES Manager

Post Syndicated from Gabrielle Zhou original https://aws.amazon.com/blogs/messaging-and-targeting/enhance-email-security-using-vpc-endpoints-with-amazon-ses-manager/

Organizations managing on-premises email infrastructure face a critical challenge: how to modernize email systems while maintaining strict security and compliance standards. For healthcare providers, financial institutions, and government agencies, email messages often contain sensitive data that must remain on private networks throughout processing.

The virtual private cloud (VPC) endpoint feature of Amazon Simple Email Service (Amazon SES) Mail Manager addresses this challenge by enabling SMTP messages to remain on your private network throughout processing, routing, and compliance logging before final delivery. This post walks you through implementing this solution to securely modernize your email infrastructure.

Consider this scenario: You’re responsible for a healthcare organization’s email infrastructure that processes thousands of patient communications daily. Your on-premises Exchange servers are aging, maintenance costs are climbing, and your organization is moving workloads to AWS. Your security team requires that email processing for sensitive patient communications—including workflow processing, temporary storage, rule-based routing, and compliance logging—remain within private, controlled networks until ready for final delivery. The Amazon SES Mail Manager VPC endpoint feature addresses this requirement by maintaining network-level isolation for email operations from generation through processing, minimizing data exposure, meeting compliance requirements, and providing defense-in-depth security before final message delivery.

This post demonstrates how to implement VPC endpoints with Amazon SES Mail Manager using exercises from the Amazon SES Mail Manager workshop. We show how to configure VPC endpoints, security groups, and ingress endpoints to maintain private network connectivity for your email processing workflows.

Solution overview

Our approach combines AWS services to create a secure, private email infrastructure:

This solution requires your applications to run within a VPC or have established connectivity between your on-premises network and Amazon VPC through AWS Direct Connect or VPN. For guidance on connecting on-premises networks to AWS, refer to Hybrid network connections.

The following diagram illustrates the solution architecture.

The workflow consists of the following steps:

  1. Amazon Elastic Compute Cloud (Amazon EC2) instances running the sender email application on subnet 10.0.0.0/18 connect to the Amazon SES Mail Manager ingress endpoint through a VPC endpoint.
  2. Sender credentials are retrieved securely from Secrets Manager.
  3. AWS KMS decrypts credentials using your managed encryption keys.
  4. Authenticated email traffic flows securely to SES Amazon SES Mail Manager.

Prerequisites

Before beginning your migration, ensure you have the following:

  • AWS account – Use an AWS account with appropriate permissions for creating and managing a VPC, Secrets Manager, AWS KMS, and Amazon SES. Make sure AWS Identity and Access Management (IAM) policies follow least privilege principles.
  • Existing VPC infrastructure – Use a VPC that hosts your applications in the same AWS account and AWS Region as Amazon SES. For more information, see Plan your VPC.
  • Amazon SES configured – Configure Amazon SES in the same Region and AWS account.
  • Network connectivity – Deploy application servers either on premises with network connectivity to your VPC using Direct Connect or VPN, or already running within the VPC.

For this example, we use Linux SMTP commands from an EC2 instance in the VPC to connect to the Amazon SES Mail Manager ingress endpoint through a VPC endpoint on port 587.

Create traffic policy

Create an Amazon SES Mail Manager traffic policy to filter incoming messages by a combination of recipient address, sender IP address range, and TLS protocol version (1.2 or 1.3). For more details about Amazon SES Mail Manager traffic policies, refer to Traffic policies and policy statements. In this example, we use a traffic policy with minimum TLS version of 1.2.

Complete the following steps:

  1. Open the Amazon SES console in the target Region.
  2. In the navigation pane, under SES Mail Manager, choose Traffic policies.
  3. Choose Create traffic policy.
  4. For Policy name, enter a descriptive name, such as first-traffic-policy.
  5. For Default action, choose Deny.
  6. Choose Add new policy statement.
  7. For Allow or deny properties, choose Allow.
  8. For Properties, choose TLS protocol version.
  9. For Operator, choose Minimum version.
  10. For Value, choose TLS 1.2.
  11. Choose Create traffic policy.

Create rule set

Rule sets are containers for an ordered set of rules that determine how the messages are processed. For more information, see Rule sets and rules. In this example, we use the archive rule to archive all emails processed by Amazon SES Mail Manager.

Complete the following steps:

  1. On the Amazon SES console, under Amazon SES Mail Manager in the navigation pane, choose Rule sets.
  2. Choose Create rule set.
  3. Name the rule (for example, first-rule-set) and choose Create rule set.
  4. Choose Create new rule, then choose Create new rule again.
  5. Under Rule settings, name the rule (for example, archive_all).
  6. Under Actions, choose Add new action.
  7. Chose Archive.
  8. Choose Create archive.
  9. Give the archive a name, such as archive_all.
  10. Set a retention period (3 months for testing).
  11. Choose Create archive.

  1. For Archive resource name, choose archive_all.
  2. Choose Save rule set.

Create security group

Complete the following steps to create a security group:

  1. On the Amazon VPC console, under Security in the navigation pane, choose Security groups.
  2. Choose Create security group.
  3. For Security group name, provide a name that uniquely identifies the security group. For this example, we name the security group my-sg-mail-manager.
  4. For Description, describe the purpose of this security group.
  5. For VPC, choose the VPC that hosts your applications.
  6. For Inbound rules, choose Add rule.
  7. For Type, choose SMTP.
  8. For Source, enter the IP range of your private subnet.
  9. Choose Add rule again.
  10. For Port range, enter 587 and the IP range of your private subnet.
  11. Choose Create security group.

Create VPC endpoint

VPC endpoints make it possible to keep your email traffic within your private AWS network. Complete the following steps to create a VPC endpoint:

  1. Open the Amazon VPC console in the target Region.
  2. Under PrivateLink and Lattice in the navigation pane, choose Endpoints.
  3. Choose Create endpoint.
  4. For Name tag, enter an optional tag, such as mm-vpce-auth-ingress-endpoint.
  5. Select AWS services.
  6. For Services, enter mail-manager to search for Amazon SES Mail Manager VPC endpoints.
  7. Select com.amazonaws.us-east-1.mail-manager-smtp.auth.fips.

  1. For VPC, choose the VPC that hosts your applications.
  2. For DNS name, select Enable DNS name
  3. For DNS record IP type, select IPv4.
  4. Under Subnets, select all Availability Zones and choose the subnet ID for each subnet.
  5. For IP type, select IPv4.

  1. For Security groups, select the group my-sg-mail-manager.
  2. Choose Create endpoint.

Create ingress endpoint

Complete the following steps to create an authenticated ingress endpoint using Secrets Manager and AWS KMS:

  1. On the Amazon SES console, under Amazon SES Mail Manager in the navigation pane, choose Ingress endpoints.
  2. Choose Create ingress endpoint.
  3. For Ingress endpoint name, enter a unique name for the ingress endpoint. For this example, we use my-authenticated-ingress-endpoint.
  4. For Type, choose Authenticated.
  5. For Authentication type, choose Secret.
  6. Choose Create new, which will open a new tab.
  7. For Secret type, choose Other type of secret.
  8. Under Key/value pairs, enter password as the key (anything else will cause authentication to fail), then enter a password as the value.
  9. For Encryption Key, choose Add new key, which will open a new tab.
  10. Choose Create key.
  11. Keep the default values for Key type and Key usage and choose Next.

  1. For Alias, enter a unique name for your custom managed key. For this example, we use my-mail-manager-key.
  2. For Description, describe the purpose of the key.
  3. Choose Next.

  1. For Key administrators, choose any users (other than yourself) or roles you want to permit to administer the key, then choose Next.
  2. For Key users, choose any users (other than yourself) or roles you want to permit to use the key, then choose Next.
  3. For Key policy, choose Edit, then enter the following KMS key policy into the key policy JSON text editor at the "statement" level by adding it as an additional statement separated by a comma. Replace the Region and account number with your own.
{
    "Effect": "Allow",
    "Principal": {
        "Service": "ses.amazonaws.com"
    },
    "Action": "kms:Decrypt",
    "Resource": "*",
    "Condition": {
        "StringEquals": {
           "kms:ViaService": "secretsmanager.us-east-1.amazonaws.com",
            "aws:SourceAccount": "000000000000"
        },
        "ArnLike": {
            "aws:SourceArn": "arn:aws:ses:us-east-1:000000000000:mailmanager-ingress-point/*"
        }
    }
}
  1. Choose Next.
  2. Review and choose Finish.
  3. Switch to the Secrets Manager tab and choose the refresh icon.
  4. Choose the KMS key you just created, then choose Next.

  1. For Secret name, provide a unique name for the secret. For this example, we use my-mail-manager-secret.
  2. For Description, describe the purpose for the secret.
  3. For Resource permissions, replace the example JSON code in the editor with the following policy. Replace the Region and the account number with your own.
{
    "Version": "2012-10-17",
    "Id": "Id",
    "Statement": [
        {
            "Effect": "Allow",
            "Principal": {
                "Service": "ses.amazonaws.com"
            },
            "Action": "secretsmanager:GetSecretValue",
            "Resource": "*",
            "Condition": {
                "StringEquals": {
                    "aws:SourceAccount": "000000000000"
                },
                "ArnLike": {
                    "aws:SourceArn": "arn:aws:ses:us-east-1:000000000000:mailmanager-ingress-point/*"
                }
            }
        }
    ]
}
  1. Choose Save, then choose Next.
  2. Configuring automatic rotation is optional. We skip this step and choose Next.
  3. Review and choose Store.
  4. Switch back to the Amazon SES console tab to finish creating the ingress endpoint.
  5. For Secret ARN, choose Refresh list, then choose the secret you just created.
  6. For Rule set, choose first-rule-set.
  7. For Traffic policy, choose first-traffic-policy.
  8. For Network type, select Private.
  9. For VPC endpoint ID, choose mm-vpce-auth-ingress-endpoint.
  10. Choose Create ingress endpoint.

Test configuration

Complete the following steps to test your configuration:

  1. Open the Amazon VPC console in the target Region.
  2. Under PrivateLink and Lattice in the navigation pane, choose Endpoints.
  3. Choose the VPC endpoint ID of mm-vpce-auth-ingress-endpoint to open the details page.
  4. Find the DNS names for the VPC endpoint. The first DNS name on this list is the Regional DNS name of the VPC endpoint; copy this DNS name and save it on a notepad for later use.

  1. Open the Amazon SES console in the target Region.
  2. Under Amazon SES Mail Manager in the navigation pane, choose Ingress endpoints.
  3. Choose my-authenticated-ingress-endpoint.
  4. In the Authentication section, locate the SMTP user name (typically starts with inp-).

  1. Connect to your EC2 instance using SSH.
  2. Use the command line to send an email using the Amazon SES SMTP interface to test the connectivity. Replace the endpoint with the DNS name of the VPC endpoint you copied earlier.

The message 250 OK esllb73q6bd94cnq004ujd544f169sog39bc9ug1 indicates the message was successfully accepted by Amazon SES Mail Manager.

Clean up

When you’re done with this solution, clean up the resources you created including Mail Manager configurations, security groups, VPC endpoints, KMS keys, and Secrets Manager secrets to avoid additional charges.

Conclusion

In this post, we showed how to enhance email security by implementing Amazon SES Mail Manager with VPC endpoints. This solution can help you modernize your email infrastructure while maintaining network-level isolation and meeting enterprise compliance requirements.

To learn more about Amazon SES, see the Amazon SES Developer Guide. For additional security best practices, refer to AWS Best Practices for Security, Identity, & Compliance. To get started using Amazon SES Mail Manager, participate in an Amazon SES Mail Manager workshop event, explore the advanced workflow features of Amazon SES Mail Manager, and consider integrating with your existing monitoring and alerting systems.


About the authors

Introducing Amazon Route 53 Global Resolver for secure anycast DNS resolution (preview)

Post Syndicated from Esra Kayabali original https://aws.amazon.com/blogs/aws/introducing-amazon-route-53-global-resolver-for-secure-anycast-dns-resolution-preview/

Today, we’re announcing Amazon Route 53 Global Resolver, a new Amazon Route 53 service that provides secure and reliable DNS resolution globally for queries from anywhere (preview). You can use Global Resolver to resolve DNS queries to public domains on the internet and private domains associated with Route 53 private hosted zones. Route 53 Global Resolver offers network administrators a unified solution to resolve queries from authenticated clients and sources in on-premises data centers, branch offices, and remote locations through globally distributed anycast IP addresses. This service includes built-in security controls including DNS traffic filtering, support for encrypted queries, and centralized logging to help organizations reduce operational overhead while maintaining compliance with security requirements.

Organizations with hybrid deployments face operational complexity when managing DNS resolution across distributed environments. Resolving public internet domains and private application domains often requires maintaining split DNS infrastructure, which increases cost and administrative burden especially when replicating to multiple locations. Network administrators must configure custom forwarding solutions, deploy Route 53 Resolver endpoints for private domain resolution, and implement separate security controls across different locations. Additionally, they must configure and maintain multi-Region failover strategies for Route 53 Resolver endpoints and provide consistent security policy enforcement across all Regions while testing failover scenarios.

Route 53 Global Resolver has key capabilities that address these challenges. The service resolves both public internet domains and Route 53 private hosted zones, eliminating the need for separate split-DNS forwarding. It provides DNS resolution through multiple protocols, including DNS over UDP (Do53), DNS-over-HTTPS (DoH), and DNS-over-TLS (DoT). Each deployment provides a single set of common IPv4 and IPv6 anycast IP addresses that route queries to the nearest AWS Region, reducing latency for distributed client populations.

Route 53 Global Resolver provides integrated security features equivalent to Route 53 Resolver DNS Firewall. Administrators can configure filtering rules using AWS Managed Domain Lists that provide flexible controls with lists classified by DNS threats (malware, spam, phishing) or web content (adult sites, gambling, social networking) that might not be safe for work or create custom domain lists by importing domains from a file. Advanced threat protection detects and blocks domain generation algorithm (DGA) patterns and DNS tunneling attempts. For encrypted DNS traffic, Route 53 Global Resolver supports DoH and DoT protocols to protect queries from unauthorized access during transit.

Route 53 Global Resolver only accepts traffic from known clients that need to authenticate with the Resolver. For Do53, DoT, and DoH connections, administrators can configure IP and CIDR allowlists. For DoH and DoT connections, token-based authentication provides granular access control with customizable expiration periods and revocation capabilities. Administrators can assign tokens to specific client groups or individual devices based on organizational requirements.

