Tag Archives: Amazon Lightsail

AWS Weekly Roundup: New capabilities in Amazon Bedrock, AWS Amplify Gen 2, Amazon RDS and more (May 13, 2024)

Post Syndicated from Abhishek Gupta original https://aws.amazon.com/blogs/aws/aws-weekly-roundup-new-capabilities-in-amazon-bedrock-aws-amplify-gen-2-amazon-rds-and-more-may-13-2024/

AWS Summit is in full swing around the world, with the most recent one being AWS Summit Singapore! Here is a sneak peek of the AWS staff and ASEAN community members at the Developer Lounge booth. It featured AWS Community speakers giving lightning talks