Route 53 Global Resolver supports DNSSEC validation to verify the authenticity and integrity of DNS responses from public nameservers. It also includes EDNS Client Subnet support, which forwards client subnet information to enable more accurate geographic-based DNS responses from content delivery networks.

Getting started with Route 53 Global Resolver
This walkthrough shows how to configure Route 53 Global Resolver for an organization with offices on the US East and West coasts that needs to resolve both public domains and private applications hosted in Route 53 private hosted zones. To configure Route 53 Global Resolver, go to the AWS Management Console, choose Global resolvers from the navigation pane, and choose Create global resolver.

In the Resolver details section, enter a Resolver name such as corporate-dns-resolver. Add an optional description like DNS resolver for corporate offices and remote clients. In the Regions section, choose the AWS Regions where you want the resolver to operate, such as US East (N. Virginia) and US West (Oregon). The anycast architecture routes DNS queries from your clients to the nearest selected Region.

After the resolver is created, the console displays the resolver details, including the anycast IPv4 and IPv6 addresses that you will use for DNS queries. You can proceed to create a DNS view by choosing Create DNS view to configure client authentication and DNS query resolution settings.

In the Create DNS view section, enter a DNS view name such as primary-view and optionally add a Description like DNS view for corporate offices. A DNS view helps you create different logical groupings for your clients and sources, and determine the DNS resolution for those groups. This helps you maintain different DNS filtering rules and private hosted zone resolution policies for different clients in your organization.

For DNSSEC validation, choose Enable to verify the authenticity of DNS responses from public DNS servers. For Firewall rules fail open behavior, choose Disable to block DNS queries when firewall rules can’t be evaluated, which provides additional security. For EDNS client subnet, keep Enable selected to forward client location information to DNS servers, which allows content delivery networks to provide more accurate geographic responses. DNS view creation might take a few minutes to become operational.

After the DNS view is created and operational, configure DNS Firewall rules to filter network traffic by choosing Create rule. In the Create DNS Firewall rules section, enter a Rule name such as block-malware-domains and optionally add a description. For Rule configuration type, you can choose Customer managed domain lists, AWS managed domain lists provided by AWS or DNS Firewall Advanced protection.

For this walkthrough, choose AWS managed domain lists. In the Domain lists dropdown, choose one or more AWS managed lists such as Threat – Malware to block known malicious domains. You can leave Query type empty to apply the rule to all DNS query types. In this example, choose A to apply this rule only to IPv4 address queries. In the Rule action section, select Block to prevent DNS resolution for domains that match the selected lists. For Response to send for Block action, keep NODATA selected to indicate that the query was successful but no response is available, then choose Create rules.

The next step is to configure access sources to specify which IP addresses or CIDR blocks are allowed to send DNS queries to the resolver. Navigate to the Access sources tab in the DNS view and then choose Create access source.

In the Access source details section, enter a Rule name such as office-networks to identify the access source. In the CIDR block field, enter the IP address range for your offices to allow queries from that network. For Protocol, select Do53 for standard DNS queries over UDP or choose DoH or DoT if you want to require encrypted DNS connections from clients. After configuring these settings, choose Create access source to allow the specified network to send DNS queries to the resolver.

Next, navigate to the Access tokens tab in the DNS view to create token-based authentication for clients and choose Create access token. In the Access token details section, enter a Token name such as remote-clients-token. For Token expiry, select an expiration period from the dropdown based on your security requirements, such as 365 days for long-term client access, or choose a shorter duration like 30 days or 90 days for tighter access control. After configuring these settings, choose Create access token to generate the token, which clients can use to authenticate DoH and DoT connections to the resolver.

After the access token is created, navigate to the Private hosted zones tab in the DNS view to associate Route 53 private hosted zones with the DNS view so that the resolver can resolve queries for your private application domains. Choose Associate private hosted zone and in the Private hosted zones section, select a private hosted zone from the list that you want the resolver to handle. After selecting the zone, choose Associate to enable the resolver to respond to DNS queries for these private domains from your configured access sources.

With the DNS view configured, firewall rules created, access sources and tokens defined, and private hosted zones associated, the Route 53 Global Resolver setup is complete and ready to handle DNS queries from your configured clients.

After creating your Route 53 Global Resolver, you need to configure your DNS clients to send queries to the resolver’s anycast IP addresses. The configuration method depends on the access control you configured in your DNS view:

  • For IP-based access sources (CIDR blocks) – Configure your source clients to point DNS traffic to the Route 53 Global Resolver anycast IP addresses provided in the resolver details. Global Resolver will only allow access from allowlisted IPs that you have specified in your access sources. You can also associate the access sources to different DNS views to provide more granular DNS resolution views for different sets of IPs.
  • For access token–based authentication – Deploy the tokens on your clients to authenticate DoH and DoT connections with Route 53 Global Resolver. You must also configure your clients to point the DNS traffic to the Route 53 Global Resolver anycast IP addresses provided in the resolver details.

For detailed configuration instructions for your specific operating system and protocol, refer to the technical documentation.

Additional things to know
We’re renaming the existing Route 53 Resolver to Route 53 VPC Resolver. This naming change clarifies the architectural distinction between the two services. VPC Resolver operates Regionally within your VPCs to provide DNS resolution for resources in your Amazon VPC environment. VPC Resolver continues to support inbound and outbound resolver endpoints for hybrid DNS architectures within specific AWS Regions.

Route 53 Global Resolver complements Route 53 VPC Resolver by providing internet-reachable, global and private DNS resolution for on-premises and remote clients without requiring VPC deployment or private connections.

Existing VPC Resolver configurations remain unchanged and continue to function as configured. The renaming affects the service name in the AWS Management Console and documentation, but API operation names remain unchanged. If your architecture requires DNS resolution for resources within your VPCs, continue using VPC Resolver.

Join the preview
Route 53 Global Resolver reduces operational overhead by providing unified DNS resolution for public and private domains through a single managed service. The global anycast architecture improves reliability and reduces latency for distributed clients. Integrated security controls and centralized logging help organizations maintain consistent security policies across all locations while meeting compliance requirements.

To learn more about Amazon Route 53 Global Resolver, visit the Amazon Route 53 documentation.

You can start using Route 53 Global Resolver through the AWS Management Console in US East (N. Virginia), US East (Ohio), US West (N. California), US West (Oregon), Europe (Frankfurt), Europe (Ireland), Europe (London), Asia Pacific (Mumbai), Asia Pacific (Singapore), Asia Pacific (Tokyo), and Asia Pacific (Sydney) Regions.

— Esra

Secure Amazon Elastic VMware Service (Amazon EVS) with AWS Network Firewall

Post Syndicated from Sheng Chen original https://aws.amazon.com/blogs/architecture/secure-amazon-elastic-vmware-service-amazon-evs-with-aws-network-firewall/

Amazon Elastic VMware Service (Amazon EVS) helps organizations migrate, run, and scale VMware workloads natively on AWS. It delivers a VMware Cloud Foundation (VCF) environment that operates directly within your Amazon Virtual Private Cloud (Amazon VPC) on Amazon EC2 bare-metal instances. The solution helps customers accelerate cloud migrations and data center exits without needing to refactor existing applications.

For customers considering a hybrid cloud architecture, a unified network security solution is required to protect application traffic across Amazon EVS environments, Amazon VPCs, on-premises data centers and the internet. It also needs to provide a single point of control for firewall policy management, centralized logging, and monitoring to streamline network security operations.

AWS Network Firewall is a managed firewall and intrusion detection and prevention service (IDS/IPS) that can help address these requirements. Built on AWS managed infrastructure, it automatically scales with traffic demands while maintaining high availability and consistent performance. The service provides centralized policy management and traffic inspection across multiple VPCs and AWS accounts. Additionally, it provides comprehensive visibility and reporting through firewall log collections to Amazon Simple Storage Service (Amazon S3), Amazon CloudWatch Logs, or Amazon Data Firehose.

In this post, we demonstrate how to utilize AWS Network Firewall to secure an Amazon EVS environment, using a centralized inspection architecture across an EVS cluster, VPCs, on-premises data centers and the internet. We walk through the implementation steps to deploy this architecture using AWS Network Firewall and AWS Transit Gateway.

Architecture overview

AWS Network Firewall operates as a “bump-in-the-wire” solution, which transparently inspects and filters network traffic across Amazon VPCs. It is inserted directly into the traffic path by updating VPC or Transit Gateway route tables, allowing it to examine all packets without requiring any changes to the existing application flow patterns.

The following diagram depicts the architecture overview of our centralized inspection model using AWS Network Firewall.

Figure 1: Secure Amazon EVS with AWS Network Firewall using centralized inspection architecture

Figure 1: Secure Amazon EVS with AWS Network Firewall using centralized inspection architecture

The Amazon EVS environment is deployed directly within a customer VPC (i.e. EVS VPC), which consists of EVS VLAN subnets that form the underlay networks for VCF deployment. This infrastructure provides connectivity for NSX overlay networks, host management, vMotion, and vSANAmazon VPC Route Server enables dynamic routing between the underlay networks and overlay networks. For more information, see Concepts and components of Amazon EVS.

The architecture also includes a standard workload VPC (i.e. VPC01), and a Direct Connect Gateway connects to the on-premises data center via an AWS Direct Connect connection. We use a dedicated egress VPC with NAT gateways for centralized internet egress, and a separate ingress VPC with Application Load Balancers to terminate ingress web traffic and steer flows back to the target services.

With this architecture, the following traffic flow patterns can be inspected:

East-West Traffic:

  • Between EVS VPCs and Workload VPCs
  • Between Workload VPCs

North-South Traffic:

  • Between EVS/Workload VPCs and on-premises
  • Between EVS/Workload VPCs and internet
  • Between on-premises and internet

The centralized inspection architecture provides several benefits:

  • Single point of control for network security inspection across multiple VPCs
  • Enhanced rule enforcement across AWS infrastructure, on-premises resources, and the internet
  • Centralized logging and monitoring

For this demo we use the AWS Network Firewall native integration with AWS Transit Gateway capability to streamline firewall deployment and management. With a native firewall attachment, AWS automatically provisions and manages all the necessary VPC resources, reducing the operational overhead of managing subnets, route tables, and firewall endpoints within the inspection VPC.

Prerequisites

This post assumes familiarity with: AWS Command Line Interface (AWS CLI), Amazon VPC, Amazon EC2, NAT gateway, Application Load Balancer, Internet gateway, AWS Direct Connect, AWS Transit Gateway and the VMware VCF platform.

The following prerequisites are necessary to complete this solution.

  • An EVS VPC includes:
    • An Amazon EVS cluster (minimum 4x i4i nodes)
    • VPC CIDR: 10.0.0.0/16
    • NSX Segments CIDR: 192.168.0.0/19 (summarized)
    • A VPC Route Server deployed in the EVS VPC to receive NSX segment routes via BGP dynamic routing. Refer to the EVS User Guide for more details.
  • A Workload VPC (VPC01):
    • CIDR: 172.21.0.0/16
  • An Egress VPC:
    • CIDR: 172.23.0.0/16
    • 1x Internet Gateway
    • 1x NAT Gateway
  • An Ingress VPC:
    • CIDR: 172.24.0.0/16
    • 1x Internet Gateway
    • 1x Application Load Balancer
  • Optional: a Direct Connect Gateway:
    •  connecting to the on-premises environment (10.0.0.0/8)

Note: The CIDR blocks used in this example are for demo purposes only; change the address spaces to match your own networking environment. The design can also be scaled to include additional EVS environments and/or other VPCs based on workload needs.

Walkthrough

In this section, we walk through the implementation steps to deploy the centralized inspection architecture with AWS Network Firewall and AWS Transit Gateway. We focus on the overall network integration of the architecture without diving into the detailed configurations of AWS Network Firewall or Transit Gateway.

1. Create an AWS Transit Gateway

In the VPC console, create a Transit Gateway. Make sure to deselect the following options:

  • Default route table association
  • Default route table propagation

Create two empty transit gateway route tables and associate them with the Transit Gateway.

  • Pre-inspection route table: steers traffic into the AWS Network Firewall for centralized inspection
  • Post-inspection route table: returns traffic back to its original destination after inspection and is permitted by the AWS Network Firewall

2. Attach VPCs to the Transit Gateway

Attach all four VPCs (EVS, VPC01, Ingress, Egress) to the same Transit Gateway. The Direct Connect Gateway can also be attached to the Transit Gateway if AWS Network Firewall is needed to inspect traffic between the on-premises environment and AWS or the internet.

Figure 2: Attach VPCs to the Transit Gateway

Figure 2: Attach VPCs to the Transit Gateway

Associate all attachments to the pre-inspection Transit Gateway route table.

Figure 3: Associate VPC attachments to the pre-inspection route table

Figure 3: Associate VPC attachments to the pre-inspection route table

3. Create an AWS Network Firewall with Transit Gateway native integration

In the Network Firewall section of the VPC console, choose Create firewall.

At the Attachment type section, select Transit Gateway to enable native integration with the existing Transit Gateway.

Figure 4: Enable AWS Network Firewall native integration with Transit Gateway

Figure 4: Enable AWS Network Firewall native integration with Transit Gateway

At the Logging configuration, enable the following log types with CloudWatch log group as the log destination. Create a log group for each log type in the CloudWatch Console.

  • Alert: /anfw-centralized/anfw01/alert
  • Flow: /anfw-centralized/anfw01/flow

Create and associate an empty firewall policy to deploy the AWS Network Firewall instance. The firewall policy contains a list of rule groups that define how the firewall inspects and manages traffic. This empty firewall policy can be configured later.

With the Transit Gateway native integration enabled, a Transit Gateway attachment is automatically created for the AWS Network Firewall, with the resource type shown as Network Function. In addition, the Appliance Mode is automatically enabled for the firewall attachment to make sure the Transit Gateway continues to use the same Availability Zone (AZ) for the attachment over the lifetime of a flow.

Associate the firewall attachment to the post-inspection Transit Gateway route table.

Figure 5: AWS Network Firewall native attachment

Figure 5: AWS Network Firewall native attachment

4. Update Transit Gateway route tables

Update the pre-inspection Transit Gateway route table with a default route that points to the AWS Network Firewall attachment. This makes sure traffic that arrives to the Transit Gateway from all VPC attachments and the Direct Connect Gateway attachment is sent to the firewall for centralized inspection.

Figure 6: Transit Gateway pre-inspection route table

Figure 6: Transit Gateway pre-inspection route table

Add the following static routes to the post-inspection route table to direct return traffic back to each VPC and the Direct Connect Gateway accordingly.

Figure 7: Transit Gateway post-inspection route table

Figure 7: Transit Gateway post-inspection route table

5. Update VPC route tables

Finally, update route tables at each VPC as per the following table.

Make sure to add the following routes at the relevant VPC route tables:

  • EVS VPC and VPC01 have a default route (marked in blue) to steer all egress flows into AWS Network Firewall for centralized inspection.
  • Ingress VPC and Egress VPC have RFC-1918 routes (marked in green) to direct return traffic to the Transit Gateway.

Within the EVS VPC, notice the NSX segment routes are automatically propagated to the NSX uplink subnet route table and the private subnet route table via the VPC Route Server.

Figure 8: NSX uplink subnet route table within EVS VPC

Figure 8: NSX uplink subnet route table within EVS VPC

A centralized security inspection architecture has now been deployed for the EVS environment, using AWS Network Firewall with Transit Gateway native integration.

6. Testing

Egress inspection (FQDN filtering)

To test egress inspection from EVS VPC or VPC01 to the internet, create a stateful rule group for the firewall instance using FQDN filtering:

  • Rule group format: Domain list
  • Domain names: .google.com
  • Source IPs: 192.168.0.0/19, 172.21.0.0/16
  • Protocols: HTTP & HTTPS
  • Action: Allow

As expected, testing web access from a virtual machine (192.168.12.10) within the EVS environment to the allowed domain (i.e. google.com) is permitted by the AWS Network Firewall. However, access to unauthorized domain (i.e. facebook.com) is blocked at the firewall with an alert trigged, which can be verified at the CloudWatch log group at /aws/network-firewall/alert/.

Figure 9: Egress inspection from EVS to internet with FQDN filtering

Figure 9: Egress inspection from EVS to internet with FQDN filtering

Ingress inspection

Create another stateful rule group to allow Application Load Balancers deployed within the Ingress VPC to access a web server running in the EVS environment via HTTP protocol:

  • Rule group format: Standard stateful rule
  • Geographic IP Filtering: Disable Geographic IP filtering
  • Protocol: HTTP
  • Source: 172.24.0.0/16
  • Source Port: ANY
  • Destination: 192.168.12.10/32
  • Destination Port ANY
  • Traffic direction: Forward
  • Action: Alert

The CloudWatch firewall logs show an Application Load Balancer (172.24.6.45) from the Ingress VPC can establish HTTP connection to the EVS web server (192.168.12.10). Additionally, the Application Load Balancer has successfully registered the EVS web server as a remote IP target.

Figure 10: Ingress inspection from Ingress VPC to EVS

Figure 10: Ingress inspection from Ingress VPC to EVS

East-West inspection

For East-West inspection testing, update the previous stateful rule group to add a new rule to block ICMP traffic from VPC01 to the EVS VPC.

  • Rule group format: Standard stateful rule
  • Geographic IP Filtering: Disable Geographic IP filtering
  • Protocol: ICMP
  • Source: 172.21.0.0/16
  • Source Port: ANY
  • Destination: 192.168.0.0/19
  • Destination Port: ANY
  • Action: Drop

As a result, pings from an EC2 instance (172.21.128.4) from VPC01 to the EVS web server (192.168.12.10) are being dropped.

Figure 11: East-West Inspection from VPC01 to EVS

Figure 11: East-West Inspection from VPC01 to EVS

Conclusion

In this post, we demonstrated how to utilize AWS Network Firewall to secure Amazon EVS workloads and to provide centralized traffic inspection between Amazon EVS environments, Amazon VPCs, on-premises data centers, and the internet. We walked through the implementation steps for deploying the centralized inspection architecture using AWS Network Firewall and AWS Transit Gateway.

To learn more, review these resources:


About the authors

Introducing AWS RTB Fabric for real-time advertising technology workloads

Post Syndicated from Betty Zheng (郑予彬) original https://aws.amazon.com/blogs/aws/introducing-aws-rtb-fabric-for-real-time-advertising-technology-workloads/

Today, we’re announcing AWS RTB Fabric, a fully managed service purpose built for real-time bidding (RTB) advertising workloads. The service helps advertising technology (AdTech) companies seamlessly connect with their supply and demand partners, such as Amazon Ads, GumGum, Kargo, MobileFuse, Sovrn, TripleLift, Viant, Yieldmo and more, to run high-volume, latency-sensitive RTB workloads on Amazon Web Services (AWS) with consistent single-digit millisecond performance and up to 80% lower networking costs compared to standard networking costs.

AWS RTB Fabric provides a dedicated, high-performance network environment for RTB workloads and partner integrations without requiring colocated, on-premises infrastructure or upfront commitments. The following diagram shows the high-level architecture of RTB Fabric.

AWS RTB Fabric also includes modules, a capability that helps customers bring their own and partner applications securely into the compute environment used for real-time bidding. Modules support containerized applications and foundation models (FMs) that can enhance transaction efficiency and bidding effectiveness. At launch, AWS RTB Fabric includes modules for optimizing traffic management, improving bid efficiency, and increasing bid response rates, all running inline within the service for consistent low-latency execution.

The growth of programmatic advertising has created a need for low-latency, cost-efficient infrastructure to support RTB workloads. AdTech companies process millions of bid requests per second across publishers, supply-side platforms (SSPs), and demand-side platforms (DSPs). These workloads are highly sensitive to latency because most RTB auctions must complete within 200–300 milliseconds and require reliable, high-speed exchange of OpenRTB requests and responses among multiple partners. Many companies have addressed this by deploying infrastructure in colocation data centers near key partners, which reduces latency but adds operational complexity, long provisioning cycles, and high costs. Others have turned to cloud infrastructure to gain elasticity and scale, but they often face complex provisioning, partner-specific connectivity, and long-term commitments to achieve cost efficiency. These gaps add operational overhead and limit agility. AWS RTB Fabric solves these challenges by providing a managed private network built for RTB workloads that delivers consistent performance, simplifies partner onboarding, and achieves predictable cost efficiency without the burden of maintaining colocation or custom networking setups.

Key capabilities
AWS RTB Fabric introduces a managed foundation for running RTB workloads at scale. The service provides the following key capabilities:

  • Simplified connectivity to AdTech partners – When you register an RTB Fabric gateway, the service automatically generates secure endpoints that can be shared with selected partners. Using the AWS RTB Fabric API, you can create optimized, private connections to exchange RTB traffic securely across different environments. External Links are also available to connect with partners who aren’t using RTB Fabric, such as those operating on premises or in third-party cloud environments. This approach shortens integration time and simplifies collaboration among AdTech participants.
  • Dedicated network for low-latency advertising transactions – AWS RTB Fabric provides a managed, high-performance network layer optimized for OpenRTB communication. It connects AdTech participants such as SSPs, DSPs, and publishers through private, high-speed links that deliver consistent single-digit millisecond latency. The service automatically optimizes routing paths to maintain predictable performance and reduce networking costs, without requiring manual peering or configuration.
  • Pricing model aligned with RTB economics – AWS RTB Fabric uses a transaction-based pricing model designed to align with programmatic advertising economics. Customers are billed per billion transactions, providing predictable infrastructure costs that align with how advertising exchanges, SSPs, and DSPs operate.
  • Built-in traffic management modules – AWS RTB Fabric includes configurable modules that help AdTech workloads operate efficiently and reliably. Modules such as Rate Limiter, OpenRTB Filter, and Error Masking help you control request volume, validate message formats, and manage response handling directly in the network path. These modules execute inline within the AWS RTB Fabric environment, maintaining network-speed performance without adding application-level latency. All configurations are managed through the AWS RTB Fabric API, so you can define and update rules programmatically as your workloads scale.

Getting started
Today, you can start building with AWS RTB Fabric using the AWS Management Console, AWS Command Line Interface (AWS CLI), or infrastructure-as-code (IaC) tools such as AWS CloudFormation and Terraform.

The console provides a visual entry point to view and manage RTB gateways and links, as shown on the Dashboard of the AWS RTB Fabric console.

You can also use the AWS CLI to configure gateways, create links, and manage traffic programmatically. When I started building with AWS RTB Fabric, I used the AWS CLI to configure everything from gateway creation to link setup and traffic monitoring. The setup ran inside my Amazon Virtual Private Cloud (Amazon VPC) endpoint while AWS managed the low-latency infrastructure that connected workloads.

To begin, I created a requester gateway to send bid requests and a responder gateway to receive and process bid responses. These gateways act as secure communication points within the AWS RTB Fabric.

# Create a requester gateway with required parameters
aws rtbfabric create-requester-gateway \
  --description "My RTB requester gateway" \
  --vpc-id vpc-12345678 \
  --subnet-ids subnet-abc12345 subnet-def67890 \
  --security-group-ids sg-12345678 \
  --client-token "unique-client-token-123"
# Create a responder gateway with required parameters
aws rtbfabric create-responder-gateway \
  --description "My RTB responder gateway" \
  --vpc-id vpc-01f345ad6524a6d7 \
  --subnet-ids subnet-abc12345 subnet-def67890 \
  --security-group-ids sg-12345678 \
  --dns-name responder.example.com \
  --port 443 \
  --protocol HTTPS

After both gateways were active, I created a link from the requester to the responder to establish a private, low-latency communication path for OpenRTB traffic. The link handled routing and load balancing automatically.

# Requester account creating a link from requester gateway to a responder gateway
aws rtbfabric create-link \
  --gateway-id rtb-gw-requester123 \
  --peer-gateway-id rtb-gw-responder456 \
  --log-settings '{"applicationLogs:{"sampling":"errorLog":10.0,"filterLog":10.0}}'
# Responder account accepting a link from requester gateway to responder gateway
aws rtbfabric accept-link \
  --gateway-id rtb-gw-responder456 \
  --link-id link-reqtoresplink789 \
  --log-settings '{"applicationLogs:{"sampling":"errorLog":10.0,"filterLog":10.0}}'

I also connected with external partners using External Links, which extended my RTB workloads to on-premises or third-party environments while maintaining the same latency and security characteristics.

# Create an inbound external link endpoint for an external partner to send bid requests to
aws rtbfabric create-inbound-external-link \
  --gateway-id rtb-gw-responder456
# Create an outbound external link for sending bid requests to an external partner
aws rtbfabric create-outbound-external-link \
  --gateway-id rtb-gw-requester123 \
  --public-endpoint "https://my-external-partner-responder.com"

To manage traffic efficiently, I added modules directly into the data path. The Rate Limiter module controlled request volume, and the OpenRTB Filter validated message formats inline at network speed.

# Attach a rate limiting module
aws rtbfabric update-link-module-flow \
  --gateway-id rtb-gw-responder456 \
  --link-id link-toresponder789 \
  --modules '{"name":"RateLimiter":"moduleParameters":{"rateLimiter":{"tps":10000}}}'

Finally, I used Amazon CloudWatch to monitor throughput, latency, and module performance, and I exported logs to Amazon Simple Storage Service (Amazon S3) for auditing and optimization.

All configurations can also be automated with AWS CloudFormation or Terraform, allowing consistent, repeatable deployment across multiple environments. With RTB Fabric, I could focus on optimizing bidding logic while AWS maintained predictable, single-digit millisecond performance across my AdTech partners.

For more details, refer to the AWS RTB Fabric User Guide.

Now available
AWS RTB Fabric is available today in the following AWS Regions: US East (N. Virginia), US West (Oregon), Asia Pacific (Singapore), Asia Pacific (Tokyo), Europe (Frankfurt), and Europe (Ireland).

AWS RTB Fabric is continually evolving to address the changing needs of the AdTech industry. The service expands its capabilities to support secure integration of advanced applications and AI-driven optimizations in real-time bidding workflows that help customers simplify operations and improve performance on AWS. To learn more about AWS RTB Fabric, visit the AWS RTB Fabric page.

Betty

Build a multi-Region AWS PrivateLink backed service with seamless failover

Post Syndicated from Madhav Vishnubhatta original https://aws.amazon.com/blogs/architecture/build-a-multi-region-aws-privatelink-backed-service-with-seamless-failover/

Global Payments Inc. is a leading worldwide provider of payment technology and software solutions, headquartered in Atlanta, Georgia. The company processes more than 75 billion transactions annually, serving more than 5 million merchant locations and nearly 2,000 financial institutions globally. Through its merger with TSYS in 2019, Global Payments expanded its capabilities beyond merchant acquiring services to include issuer processing solutions.

The company’s services now encompass ecommerce and omnichannel payments, business management software, customer engagement tools, and cloud-based solutions. Their commitment to technological innovation and customer service has positioned them as one of the largest financial technology companies globally, consistently ranking among the Fortune 500.

This post demonstrates how the Issuer Solutions business of Global Payments, as a service provider, implemented cross-Region failover for an AWS PrivateLink backed service exposed to their customers. Their solution enables failover to a secondary Region without customer coordination, reducing Recovery Time Objective (RTO).

AWS PrivateLink involves two key roles: service providers and service consumers. Service providers build, own, and manage endpoint services. Service consumers create and manage Amazon Virtual Private Cloud (Amazon VPC) endpoints that connect their VPC to an Amazon VPC endpoint service privately, without exposing the traffic to the public internet. Enterprises often build services in multiple AWS Regions for resilience. This approach requires endpoint services in two Regions, with service consumers creating VPC endpoints for each service.

The architecture uses Amazon Route 53 to resolve the service’s Fully Qualified Domain Name (FQDN) to the active Region’s service. Amazon Application Recovery Controller (ARC) is used to initiate the failover.

Customer requirements

Issuer Solutions had the following requirements for this implementation:

  • The ability for consumers to access the service privately, without traversing the public internet
  • Resilience to degradation in a single Region by allowing failover to a secondary Region
  • Independent failover without customer coordination
  • Reliable and simple failover process

Solution overview

The following simplified architecture diagram illustrates the connectivity and failover mechanisms. The exact service implementation of Issuer Solutions is beyond this post’s scope. For simplicity, we represent the service as a Network Load Balancer backed by Amazon Elastic Compute Cloud (Amazon EC2) instances.

AWS Architecture diagram showing primary and secondary regions with Route53 Private Hosted Zones, VPC endpoints, and PrivateLink integration, illustrating the connectivity and failover mechanisms.

The solution consists of the following key components:

  • The service provider deploys identical services in two Regions. The service is represented in this simplified version with a Network Load Balancer backed by EC2 instances. Each Region is independent and therefore resilient against failures in the other Region.
  • Services are exposed through PrivateLink as VPC endpoint services in each Region, allowing client connections without needing NAT gateways or internet gateways and keeping the traffic within the customers’ own private IP space.
  • The service provider authorizes the consumer AWS account to find the services using the VPC endpoint service names.
  • The service consumer uses the VPC PrivateLink endpoint service names to create VPC endpoints with Elastic Network Interfaces (ENIs) in two Availability Zones in each Region. The consumer does this in both consumer Regions, and each consumer Region has two sets of VPC endpoints: one for the primary service of the provider and one for the secondary service.
  • The service consumer creates a Route 53 private hosted zone in each of the two Regions they use, each with two alias records, with a simple routing policy, pointing to the VPC endpoints’ FQDNs in their own Regions. These two alias records are primary.example.com and secondary.example.com.
  • The service provider creates a Route 53 ARC cluster with routing controls for the primary and secondary Regions.
  • The service provider creates a private hosted zone with a failover record set for a consumer specific CNAME like custC.service.p.com that resolves to primary.example.com and secondary.example.com. These records are associated with health checks that are associated with Route 53 ARC routing controls.

As shown in the architecture diagram, it is not necessary for the provider’s and consumer’s Regions to be the same because AWS supports creating VPC endpoints in a Region different to that of the VPC endpoint service itself. Refer to AWS PrivateLink now supports cross-region connectivity for more details.

How the DNS resolution works

Each consumer Region has two Route 53 private hosted zones involved in DNS resolution in this approach: the service provider’s hosted zone and the service consumer’s hosted zone. Both hosted zones are associated with the VPC used by the service consumer. Here is how the DNS resolution works:

  1. When a client in the consumer VPC wants to reach the service, it uses the FQDN custC.service.p.com.
  2. The hosted zone in the service provider’s account resolves custC.service.p.com to either primary.example.com or secondary.example.com depending on the status of the health checks controlled by ARC. For now, let’s assume this resolves to primary.example.com.
  3. Next, primary.example.com resolves to the VPC endpoint FQDN com.amazonaws.vpce.<primary-region>.vpce-svcabc123 due to the hosted zone in the service consumer.

At the time of failover, the service provider will update the ARC health checks to turn off the primary control and turn on the secondary routing control. This causes the service provider’s hosted zone to resolve custC.service.p.com to secondary.example.com, which in turn resolves to the VPC endpoint FQDN in the secondary Region due to the service consumer’s hosted zone.

Considerations

With this setup, the service provider can fail over when they need to without the service consumer having to manually make any changes. This is especially useful for services that have multiple service consumers. Additionally, service consumers can make changes to the VPC endpoint as they see fit. They only need to update the hosted zone they manage to make sure that primary.example.com and secondary.example.com point to the correct VPC endpoints.

We used ARC in this post because it offers a robust solution for cross-Region failover with built-in static stability. ARC also avoids single points of failure in the failover logic by distributing it across multiple Regions.

This setup demonstrates an active-passive configuration where traffic is routed to a single Region at a time using the Route 53 failover routing policy. For an active-active approach, you can adapt this setup by employing alternative Route 53 policies such as weighted or latency-based routing, as detailed in Active-active and active-passive failover.

Code sample

We have created a GitHub repository with Terraform code to demonstrate this solution. The repository has the steps to set it up and test it.

Conclusion

This implementation of cross-Region failover by Global Payments Issuer Solutions for their PrivateLink backed service demonstrates a robust and flexible approach to providing high availability and resilience. By using AWS services such as PrivateLink, Route 53, and Route 53 ARC, they have created a solution that meets their key requirements. This architecture not only benefits Global Payments by allowing them to manage failovers efficiently, but also provides advantages to their service consumers. Customers maintain control over their own infrastructure while benefiting from seamless service continuity. As cloud architectures continue to evolve, solutions like this showcase the power of combining various AWS services to create highly available and fault-tolerant systems that meet complex business needs.

Clone our GitHub repository now and deploy this solution in your own AWS environment to try out this approach to cross-Region failover. Contact your AWS representative today to begin your journey toward enhanced business continuity.


About the Authors

Designing centralized and distributed network connectivity patterns for Amazon OpenSearch Serverless

Post Syndicated from Ankush Goyal original https://aws.amazon.com/blogs/big-data/designing-centralized-and-distributed-network-connectivity-patterns-for-amazon-opensearch-serverless/

Amazon OpenSearch Serverless is a fully managed search and analytics service that automatically provisions and scales infrastructure to help you run search and analytics workloads without cluster management. With OpenSearch Serverless, you can quickly build search and analytics capabilities into your applications.

As organizations scale their use of OpenSearch Serverless, understanding network architecture and DNS management becomes increasingly important. Building upon the connectivity patterns discussed in our previous post Network connectivity patterns for Amazon OpenSearch Serverless, this post covers advanced deployment scenarios focused on centralized and distributed access patterns—specifically, how enterprises can simplify network connectivity across multiple AWS accounts and extend access to on-premises environments for their OpenSearch Serverless deployments.

We outline two key deployment patterns:

  • Pattern 1 – A centralized endpoint model where interface virtual private cloud (VPC) endpoints for OpenSearch Serverless are deployed in a shared services VPC, allowing spoke VPCs from other AWS accounts and on premises to access OpenSearch Serverless collections through these consolidated endpoints.
  • Pattern 2 – A distributed endpoint model where interface VPC endpoints are created in individual spoke VPCs, with multiple consumers (central account, on-premises networks, and other spoke accounts) accessing these endpoints through centralized DNS management. This approach provides direct connectivity within each spoke VPC while maintaining centralized DNS control and management across the organization.

Before diving into advanced deployment patterns, let’s review the DNS behavior of OpenSearch Serverless when accessed through an interface VPC endpoint (AWS PrivateLink). Understanding this foundational aspect can help clarify the connectivity patterns we explore in this post.

OpenSearch Serverless interface VPC endpoint DNS resolution

When creating an OpenSearch Serverless interface VPC endpoint, the service automatically provisions three private hosted zones: one visible private hosted zone us-east-1.aoss.amazonaws.com that handles domain resolution for the OpenSearch Serverless collection and dashboard, another visible private hosted zone us-east-1.opensearch.amazonaws.com that manages resolution for the OpenSearch UI (OpenSearch Dashboards), and one hidden internal private hosted zone that manages the final DNS resolution to private IP addresses.

Our objective in this post is to explore how the two private hosted zones for OpenSearch Serverless work together: the visible private hosted zone us-east-1.aoss.amazonaws.com for collections and dashboards, and the hidden private hosted zone for final DNS resolution to private IP addresses. We examine how these private hosted zones enable scalable DNS resolution in both centralized and distributed architectures. The following workflow diagram shows the DNS resolution flow for the us-east-1 AWS Region. The same pattern applies to other Regions, with the Region identifiers in the DNS records changing accordingly.

DNS Workflow Diagram AOSS

The workflow consists of the following steps:

  1. A user requests access to a collection URL (for example, abc.us-east-1.aoss.amazonaws.com).
  2. The DNS request is sent to the Amazon Route 53 Resolver, which checks the visible private hosted zone us-east-1.aoss.amazonaws.com and finds a CNAME record pointing to the endpoint-specific domain.
  3. The Route 53 Resolver uses the hidden internal private hosted zone to resolve this endpoint-specific domain to the VPC endpoint’s private IP address.
  4. Traffic is allowed only if it originates from the interface VPC endpoint approved by OpenSearch Serverless network policies.

Although this DNS Resolution Process provides flexible and secure private access, it becomes complex when you need connectivity from multiple VPCs, different AWS accounts, or on-premises networks. The following patterns address these challenges and outline strategies to simplify network access and DNS management for OpenSearch Serverless in such environments.

Pattern 1: Centralized interface VPC endpoint for OpenSearch Serverless

This pattern uses a centralized approach where a shared services AWS account with a shared services VPC hosts the OpenSearch Serverless interface VPC endpoint and OpenSearch Serverless collection. From there, other AWS accounts with Amazon VPCs (spoke VPCs) need to be able to access OpenSearch Serverless collections through this central endpoint. Organizations commonly implement this setup in hub-and-spoke network designs that connect their VPCs using either AWS Transit Gateway or AWS Cloud WAN. The following diagram illustrates this architecture.

AOSS Centralized Account

Challenge

When accessing from on-premises networks, both network access and DNS resolution for the OpenSearch Serverless interface VPC endpoint work successfully. However, although the endpoint is network-accessible from spoke VPCs (for example, through Transit Gateway or AWS Cloud WAN), DNS resolution from these VPCs fail.

This happens because OpenSearch Serverless creates and uses a private hosted zone us-east-1.aoss.amazonaws.com that is only associated with the VPC containing the endpoint, in this case, the Shared Services VPC. Simply sharing this private hosted zone with the spoke VPCs doesn’t solve the problem, because the wildcard CNAME record references a DNS name privatelink.c0X.sgw.iad.prod.aoss.searchservices.aws.dev. This DNS name can’t be resolved from other VPCs without additional configuration, because it belongs to a private hosted zone privatelink.c0X.sgw.iad.prod.aoss.searchservices.aws.dev that is only associated with the shared services VPC. This private hosted zone isn’t visible in your account and is controlled by AWS.

Solution: Use Amazon Route 53 Profiles for cross-VPC DNS resolution

To enable centralized DNS resolution, you can use Amazon Route 53 Profiles. With Route 53 Profiles, you can manage and apply DNS-related Amazon Route 53 configurations across multiple VPCs and AWS accounts. The following diagram illustrates the solution architecture.

AOSS Centralized Account Route53 Profile

The solution consists of the following steps:

  1. Create an OpenSearch Serverless interface VPC endpoint in the shared services VPC. This automatically creates and associates the following:
      1. Two default private hosted zones.
      2. One hidden private hosted zone with this VPC.
  2. Create a Route 53 Profile in the shared services account.
  3. Associate the interface VPC endpoint for OpenSearch Serverless with the Route 53 Profile.
    1. The Route 53 Profile automatically associates the hidden private hosted zone with the profile.
  4. Associate the private hosted zone us-east-1.aoss.amazonaws.com that was automatically created by OpenSearch Serverless with the Route 53 Profile.
  5. Share the Route 53 Profile with your other AWS accounts in your organization using AWS Resource Access Manager (AWS RAM).
  6. Associate the spoke VPCs (located in different accounts) with the Route 53 Profile.

If you have an existing Route 53 Profile in your shared services account that is already associated to spoke VPCs, you can simply associate the OpenSearch Serverless interface VPC endpoint and the private hosted zone us-east-1.aoss.amazonaws.com to this profile.

After completing these steps, the DNS resolution for the OpenSearch Serverless collection and dashboard endpoints works seamlessly from spoke VPCs associated with the Route 53 Profile. Clients in spoke VPCs can resolve and access OpenSearch Serverless collections and dashboards through the centralized VPC endpoint.

Pattern 2: Distributed interface VPC endpoint for OpenSearch Serverless

Each spoke VPC, residing in its respective AWS account, hosts its own OpenSearch Serverless collection and interface VPC endpoint. We now want to achieve the following:

  • Centralize DNS management in a shared services VPC to provide consistent resolution for OpenSearch Serverless collections deployed across multiple spoke accounts
  • Provide on-premises resources with DNS resolution capability for all OpenSearch Serverless collections across the organization through a Route 53 Resolver inbound endpoint in the shared services VPC

The following diagram illustrates this architecture.

AOSS Distributed

Challenge

Managing DNS resolution for OpenSearch Serverless collections and dashboards becomes complex in this distributed model because each interface VPC endpoint creates its own set of private hosted zones that are only associated with their respective VPCs. This creates a fragmented DNS landscape where the shared services VPC and on-premises networks need a consolidated way to resolve domains of OpenSearch Serverless collections and dashboards across multiple spoke accounts.

Solution: Use a self-managed private hosted zone in the shared services VPC for on-prem DNS resolution

To enable centralized DNS resolution for distributed endpoints, create a self-managed private hosted zone in the shared services account and associate it with the shared services VPC. Within this private hosted zone, you can create CNAME records that map each OpenSearch Serverless collection endpoint to its respective interface VPC endpoint DNS names in the spoke accounts. The following diagram illustrates this architecture.

AOSS Distributed Centralized DNS On Prem and VPC

Implementation consists of the following steps:

  1. Create a self-managed private hosted zone in the shared services account with the domain name us-east-1.aoss.amazonaws.com and associate it with the shared services VPC. For each OpenSearch Serverless collection, create a CNAME record that points to the Regional DNS name of its corresponding interface VPC endpoint.

This configuration enables both on-premises resources and resources in the shared services VPC to resolve OpenSearch Serverless endpoints that are in the spoke accounts.

After you complete these steps, each OpenSearch Serverless interface VPC endpoint remains within its original AWS account, maintaining security boundaries and account-level autonomy. On-premises systems can access OpenSearch Serverless collections and dashboards using original collection DNS names (for example, {collection-name}.us-east-1.aoss.amazonaws.com) through DNS resolution provided by the private hosted zone in the shared services VPC.

Conclusion

As organizations scale their adoption of OpenSearch Serverless, establishing secure and centralized network access becomes increasingly important. In this post, we explored two architectural patterns specifically around DNS management:

  • Centralized endpoint model – This pattern is ideal when a shared services account manages the OpenSearch Serverless interface VPC endpoints, allowing multiple spoke accounts to access OpenSearch Serverless collections and dashboards through a centralized set of network resources.
  • Distributed endpoint model with centralized DNS – This pattern is suitable for organizations that require account-level autonomy, where each AWS account manages its own OpenSearch Serverless interface VPC endpoints, while DNS resolution is centralized through a shared self-managed private hosted zone in a shared services account.

By understanding the DNS architecture of OpenSearch Serverless and using services like Route 53 Profiles and AWS RAM, organizations can build secure and robust access patterns that align with their organizational structure and needs.


About the Authors

Ankush GoyalAnkush Goyal is a Enterprise Support Lead in AWS Enterprise Support who helps customers streamline their cloud operations on AWS. He is a results-driven IT professional with over 20 years of experience.

Anvesh KogantiAnvesh Koganti is a Solutions Architect at AWS specializing in Networking. He focuses on helping customers build networking architectures for highly scalable and resilient AWS environments. Outside of work, Anvesh is passionate about consumer technology and enjoys listening to podcasts on tech and business. When disconnecting from the digital world, Anvesh spends time outdoors hiking and biking.

Salman AhmedSalman Ahmed is a Senior Technical Account Manager in AWS Enterprise Support. He specializes in guiding customers through the design, implementation, and support of AWS solutions. Combining his networking expertise with a drive to explore new technologies, he helps organizations successfully navigate their cloud journey. Outside of work, he enjoys photography, traveling, and watching his favorite sports teams.

Reduce your operational overhead today with Amazon CloudFront SaaS Manager

Post Syndicated from Veliswa Boya original https://aws.amazon.com/blogs/aws/reduce-your-operational-overhead-today-with-amazon-cloudfront-saas-manager/

Today, I’m happy to announce the general availability of Amazon CloudFront SaaS Manager, a new feature that helps software-as-a-service (SaaS) providers, web development platform providers, and companies with multiple brands and websites efficiently manage delivery across multiple domains. Customers already use CloudFront to securely deliver content with low latency and high transfer speeds. CloudFront SaaS Manager addresses a critical challenge these organizations face: managing tenant websites at scale, each requiring TLS certificates, distributed denial-of-service (DDoS) protection, and performance monitoring.

With CloudFront Saas Manager, web development platform providers and enterprise SaaS providers who manage a large number of domains will use simple APIs and reusable configurations that use CloudFront edge locations worldwide, AWS WAF, and AWS Certificate Manager. CloudFront SaaS Manager can dramatically reduce operational complexity while providing high-performance content delivery and enterprise-grade security for every customer domain.

How it works
In CloudFront, you can use multi-tenant SaaS deployments, a strategy where a single CloudFront distribution serves content for multiple distinct tenants (users or organizations). CloudFront SaaS Manager uses a new template-based distribution model called a multi-tenant distribution to serve content across multiple domains while sharing configuration and infrastructure. However, if supporting single websites or application, a standard distribution would be better or recommended.

A template distribution defines the base configuration that will be used across domains such as origin configurations, cache behaviors, and security settings. Each template distribution has a distribution tenant to represent domain-specific origin paths or origin domain names including web access control list (ACL) overrides and custom TLS certificates.

Optionally, multiple distribution tenants can use the same connection group that provides the CloudFront routing endpoint that serves content to viewers. DNS records point to the CloudFront endpoint of the connection group using a Canonical Name Record (CNAME).

To learn more, visit Understand how multi-tenant distributions work in the Amazon CloudFront Developer Guide.

CloudFront SaaS Manager in action
I’d like to give you an example to help you understand the capabilities of CloudFront SaaS Manager. You have a company called MyStore, a popular e-commerce platform that helps your customer easily set up and manage an online store. MyStore’s tenants already enjoy outstanding customer service, security, reliability, and ease-of-use with little setup required to get a store up and running, resulting in 99.95 percent uptime for the last 12 months.

Customers of MyStore are unevenly distributed across three different pricing tiers: Bronze, Silver, and Gold, and each customer is assigned a persistent mystore.app subdomain. You can apply these tiers to different customer segments, customized settings, and operational Regions. For example, you can add AWS WAF service in the Gold tier as an advanced feature. In this example, MyStore has decided not to maintain their own web servers to handle TLS connections and security for a growing number of applications hosted on their platform. They are evaluating CloudFront to see if that will help them reduce operational overhead.

Let’s find how as MyStore you configure your customer’s websites distributed in multiple tiers with the CloudFront SaaS Manager. To get started, you can create a multi-tenant distribution that acts as a template corresponding to each of the three pricing tiers the MyStore offers: Bronze, Sliver, and Gold shown in Multi-tenant distribution under the SaaS menu on the Amazon CloudFront console.

To create a multi-tenant distribution, choose Create distribution and select Multi-tenant architecture if you have multiple websites or applications that will share the same configuration. Follow the steps to provide basic details such as a name for your distribution, tags, and wildcard certificate, specify origin type and location for your content such as a website or app, and enable security protections with AWS WAF web ACL feature.

When the multi-tenant distribution is created successfully, you can create a distribution tenant by choosing Create tenant in the Distribution tenants menu in the left navigation pane. You can create a distribution tenant to add your active customer to be associated with the Bronze tier.

Each tenant can be associated with up to one multi-tenant distribution. You can add one or more domains of your customers to a distribution tenant and assign custom parameter values such as origin domains and origin paths. A distribution tenant can inherit the TLS certificate and security configuration of its associated multi-tenant distribution. You can also attach a new certificate specifically for the tenant, or you can override the tenant security configuration.

When the distribution tenant is created successfully, you can finalize this step by updating a DNS record to route traffic to the domain in this distribution tenant and creating a CNAME pointed to the CloudFront application endpoint. To learn more, visit Create a distribution in the Amazon CloudFront Developer Guide.

Now you can see all customers in each distribution tenant to associate multi-tenant distributions.

By increasing customers’ business needs, you can upgrade your customers from Bronze to Silver tiers by moving those distribution tenants to a proper multi-tenant distribution.

During the monthly maintenance process, we identify domains associated with inactive customer accounts that can be safely decommissioned. If you’ve decided to deprecate the Bronze tier and migrate all customers who are currently in the Bronze tier to the Silver tier, then you can delete a multi-tenant distribution to associate the Bronze tier. To learn more, visit Update a distribution or Distribution tenant customizations in the Amazon CloudFront Developer Guide.

By default, your AWS account has one connection group that handles all your CloudFront traffic. You can enable Connection group in the Settings menu in the left navigation pane to create additional connection groups, giving you more control over traffic management and tenant isolation.

To learn more, visit Create custom connection group in the Amazon CloudFront Developer Guide.

Now available
Amazon CloudFront SaaS Manager is available today. To learn about, visit CloudFront SaaS Manager product page and documentation page. To learn about SaaS on AWS, visit AWS SaaS Factory.

Give CloudFront SaaS Manager a try in the CloudFront console today and send feedback to AWS re:Post for Amazon CloudFront or through your usual AWS Support contacts.

Veliswa.
_______________________________________________

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Amazon API Gateway now supports dual-stack (IPv4 and IPv6) endpoints

Post Syndicated from Betty Zheng (郑予彬) original https://aws.amazon.com/blogs/aws/amazon-api-gateway-now-supports-dual-stack-ipv4-and-ipv6-endpoints/

Today, we are launching IPv6 support for Amazon API Gateway across all endpoint types, custom domains, and management APIs, in all commercial and AWS GovCloud (US) Regions. You can now configure REST, HTTP, and WebSocket APIs, and custom domains, to accept calls from IPv6 clients alongside the existing IPv4 support. You can also call API Gateway management APIs from dual-stack (IPv6 and IPv4) clients. As organizations globally confront growing IPv4 address scarcity and increasing costs, implementing IPv6 becomes critical for future-proofing network infrastructure. This dual-stack approach helps organizations maintain future network compatibility and expand global reach. To learn more about dualstack in the Amazon Web Services (AWS) environment, see the IPv6 on AWS documentation.

Creating new dual-stack resources

This post focuses on two ways to create an API or a domain name with a dualstack IP address type: AWS Management Console and AWS Cloud Development Kit (CDK).

AWS Console

When creating a new API or domain name in the console, select IPv4 only or dualstack (IPv4 and IPv6) for the IP address type.

As shown in the following image, you can select the dualstack option when creating a new REST API.
For custom domain names, you can similarly configure dualstack as shown in the next image.

If you need to revert to IPv4-only for any reason, you can modify the IP address type setting, with no need to redeploy your API for the update to take effect.

REST APIs of all endpoint types (EDGE, REGIONAL and PRIVATE) support dualstack. Private REST APIs only support dualstack configuration.

AWS CDK

With AWS CDK, start by configuring a dual-stack REST API and domain name.

const api = new apigateway.RestApi(this, "Api", {
  restApiName: "MyDualStackAPI",
  endpointConfiguration: {ipAddressType: "dualstack"}
});

const domain_name = new apigateway.DomainName(this, "DomainName", {
  regionalCertificateArn: 'arn:aws:acm:us-east-1:111122223333:certificate/a1b2c3d4-5678-90ab',
  domainName: 'dualstack.example.com',
  endpointConfiguration: {
    types: ['Regional'],
    ipAddressType: 'dualstack'
  },
  securityPolicy: 'TLS_1_2'
});

const basepathmapping = new apigateway.BasePathMapping(this, "BasePathMapping", {
  domainName: domain_name,
  restApi: api
});

IPv6 Source IP and authorization

When your API begins receiving IPv6 traffic, client source IPs will be in IPv6 format. If you use resource policies, Lambda authorizers, or AWS Identity and Access Management (IAM) policies that reference source IP addresses, make sure they’re updated to accommodate IPv6 address formats.

For example, to permit traffic from a specific IPv6 range in a resource policy.

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Principal": "*",
      "Action": "execute-api:Invoke",
      "Resource": "execute-api:stage-name/*",
      "Condition": {
        "IpAddress": {
          "aws:SourceIp": [
            "192.0.2.0/24",
            "2001:db8:1234::/48"
          ]
        }
      }
    }
  ]
}

Summary

API Gateway dual-stack support helps manage IPv4 address scarcity and costs, comply with government and industry mandates, and prepare for the future of networking. The dualstack implementation provides a smooth transition path by supporting both IPv4 and IPv6 clients simultaneously.

To get started with API Gateway dual-stack support, visit the Amazon API Gateway documentation. You can configure dualstack for new APIs or update existing APIs with minimal configuration changes.

Betty

Special thanks to Ellie Frank (elliesf), Anjali Gola (anjaligl), and Pranika Kakkar (pranika) for providing resources, answering questions, and offering valuable feedback during the writing process. This blog post was made possible through the collaborative support of the service and product management teams.


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New physical AWS Data Transfer Terminals let you upload to the cloud faster

Post Syndicated from Channy Yun (윤석찬) original https://aws.amazon.com/blogs/aws/new-physical-aws-data-transfer-terminals-let-you-upload-to-the-cloud-faster/

Today, we’re announcing the general availability of AWS Data Transfer Terminal, a secure physical location where you can bring your storage devices and upload data faster to the AWS Cloud.

The first Data Transfer Terminals are located in Los Angeles and New York, with plans to add more locations globally. You can reserve a time slot to visit your nearest location and upload data rapidly and securely to any AWS public endpoints, such as Amazon Simple Storage Service (Amazon S3), Amazon Elastic File System (Amazon EFS), or others, using a high throughput connection. Using AWS Data Transfer Terminal, you can significantly reduce the time of ingesting data with high throughput connectivity in the location near by you. You can upload large datasets from fleets of vehicles operating and collecting data in metro areas for training machine learning (ML) models, digital audio and video files from content creators for media processing workloads, and mapping or imagery data from local government organizations for geographic analysis.

After the data is uploaded to AWS, you can use the extensive suite of AWS services to generate value from your data and accelerate innovation. You can also bring your AWS Snowball devices to the location for upload and retain the device for continued use and not rely on traditional shipping methods.

Getting started with AWS Data Transfer Terminal
You can find the availability of a location in the AWS Management Console and reserve the date and time to visit. Then, you can visit the location, make a connection between your storage device and S3 bucket, initiate the transfer of your data, and validate that your transfer is complete.

Go to the AWS Data Transfer Terminal console, then choose Get started.

Choose Create Transfer Team and make a team by adding the team’s name and description with agreement of service terms and conditions. You can add your team members for personal or group reservation in the team setting.

To reserve your time and location, choose Create Reservation.

In the first step, choose your team, a process owner to manage your reservation, and team members to visit the location for the data transferring job. Now, you can choose a location of Data Transfer Terminal facility and set your preferred visiting time. You’ll pay for the space reservation at an hourly rate for your reserved time.

To secure your reservation, choose Next and Create after reviewing the reservation details.

After your reservation is requested, you can find your upcoming reservations in the team page. You can check the reservation status or cancel your reservation.

On your reserved date and time, visit the location and confirm access with the building reception. You’re escorted by building staff to the floor and your reserved room of the Data Transfer Terminal location.

Don’t be surprised if there are no AWS signs in the building or room. This is for security reasons to keep your work location as secret as possible.

Visiting a pilot Terminal
Instead of me visiting a Data Transfer Terminal location where I live in Seoul, Jeff Barr visited a pilot location near him in Seattle to test uploading data as my team member.

The room is equipped with a patch panel, fiber optic cable, and a personal computer. The patch panel is installed inside a wall mount rack or small floor rack to allow additional space on the desk table. With the personal computer, you can see how to remote access to the server during data transfer process.

Here is Jeff’s feedback about visiting and working at the pilot facility.

When I arrived at the building, I was kindly escorted in and able to work easily using the instructions provided at the time of reservation. This location provides me with direct access to AWS global network infrastructure in a secure and on-demand format. I am excited to see how customers use AWS Data Transfer Terminal to more quickly get data into the cloud where they can more rapidly innovate and build on AWS.

Thanks, Jeff, for visiting the facility and doing the uploading job in my place!

Now available
AWS Data Transfer Terminal is now available today in Los Angeles and New York, with plans to add more locations globally.

You’ll be charged for on-demand use per hour for each location. There will be no per GB charge for the data transfer if you upload data into AWS Regions in the same continent of your location. To learn more, visit the Data Transfer Terminal pricing page.

Give AWS Data Transfer Terminal a try in the AWS Management Console. To learn more, refer to the Data Transfer Terminal page and send feedback through your usual AWS Support contacts.

Channy

Introducing Amazon CloudFront VPC origins: Enhanced security and streamlined operations for your applications

Post Syndicated from Matheus Guimaraes original https://aws.amazon.com/blogs/aws/introducing-amazon-cloudfront-vpc-origins-enhanced-security-and-streamlined-operations-for-your-applications/

I’m happy to introduce the release of Amazon CloudFront Virtual Private Cloud (VPC) origins, a new feature that enables content delivery from applications hosted in private subnets within their Amazon Virtual Private Cloud (Amazon VPC). This makes it easy to secure web applications, allowing you to focus on growing your businesses while improving security and maintaining high-performance and global scalability with CloudFront.

Customers serving content from Amazon Simple Storage Solution (Amazon S3), AWS Elemental Services and AWS Lambda Function URLs can use Origin Access Control as a managed solution to secure their origins, and make CloudFront the single front-door to your application. However, this was more difficult to achieve for applications that are hosted on Amazon Elastic Compute Cloud (Amazon EC2) or using load balancers, because you had to create your own solution to achieve the same result. You would have to use a combination of methods such as using access control lists (ACLs), managing firewall rules, or using logic such as header validation and a few other techniques to ensure that the endpoint remained exclusive to CloudFront.

CloudFront VPC origins removes the need for this kind of undifferentiated work by offering a managed solution that can be used to point CloudFront distributions directly to Application Load Balancers (ALBs), Network Load Balancers (NLBs), or EC2 instances inside your private subnets. This ensures that CloudFront becomes the sole ingress point for those resources with minimum configuration effort, providing you with improved performance and a cost-saving opportunity because it also eliminates the need for public IP addresses.

Configuring a CloudFront VPC origin
CloudFront VPC origins is available at no additional cost, making it an accessible option for all AWS customers. It can be integrated with new or existing CloudFront distributions using the Amazon CloudFront console or the AWS Command Line Interface (AWS CLI).

Imagine that you have an application hosted privately on an AWS Fargate for Amazon ECS fronted through an ALB. Let’s create a CloudFront distribution that uses the ALB directly inside the private subnet.

Start by navigating to the CloudFront console and select the new menu option: VPC origins.

vpc origins page

Creating a new VPC origin is straightforward. You only need to select from a few options. In the Origin ARN, you can search for available resources that are hosted in private subnets or enter it directly. You select the resources that you want, choose a friendly name for your VPC origin alongside some security options, and then confirm. Please note that, at launch, the VPC origin resource must be in the same AWS Account as the CloudFront distribution, although support for resources across all accounts is coming soon.

creating a vpc origin

After the creation process is complete, your VPC origin will be deployed and ready to go! You can check its status on the VPC origins page.

With this, we have created a CloudFront distribution that serves content directly from a resource hosted on a private subnet in a few clicks! After your VPC origin is created, you can navigate to your Distribution window, and add the VPC origin to your Distribution by either selecting the ARN from the dropdown or copy-pasting the ARN manually.

Remember, though, that it’s important to still continue to layer your application’s security by using services such as AWS Web Application Firewall (WAF) to protect from web exploits, or AWS Shield for managed DDos protection, and other services to achieve a full-spectrum protection.

Conclusion
CloudFront VPC Origins offers a new way for organizations to deliver secure, high-performance applications by enabling CloudFront distributions to serve content directly from resources hosted within private subnets. This reduces the complexity and cost of maintaining public-facing origins while ensuring that your application remains secure.

To learn more, see the getting started guide.

Matheus Guimaraes | @codingmatheus

Amazon CloudFront now accepts your applications’ gRPC calls

Post Syndicated from Sébastien Stormacq original https://aws.amazon.com/blogs/aws/amazon-cloudfront-now-accepts-your-applications-grpc-calls/

Starting today, you can deploy Amazon CloudFront, our global content delivery network (CDN), in front of your gRPC API endpoints.

gRPC is a modern, efficient, and language-agnostic framework for building APIs. It uses Protocol Buffers (protobuf) as its interface definition language (IDL), which enable you to define services and message types in a platform-independent manner. With gRPC, communication between services is achieved through lightweight and high-performance remote procedure calls (RPCs) over HTTP/2. This promotes efficient and low-latency communication across services, making it ideal for microservices architectures.

gRPC offers features such as bidirectional streaming, flow control, and automatic code generation for a variety of programming languages. It’s well-suited for scenarios in which you require high performance, efficient communication, and real-time data streaming. If your application needs to handle a large amount of data or requires low-latency communication between client and server, gRPC can be a good choice. However, gRPC might be more challenging to learn compared to REST. For example, gRPC relies on the protobuf serialization format, which requires developers to define their data structures and service methods in .proto files.

I see two benefits of deploying CloudFront in front of your gRPC API endpoints.

First, it allows the reduction of latency between the client application and your API implementation. CloudFront offers a global network of over 600+ edge locations with intelligent routing to the closest edge. Edge locations provide TLS termination and optional caching for your static content. CloudFront transfers client application requests to your gRPC origin through the fully managed, low-latency, and high-bandwidth private AWS network.

Secondly, your applications benefit from additional security services deployed on edge locations, such as traffic encryption, the validation of the HTTP headers through AWS Web Application Firewall, and AWS Shield Standard protection against distributed denial of service (DDoS) attacks.

Let’s see it in action
To start this demo, I use the gRPC route-guide demo from the official gRPC code repository. I deploy this example application in a container for ease of deployment (but any other deployment option is supported too).

I use this Dockerfile

FROM python:3.7
RUN pip install protobuf grpcio
COPY ./grpc/examples/python/route_guide .
CMD python route_guide_server.py
EXPOSE 50051

I also use the AWS Copilot command line to deploy my container on Amazon Elastic Container Service (Amazon ECS). The Copilot command prompts me to collect the information it requires to build and deploy the container. Then, it creates the ECS cluster, the ECS service, and the ECS task automatically. It also creates a TLS certificate and the load balancer for me. I test the client application by modifying line 122 to use the DNS name of the load balancer listener endpoint. I also change the client application code to use grpc.secure_channel instead of grpc.insecure_channel because the load balancer provides the application with an HTTPS endpoint.

gRPC client application demo - source code with ALB

When I’m confident my API is correctly deployed and working, I proceed and configure CloudFront.

First, in the CloudFront section of the AWS Management Console, I select Create distribution.

Under Origin, I enter my gRPC endpoint DNS name as Origin domain. I enable HTTPS only as Protocol and leave the HTTPS port as is (443). Then I choose a Name for the distribution.

CloudFront - Add origin and name

Under Viewer, I select HTTPS only as Viewer protocol policy. Then, I select GET, HEAD, OPTIONS, PUT, POST, PATCH, DELETE as Allowed HTTP methods. I select Enable for Allow gRPC requests over HTTP/2.

CloudFront - Viewer Policy

Under Cache key and origin requests, I select AllViewer as Origin request policy.

The default cache policy is CacheOptimized, but gRPC isn’t cacheable API traffic. Therefore, I select CachingDisabled as Cache policy.

CloudFront - Cache policy

AWS WAF helps protect you against common web exploits and bots that can affect availability, compromise security, or consume excessive resources. For gRPC traffic, AWS WAF can inspect the HTTP headers of the request and enforce access control. It doesn’t inspect the request body in protobuf format.

For this demo, I choose to not use AWS WAF. Under Web Application Firewall (WAF), I select Do not enable security protections.

CloudFront - Security

I also keep all the other options with their default value. HTTP/2 support is selected by default. Do not disable it because it is required for gRPC.

Finally, I select Create distribution.

CloudFront - Create distribution

There is only one switch to enable gRPC on top of the usual setup. When turned on, with HTTP/2 and HTTP POST enabled, CloudFront detects gRPC client traffic and forwards it to your gRPC origin.

After a few minutes, the distribution is ready. I copy and paste the endpoint URL of the CloudFront distribution, and I change the client-side app to make it point to CloudFront instead of the previously created load balancer.

gRPC client application demo - source code

I test the application again, and it works.

gRPC client application demo - execution

Pricing and Availability
gRPC origins are available on all the more than 600 CloudFront edge locations at no additional cost. The usual requests and data transfer fees apply.

Go and point your CloudFront origin to a gRPC endpoint today.

— seb

AWS and Multicloud: Existing capabilities & continued enhancements

Post Syndicated from Jeff Barr original https://aws.amazon.com/blogs/aws/aws-and-multicloud-existing-capabilities-continued-enhancements/

When I speak to large-scale AWS customers about their challenges and concerns, the conversation often turns to the topic of multicloud. Whether by intent or by accident, these customers sometimes choose to make use of services from more than one cloud provider, sometimes in conjunction with applications or services that are still hosted on-premises. In some cases they made early, bottom-up choices at the team and division level, choosing cloud offerings from multiple vendors in the absence of a top-down mandate. In others, they acquired or merged with another organization and discovered a similar multi-vendor situation.

Regardless of the path, these customers tell me that they want to simplify and centralize their oversight and management of this diverse portfolio of cloud and on-premises resources. It is sometimes the case that the “multi” situation is time-bound, with a plan in place to ultimately consolidate operations in one place. It is also sometimes the case that the customer plans to retain their diverse portfolio.

AWS and multicloud
Our goal with AWS is to make you successful no matter what architectural choices you have made. In this post I want to outline our approach, share some capabilities that our customers have been using over the years, and provide you with an update on some of the more recent service announcements and content that we have created to give you guidance that will help you to succeed.

Our approach is to extend existing AWS operational and management capabilities to work in multicloud and hybrid environments. Because we extend existing capabilities, your investment in training, development, scripting, and runbooks is preserved, and actually becomes even more worthwhile since it applies to your other (non-AWS) resources. For example, you can use the same service (AWS Systems Manager) to patch and update Amazon Elastic Compute Cloud (Amazon EC2) instances, servers running on-premises, and servers provided by other cloud providers. Similarly, you can use Amazon CloudWatch to monitor applications, compute resources, and other cloud resources in all of those environments. These are two examples of how we are putting our approach into practice for you.

The AWS Solutions for Hybrid and Multicloud page contains additional examples of our extension-based approach to adding new capabilities, along some success stories from customers who have put the capabilities to use including Phillips 66 and Deutsche Börse.

Whether you choose to operate entirely on AWS or in multicloud and hybrid environments, one of the primary reasons to adopt AWS is the broad choice of services we offer, enabling you to innovate, build, deploy, and monitor your workloads. Just as we recently launched free data transfer out to the internet (DTO) when you want to move outside of AWS, we are committed to helping you be successful regardless of your approach.

Now that I have explained our approach and highlighted some of the principal multicloud service offerings, let’s take a look at a few of the newest multicloud and hybrid capabilities.

Multicloud launches
Since the beginning of 2023 we have launched eighteen new multicloud capabilities to existing AWS services, including 15 for data & analytics, 1 for security, and 2 for identity. Many of these launches add to the existing multicloud capabilities of the respective services:

AWS DataSync – This service transfers data between storage services. In addition to existing support for Google Cloud Storage, Azure Files, and Azure Blob Storage, we added support for five additional cloud service providers and storage services including Oracle Cloud Storage and DigitalOcean Spaces (full list). To learn more about this service, read What is AWS DataSync. To get started, I create a source location:

AWS Glue – This data integration service helps you to discover, prepare, and integrate all of your data at any scale. You can use it to connect to more than 80 different data sources, including cloud databases and analytics services. In October 2023, we introduced additional new connectors that allow you to move data bidirectionally between Amazon Simple Storage Service (Amazon S3), and either Azure Blob Storage or Azure Data Lake Storage (full list). We also launched six database connectors for AWS Glue for Apache Spark, including Teradata, SAP HANA, Azure SQL, Azure Cosmos DB, Vertica, and MongoDB (full list). To learn more about AWS Glue, read What is AWS Glue. I create a visual job flow to get started:

Amazon Athena – This serverless analytics service lets you use interactive SQL queries to analyze petabyte-scale data where it lives (more than 25 external data sources, including other cloud data stores), without copying or transforming it. Last year we added a new data source connector that allows you to query data in Google Cloud Storage. To learn more about Amazon Athena, read What is Amazon Athena.

Amazon AppFlow – You can take advantage of data and analytics in Google BigQuery using a connector available in Amazon AppFlow. To get started with Amazon AppFlow I create a flow and configure a data source:

Amazon Security Lake – This service helps you to achieve a more complete, organization-wide view of your security posture. It centralizes security data from your AWS environments, SaaS providers, on-premises environments, and cloud sources (Azure and GCP) into a purpose-built data lake. It became generally available last year, and now supports collection and analysis of security data from sources that support the Open Cybersecurity Schema Framework (OCSF) standard—more than 80 sources (full list).

AWS Secrets Manager – This service centrally manages secrets such as database credentials and API keys. Secrets are securely encrypted and can be centrally audited, with support for replication to support disaster recovery and multi-region applications. Last year we announced that you can Use AWS Secrets Manager to store and manage secrets in on-premises or multicloud workloads. To learn more, read What is AWS Secrets Manager.

AWS Identity and Access Management (IAM) – AWS IAM Identity Center now supports automated user provisioning from Google Workspace. The integration helps administrators simplify AWS access management across multiple accounts while maintaining familiar Google Workspace experiences for end users as they sign in.

Amazon CloudWatch – This service lets you query, visualize, and alarm on metrics of all sorts: application, AWS, on-premises, and multicloud. At re:Invent 2023 we added even more support for consolidation of hybrid, multicloud, and on-premises metrics. This new feature allows you to select and configure connectors that pull data from Amazon Managed Service for Prometheus, generic Prometheus, Amazon OpenSearch Service, Amazon RDS for MySQL, Amazon RDS for PostgreSQL, CSV files stored in Amazon Simple Storage Service (Amazon S3), and Microsoft Azure Monitor.

Multicloud content and guidance
Now that you know about some of our latest multicloud launches, let’s take a look at some of the blog posts and other content that my colleagues have created.

First, some blog posts:

Next, some of the most popular multicloud videos from AWS re:Invent 2023:

And finally, be sure to bookmark the AWS Solutions for Hybrid and Multicloud page.

We’re here to help
If you are running in a multicloud environment and are ready to simplify and centralize, be sure to reach out to your AWS Account Manager (AM) or Technical Account Manager (TAM). Both will be happy to help!

Jeff;

Scale AWS Glue jobs by optimizing IP address consumption and expanding network capacity using a private NAT gateway

Post Syndicated from Sushanth Kothapally original https://aws.amazon.com/blogs/big-data/scale-aws-glue-jobs-by-optimizing-ip-address-consumption-and-expanding-network-capacity-using-a-private-nat-gateway/

As businesses expand, the demand for IP addresses within the corporate network often exceeds the supply. An organization’s network is often designed with some anticipation of future requirements, but as enterprises evolve, their information technology (IT) needs surpass the previously designed network. Companies may find themselves challenged to manage the limited pool of IP addresses.

For data engineering workloads when AWS Glue is used in such a constrained network configuration, your team may sometimes face hurdles running many jobs simultaneously. This happens because you may not have enough IP addresses to support the required connections to databases. To overcome this shortage, the team may get more IP addresses from your corporate network pool. These obtained IP addresses can be unique (non-overlapping) or overlapping, when the IP addresses are reused in your corporate network.

When you use overlapping IP addresses, you need an additional network management to establish connectivity. Networking solutions can include options like private Network Address Translation (NAT) gateways, AWS PrivateLink, or self-managed NAT appliances to translate IP addresses.

In this post, we will discuss two strategies to scale AWS Glue jobs:

  1. Optimizing the IP address consumption by right-sizing Data Processing Units (DPUs), using the Auto Scaling feature of AWS Glue, and fine-tuning of the jobs.
  2. Expanding the network capacity using additional non-routable Classless Inter-Domain Routing (CIDR) range with a private NAT gateway.

Before we dive deep into these solutions, let us understand how AWS Glue uses Elastic Network Interface (ENI) for establishing connectivity. To enable access to data stores inside a VPC, you need to create an AWS Glue connection that is attached to your VPC. When an AWS Glue job runs in your VPC, the job creates an ENI inside the configured VPC for each data connection, and that ENI uses an IP address in the specified VPC. These ENIs are short-lived and active until job is complete.

Now let us look at the first solution that explains optimizing the AWS Glue IP address consumption.

Strategies for efficient IP address consumption

In AWS Glue, the number of workers a job uses determines the count of IP addresses used from your VPC subnet. This is because each worker requires one IP address that maps to one ENI. When you don’t have enough CIDR range allocated to the AWS Glue subnet, you may observe IP address exhaustion errors. The following are some best practices to optimize AWS Glue IP address consumption:

  • Right-sizing the job’s DPUs – AWS Glue is a distributed processing engine. It works efficiently when it can run tasks in parallel. If a job has more than the required DPUs, it doesn’t always run quicker. So, finding the right number of DPUs will make sure you use IP addresses optimally. By building observability in the system and analyzing the job performance, you can get insights into ENI consumption trends and then configure the appropriate capacity on the job for the right size. For more details, refer to Monitoring for DPU capacity planning. The Spark UI is a helpful tool to monitor AWS Glue jobs’ workers usage. For more details, refer to Monitoring jobs using the Apache Spark web UI.
  • AWS Glue Auto Scaling – It’s often difficult to predict a job’s capacity requirements upfront. Enabling the Auto Scaling feature of AWS Glue will offload some of this responsibility to AWS. At runtime based on the workload requirements, the job automatically scales worker nodes upto the defined maximum configuration. If there is no additional need, AWS Glue will not overprovision workers, thereby saving resources and reducing cost. The Auto Scaling feature is available in AWS Glue 3.0 and later. For more information, refer to Introducing AWS Glue Auto Scaling: Automatically resize serverless computing resources for lower cost with optimized Apache Spark.
  • Job-level optimization – Identify job-level optimizations by using AWS Glue job metrics , and apply best practices from Best practices for performance tuning AWS Glue for Apache Spark jobs.

Next let us look at the second solution that elaborates network capacity expansion.

Solutions for network size (IP address) expansion

In this section, we will discuss two possible solutions to expand network size in more detail.

Expand VPC CIDR ranges with routable addresses

One solution is to add more private IPv4 CIDR ranges from RFC 1918 to your VPC. Theoretically, each AWS account can be assigned to some or all these IP address CIDRs. Your IP Address Management (IPAM) team often manages the allocation of IP addresses that each business unit can use from RFC1918 to avoid overlapping IP addresses across multiple AWS accounts or business units. If your current routable IP address quota allocated by the IPAM team is not sufficient, then you can request for more.

If your IPAM team issues you an additional non-overlapping CIDR range, then you can either add it as a secondary CIDR to your existing VPC or create a new VPC with it. If you are planning to create a new VPC, then you can inter-connect the VPCs via VPC peering or AWS Transit Gateway.

If this additional capacity is sufficient to run all your jobs within defined the timeframe, then it is a simple and cost-effective solution. Otherwise, you can consider adopting overlapping IP addresses with a private NAT gateway, as described in the following section. With the following solution you must use Transit Gateway to connect VPCs as VPC peering is not possible when there are overlapping CIDR ranges in those two VPCs.

Configure non-routable CIDR with a private NAT gateway

As described in the AWS whitepaper Building a Scalable and Secure Multi-VPC AWS Network Infrastructure, you can expand your network capacity by creating a non-routable IP address subnet and using a private NAT gateway that is located in a routable IP address space (non-overlapping) to route traffic. A private NAT gateway translates and routes traffic between non-routable IP addresses and routable IP addresses. The following diagram demonstrates the solution with reference to AWS Glue.

High level architecture

As you can see in the above diagram, VPC A (ETL) has two CIDR ranges attached. The smaller CIDR range 172.33.0.0/24 is routable because it not reused anywhere, whereas the larger CIDR range 100.64.0.0/16 is non-routable because it is reused in the database VPC.

In VPC B (Database), we have hosted two databases in routable subnets 172.30.0.0/26 and 172.30.0.64/26. These two subnets are in two separate Availability Zones for high availability. We also have two additional unused subnet 100.64.0.0/24 and 100.64.1.0/24 to simulate a non-routable setup.

You can choose the size of the non-routable CIDR range based on your capacity requirements. Since you can reuse IP addresses, you can create a very large subnet as needed. For example, a CIDR mask of /16 would give you approximately 65,000 IPv4 addresses. You can work with your network engineering team and size the subnets.

In short, you can configure AWS Glue jobs to use both routable and non-routable subnets in your VPC to maximize the available IP address pool.

Now let us understand how Glue ENIs that are in a non-routable subnet communicate with data sources in another VPC.

Call flow

The data flow for the use case demonstrated here is as follows (referring to the numbered steps in figure above):

  1. When an AWS Glue job needs to access a data source, it first uses the AWS Glue connection on the job and creates the ENIs in the non-routable subnet 100.64.0.0/24 in VPC A. Later AWS Glue uses the database connection configuration and attempts to connect to the database in VPC B 172.30.0.0/24.
  2. As per the route table VPCA-Non-Routable-RouteTable the destination 172.30.0.0/24 is configured for a private NAT gateway. The request is sent to the NAT gateway, which then translates the source IP address from a non-routable IP address to a routable IP address. Traffic is then sent to the transit gateway attachment in VPC A because it’s associated with the VPCA-Routable-RouteTable route table in VPC A.
  3. Transit Gateway uses the 172.30.0.0/24 route and sends the traffic to the VPC B transit gateway attachment.
  4. The transit gateway ENI in VPC B uses VPC B’s local route to connect to the database endpoint and query the data.
  5. When the query is complete, the response is sent back to VPC A. The response traffic is routed to the transit gateway attachment in VPC B, then Transit Gateway uses the 172.33.0.0/24 route and sends traffic to the VPC A transit gateway attachment.
  6. The transit gateway ENI in VPC A uses the local route to forward the traffic to the private NAT gateway, which translates the destination IP address to that of ENIs in non-routable subnet.
  7. Finally, the AWS Glue job receives the data and continues processing.

The private NAT gateway solution is an option if you need extra IP addresses when you can’t obtain them from a routable network in your organization. Sometimes with each additional service there is an additional cost incurred, and this trade-off is necessary to meet your goals. Refer to the NAT Gateway pricing section on the Amazon VPC pricing page for more information.

Prerequisites

To complete the walk-through of the private NAT gateway solution, you need the following:

Deploy the solution

To implement the solution, complete the following steps:

  1. Sign in to your AWS management console.
  2. Deploy the solution by clicking Launch stack . This stack defaults to us-east-1, you can select your desired Region.
  3. Click next and then specify the stack details. You can retain the input parameters to the prepopulated default values or change them as needed.
  4. For DatabaseUserPassword, enter an alphanumeric password of your choice and ensure to note it down for further use.
  5. For S3BucketName, enter a unique Amazon Simple Storage Service (Amazon S3) bucket name. This bucket stores the AWS Glue job script that will be copied from an AWS public code repository.Stack details
  6. Click next.
  7. Leave the default values and click next again.
  8. Review the details, acknowledge the creation of IAM resources, and click submit to start the deployment.

You can monitor the events to see resources being created on the AWS CloudFormation console. It may take around 20 minutes for the stack resources to be created.

After the stack creation is complete, go to the Outputs tab on the AWS CloudFormation console and note the following values for later use:

  • DBSource
  • DBTarget
  • SourceCrawler
  • TargetCrawler

Connect to an AWS Cloud9 instance

Next, we need to prepare the source and target Amazon RDS for MySQL tables using an AWS Cloud9 instance. Complete the following steps:

  1. On the AWS Cloud9 console page, locate the aws-glue-cloud9 environment.
  2. In the Cloud9 IDE column, click on Open to launch your AWS Cloud9 instance in a new web browser.

Prepare the source MySQL table

Complete the following steps to prepare your source table:

  1. From the AWS Cloud9 terminal, install the MySQL client using the following command: sudo yum update -y && sudo yum install -y mysql
  2. Connect to the source database using the following command. Replace the source hostname with the DBSource value you captured earlier. When prompted, enter the database password that you specified during the stack creation. mysql -h <Source Hostname> -P 3306 -u admin -p
  3. Run the following scripts to create the source emp table, and load the test data:
    -- connect to source database
    USE srcdb;
    -- Drop emp table if it exists
    DROP TABLE IF EXISTS emp;
    -- Create the emp table
    CREATE TABLE emp (empid INT AUTO_INCREMENT,
                      ename VARCHAR(100) NOT NULL,
                      edept VARCHAR(100) NOT NULL,
                      PRIMARY KEY (empid));
    -- Create a stored procedure to load sample records into emp table
    DELIMITER $$
    CREATE PROCEDURE sp_load_emp_source_data()
    BEGIN
    DECLARE empid INT;
    DECLARE ename VARCHAR(100);
    DECLARE edept VARCHAR(50);
    DECLARE cnt INT DEFAULT 1; -- Initialize counter to 1 to auto-increment the PK
    DECLARE rec_count INT DEFAULT 1000; -- Initialize sample records counter
    TRUNCATE TABLE emp; -- Truncate the emp table
    WHILE cnt <= rec_count DO -- Loop and load the required number of sample records
    SET ename = CONCAT('Employee_', FLOOR(RAND() * 100) + 1); -- Generate random employee name
    SET edept = CONCAT('Dept_', FLOOR(RAND() * 100) + 1); -- Generate random employee department
    -- Insert record with auto-incrementing empid
    INSERT INTO emp (ename, edept) VALUES (ename, edept);
    -- Increment counter for next record
    SET cnt = cnt + 1;
    END WHILE;
    COMMIT;
    END$$
    DELIMITER ;
    -- Call the above stored procedure to load sample records into emp table
    CALL sp_load_emp_source_data();
  4. Check the source emp table’s count using the below SQL query (you need this at later step for verification). select count(*) from emp;
  5. Run the following command to exit from the MySQL client utility and return to the AWS Cloud9 instance’s terminal: quit;

Prepare the target MySQL table

Complete the following steps to prepare the target table:

  1. Connect to the target database using the following command. Replace the target hostname with the DBTarget value you captured earlier. When prompted enter the database password that you specified during the stack creation. mysql -h <Target Hostname> -P 3306 -u admin -p
  2. Run the following scripts to create the target emp table. This table will be loaded by the AWS Glue job in the subsequent step.
    -- connect to the target database
    USE targetdb;
    -- Drop emp table if it exists 
    DROP TABLE IF EXISTS emp;
    -- Create the emp table
    CREATE TABLE emp (empid INT AUTO_INCREMENT,
                      ename VARCHAR(100) NOT NULL,
                      edept VARCHAR(100) NOT NULL,
                      PRIMARY KEY (empid)
    );

Verify the networking setup (Optional)

The following steps are useful to understand NAT gateway, route tables, and the transit gateway configurations of private NAT gateway solution. These components were created during the CloudFormation stack creation.

  1. On the Amazon VPC console page, navigate to Virtual private cloud section and locate NAT gateways.
  2. Search for NAT Gateway with name Glue-OverlappingCIDR-NATGW and explore it further. As you can see in the following screenshot, the NAT gateway was created in VPC A (ETL) on the routable subnet.NAT Gateway setup
  3. In the left side navigation pane, navigate to Route tables under virtual private cloud section.
  4. Search for VPCA-Non-Routable-RouteTable and explore it further. You can see that the route table is configured to translate traffic from overlapping CIDR using the NAT gateway.Route table setup
  5. In the left side navigation pane, navigate to Transit gateways section and click on Transit gateway attachments. Enter VPC- in the search box and locate the two newly created transit gateway attachments.
  6. You can explore these attachments further to learn their configurations.

Run the AWS Glue crawlers

Complete the following steps to run the AWS Glue crawlers that are required to catalog the source and target emp tables. This is a prerequisite step for running the AWS Glue job.

  1. On the AWS Glue Console page, under Data Catalog section in the navigation pane, click on Crawlers.
  2. Locate the source and target crawlers that you noted earlier.
  3. Select these crawlers and click Run to create the respective AWS Glue Data Catalog tables.
  4. You can monitor the AWS Glue crawlers for the successful completion. It may take around 3–4 minutes for both crawlers to complete. When they’re done, the last run status of the job changes to Succeeded, and you can also see there are two AWS Glue catalog tables created from this run.Crawler run sucessful

Run the AWS Glue ETL job

After you set up the tables and complete the prerequisite steps, you are now ready to run the AWS Glue job that you created using the CloudFormation template. This job connects to the source RDS for MySQL database, extracts the data, and loads the data into the target RDS for MySQL database. This job reads data from a source MySQL table and loads it to the target MySQL table using private NAT gateway solution. To run the AWS Glue job, complete the following steps:

  1. On the AWS Glue console, click on ETL jobs in the navigation pane.
  2. Click on the job glue-private-nat-job.
  3. Click Run to start it.

The following is the PySpark script for this ETL job:

import sys
from awsglue.transforms import *
from awsglue.utils import getResolvedOptions
from pyspark.context import SparkContext
from awsglue.context import GlueContext
from awsglue.job import Job

args = getResolvedOptions(sys.argv, ["JOB_NAME"])
sc = SparkContext()
glueContext = GlueContext(sc)
spark = glueContext.spark_session
job = Job(glueContext)
job.init(args["JOB_NAME"], args)

# Script generated for node AWS Glue Data Catalog
AWSGlueDataCatalog_node = glueContext.create_dynamic_frame.from_catalog(
    database="glue_cat_db_source",
    table_name="srcdb_emp",
    transformation_ctx="AWSGlueDataCatalog_node",
)

# Script generated for node Change Schema
ChangeSchema_node = ApplyMapping.apply(
    frame=AWSGlueDataCatalog_node,
    mappings=[
        ("empid", "int", "empid", "int"),
        ("ename", "string", "ename", "string"),
        ("edept", "string", "edept", "string"),
    ],
    transformation_ctx="ChangeSchema_node",
)

# Script generated for node AWS Glue Data Catalog
AWSGlueDataCatalog_node = glueContext.write_dynamic_frame.from_catalog(
    frame=ChangeSchema_node,
    database="glue_cat_db_target",
    table_name="targetdb_emp",
    transformation_ctx="AWSGlueDataCatalog_node",
)

job.commit()

Based on the job’s DPU configuration, AWS Glue creates a set of ENIs in the non-routable subnet that is configured on the AWS Glue connection. You can monitor these ENIs on the Network Interfaces page of the Amazon Elastic Compute Cloud (Amazon EC2) console.

The below screenshot shows the 10 ENIs that were created for the job run to match the requested number of workers configured on the job parameters. As expected, the ENIs were created in the non-routable subnet of VPC A, enabling scalability of IP addresses. After the job is complete, these ENIs will be automatically released by AWS Glue.Execution ENIs

When the AWS Glue job is running, you can monitor its status. Upon successful completion, the job’s status changes to Succeeded.Job successful completition

Verify the results

After the AWS Glue job is complete, connect to the target MySQL database. Verify if the target record count matches to the source. You can use the below SQL query in AWS Cloud9 terminal.

USE targetdb;
SELECT count(*) from emp;

Finally, exit from the MySQL client utility using the following command and return to the AWS Cloud9 terminal: quit;

You can now confirm that AWS Glue has successfully completed a job to load data to a target database using the IP addresses from a non-routable subnet. This concludes end to end testing of the private NAT gateway solution.

Clean up

To avoid incurring future charges, delete the resource created via CloudFormation stack by completing the following steps:

  1. On the AWS CloudFormation console, click Stacks in the navigation pane.
  2. Select the stack AWSGluePrivateNATStack.
  3. Click on Delete to delete the stack. When prompted confirm the stack deletion.

Conclusion

In this post, we demonstrated how you can scale AWS Glue jobs by optimizing IP addresses consumption and expanding your network capacity by using a private NAT gateway solution. This two-fold approach helps you to get unblocked in an environment that has IP address capacity constraints. The options discussed in the AWS Glue IP address optimization section are complimentary to the IP address expansion solutions, and you can iteratively build to mature your data platform.

Learn more about AWS Glue job optimization techniques from Monitor and optimize cost on AWS Glue for Apache Spark and Best practices to scale Apache Spark jobs and partition data with AWS Glue.


About the authors

Author1Sushanth Kothapally is a Solutions Architect at Amazon Web Services supporting Automotive and Manufacturing customers. He is passionate about designing technology solutions to meet business goals and has keen interest in serverless and event-driven architectures.

Author2Senthil Kamala Rathinam is a Solutions Architect at Amazon Web Services specializing in Data and Analytics. He is passionate about helping customers to design and build modern data platforms. In his free time, Senthil loves to spend time with his family and play badminton.

Free data transfer out to internet when moving out of AWS

Post Syndicated from Sébastien Stormacq original https://aws.amazon.com/blogs/aws/free-data-transfer-out-to-internet-when-moving-out-of-aws/

You told us one of the primary reasons to adopt Amazon Web Services (AWS) is the broad choice of services we offer, enabling you to innovate, build, deploy, and monitor your workloads. AWS has continuously expanded its services to support virtually any cloud workload. It now offers over 200 fully featured services for compute, storage, databases, networking, analytics, machine learning (ML) and artificial intelligence (AI), and many more. For example, Amazon Elastic Compute Cloud (Amazon EC2) offers over 750 generally available instances—more than any other major cloud provider—and you can choose from numerous relational, analytics, key-value, document, or graph databases.

We believe this choice must include the one to migrate your data to another cloud provider or on-premises. That’s why, starting today, we’re waiving data transfer out to the internet (DTO) charges when you want to move outside of AWS.

Over 90 percent of our customers already incur no data transfer expenses out of AWS because we provide 100 gigabytes per month free from AWS Regions to the internet. This includes traffic from Amazon EC2, Amazon Simple Storage Service (Amazon S3), Application Load Balancer, among others. In addition, we offer one terabyte of free data transfer out of Amazon CloudFront every month.

If you need more than 100 gigabytes of data transfer out per month while transitioning, you can contact AWS Support to ask for free DTO rates for the additional data. It’s necessary to go through support because you make hundreds of millions of data transfers each day, and we generally do not know if the data transferred out to the internet is a normal part of your business or a one-time transfer as part of a switch to another cloud provider or on premises.

We will review requests at the AWS account level. Once approved, we will provide credits for the data being migrated. We don’t require you to close your account or change your relationship with AWS in any way. You’re welcome to come back at any time. We will, of course, apply additional scrutiny if the same AWS account applies multiple times for free DTO.

We believe in customer choice, including the choice to move your data out of AWS. The waiver on data transfer out to the internet charges also follows the direction set by the European Data Act and is available to all AWS customers around the world and from any AWS Region.

Freedom of choice is not limited to data transfer rates. AWS also supports Fair Software Licensing Principles, which make it easy to use software with other IT providers of your choice. You can read this blog post for more details.

You can check the FAQ for more information, or you can contact AWS Customer Support to request credits for DTO while switching.

But I sincerely hope you will not.

— seb

Generative AI Infrastructure at AWS

Post Syndicated from Betsy Chernoff original https://aws.amazon.com/blogs/compute/generative-ai-infrastructure-at-aws/

Building and training generative artificial intelligence (AI) models, as well as predicting and providing accurate and insightful outputs requires a significant amount of infrastructure.

There’s a lot of data that goes into generating the high-quality synthetic text, images, and other media outputs that large-language models (LLMs), as well as foundational models (FMs), create. To start, the data set generally has somewhere around one billion variables present in the model that it was trained on (also known as parameters). To process that massive amount of data (think: petabytes), it can take hundreds of hardware accelerators (which are incorporated into purpose-built ML silicon or GPUs).

Given how much data is required for an effective LLM, it becomes costly and inefficient if an organization can’t access the data for these models as quickly as their GPUs/ML silicon are processing it. Selecting infrastructure for generative AI workloads impacts everything from cost to performance to sustainability goals to the ease of use. To successfully run training and inference for FMs organizations need:

  1. Price-performant accelerated computing (including the latest GPUs and dedicated ML Silicon) to power large generative AI workloads.
  2. High-performance and low-latency cloud storage that’s built to keep accelerators highly utilized.
  3. The most performant and cutting-edge technologies, networking, and systems to support the infrastructure for a generative AI workload.
  4. The ability to build with cloud services that can provide seamless integration across generative AI applications, tools, and infrastructure.

Overview of compute, storage, & networking for generative AI

Amazon Elastic Compute Cloud (Amazon EC2) accelerated computing portfolio (including instances powered by GPUs and purpose-built ML silicon) offers the broadest choice of accelerators to power generative AI workloads.

To keep the accelerators highly utilized, they need constant access to data for processing. AWS provides this fast data transfer from storage (up to hundreds of GBs/TBs of data throughput) with Amazon FSx for Lustre and Amazon S3.

Accelerated computing instances combined with differentiated AWS technologies such as the AWS Nitro System, up to 3,200 Gbps of Elastic Fabric Adapter (EFA) networking, as well as exascale computing with Amazon EC2 UltraClusters helps to deliver the most performant infrastructure for generative AI workloads.

Coupled with other managed services such as Amazon SageMaker HyperPod and Amazon Elastic Kubernetes Service (Amazon EKS), these instances provide developers with the industry’s best platform for building and deploying generative AI applications.

This blog post will focus on highlighting announcements across Amazon EC2 instances, storage, and networking that are centered around generative AI.

AWS compute enhancements for generative AI workloads

Training large FMs requires extensive compute resources and because every project is different, a broad set of options are needed so that organization of all sizes can iterate faster, train more models, and increase accuracy. In 2023, there were a lot of launches across the AWS compute category that supported both training and inference workloads for generative AI.

One of those launches, Amazon EC2 Trn1n instances, doubled the network bandwidth (compared to Trn1 instances) to 1600 Gbps of Elastic Fabric Adapter (EFA). That increased bandwidth delivers up to 20% faster time-to-train relative to Trn1 for training network-intensive generative AI models, such as LLMs and mixture of experts (MoE).

Watashiha offers an innovative and interactive AI chatbot service, “OGIRI AI,” which uses LLMs to incorporate humor and offer a more relevant and conversational experience to their customers. “This requires us to pre-train and fine-tune these models frequently. We pre-trained a GPT-based Japanese model on the EC2 Trn1.32xlarge instance, leveraging tensor and data parallelism,” said Yohei Kobashi, CTO, Watashiha, K.K. “The training was completed within 28 days at a 33% cost reduction over our previous GPU based infrastructure. As our models rapidly continue to grow in complexity, we are looking forward to Trn1n instances which has double the network bandwidth of Trn1 to speed up training of larger models.”

AWS continues to advance its infrastructure for generative AI workloads, and recently announced that Trainium2 accelerators are also coming soon. These accelerators are designed to deliver up to 4x faster training than first generation Trainium chips and will be able to be deployed in EC2 UltraClusters of up to 100,000 chips, making it possible to train FMs and LLMs in a fraction of the time, while improving energy efficiency up to 2x.

AWS has continued to invest in GPU infrastructure over the years, too. To date, NVIDIA has deployed 2 million GPUs on AWS, across the Ampere and Grace Hopper GPU generations. That’s 3 zetaflops, or 3,000 exascale super computers. Most recently, AWS announced the Amazon EC2 P5 Instances that are designed for time-sensitive, large-scale training workloads that use NVIDIA CUDA or CuDNN and are powered by NVIDIA H100 Tensor Core GPUs. They help you accelerate your time to solution by up to 4x compared to previous-generation GPU-based EC2 instances, and reduce cost to train ML models by up to 40%. P5 instances help you iterate on your solutions at a faster pace and get to market more quickly.

And to offer easy and predictable access to highly sought-after GPU compute capacity, AWS launched Amazon EC2 Capacity Blocks for ML. This is the first consumption model from a major cloud provider that lets you reserve GPUs for future use (up to 500 deployed in EC2 UltraClusters) to run short duration ML workloads.

AWS is also simplifying training with Amazon SageMaker HyperPod, which automates more of the processes required for high-scale fault-tolerant distributed training (e.g., configuring distributed training libraries, scaling training workloads across thousands of accelerators, detecting and repairing faulty instances), speeding up training by as much as 40%. Customers like Perplexity AI elastically scale beyond hundreds of GPUs and minimize their downtime with SageMaker HyperPod.

Deep-learning inference is another example of how AWS is continuing its cloud infrastructure innovations, including the low-cost, high-performance Amazon EC2 Inf2 instances powered by AWS Inferentia2. These instances are designed to run high-performance deep-learning inference applications at scale globally. They are the most cost-effective and energy-efficient option on Amazon EC2 for deploying the latest innovations in generative AI.

Another example is with Amazon SageMaker, which helps you deploy multiple models to the same instance so you can share compute resources—reducing inference cost by 50%. SageMaker also actively monitors instances that are processing inference requests and intelligently routes requests based on which instances are available—achieving 20% lower inference latency (on average).

AWS invests heavily in the tools for generative AI workloads. For AWS ML silicon, AWS has focused on AWS Neuron, the software development kit (SDK) that helps customers get the maximum performance from Trainium and Inferentia. Neuron supports the most popular publicly available models, including Llama 2 from Meta, MPT from Databricks, Mistral from mistral.ai, and Stable Diffusion from Stability AI, as well as 93 of the top 100 models on the popular model repository Hugging Face. It plugs into ML frameworks like PyTorch and TensorFlow, and support for JAX is coming early this year. It’s designed to make it easy for AWS customers to switch from their existing model training and inference pipelines to Trainium and Inferentia with just a few lines of code.

Cloud storage on AWS enhancements for generative AI

Another way AWS is accelerating the training and inference pipelines is with improvements to storage performance—which is not only critical when thinking about the most common ML tasks (like loading training data into a large cluster of GPUs/accelerators), but also for checkpointing and serving inference requests. AWS announced several improvements to accelerate the speed of storage requests and reduce the idle time of your compute resources—which allows you to run generative AI workloads faster and more efficiently.

To gather more accurate predictions, generative AI workloads are using larger and larger datasets that require high-performant storage at scale to handle the sheer volume in of data.

With Amazon S3 Express One Zone a new storage class purpose-built to high-performance and low-latency object storage for an organizations most frequently accessed data, making it ideal for request-intensive operations like ML training and inference. Amazon S3 Express One Zone is the lowest-latency cloud object storage available, with data access speed up to 10x faster and request costs up to 50% lower than Amazon S3 Standard, from any AWS Availability Zone within an AWS Region.

AWS continues to optimize data access speeds for ML frameworks too. Recently, Amazon S3 Connector for PyTorch launched, which loads training data up to 40% faster than with the existing PyTorch connectors to Amazon S3. While most customers can meet their training and inference requirements using Mountpoint for Amazon S3 or Amazon S3 Connector for PyTorch, some are also building and managing their own custom data loaders. To deliver the fastest data transfer speeds between Amazon S3, and Amazon EC2 Trn1, P4d, and P5 instances, AWS recently announced the ability to automatically accelerate Amazon S3 data transfer in the AWS Command Line Interface (AWS CLI) and Python SDK. Now, training jobs download training data from Amazon S3 up to 3x faster and customers like Scenario are already seeing great results, with a 5x throughput improvement to model download times without writing a single line of code.

To meet the changing performance requirements that training generative AI workloads can  require, Amazon FSx for Lustre announced throughput scaling on-demand. This is particularly useful for model training because it enables you to adjust the throughput tier of your file systems to meet these requirements with greater agility and lower cost.

EC2 networking enhancements for generative AI

Last year, AWS introduced EC2 UltraCluster 2.0, a flatter and wider network fabric that’s optimized specifically for the P5 instance and future ML accelerators. It allows us to reduce latency by 16% and supports up to 20,000 GPUs, with up to 10x the overall bandwidth. In a traditional cluster architecture, as clusters get physically bigger, latency will also generally increase. But, with UltraCluster 2.0, AWS is increasing the size while reducing latency, and that’s exciting.

AWS is also continuing to help you make your network more efficient. Take for example a recent launch with Amazon EC2 Instance Topology API. It gives you an inside look at the proximity between your instances, so you can place jobs strategically. Optimized job scheduling means faster processing for distributed workloads. Moving jobs that exchange data the most frequently to the same physical location in a cluster can eliminate multiple hops in the data path. As models push boundaries, this type of software innovation is key to getting the most out of your hardware.

In addition to Amazon Q (a generative AI powered assistant from AWS), AWS also launched Amazon Q networking troubleshooting (preview).

You can ask Amazon Q to assist you in troubleshooting network connectivity issues caused by network misconfiguration in your current AWS account. For this capability, Amazon Q works with Amazon VPC Reachability Analyzer to check your connections and inspect your network configuration to identify potential issues. With Amazon Q network troubleshooting, you can ask questions about your network in conversational English—for example, you can ask, “why can’t I SSH to my server,” or “why is my website not accessible”.

Conclusion

AWS is bringing customers even more choice for their infrastructure, including price-performant, sustainability focused, and ease-of-use options. Last year, AWS capabilities across this stack solidified our commitment to meeting the customer focus and goal of: Making generative AI accessible to customers of all sizes and technical abilities so they can get to reinventing and transforming what is possible.

Additional resources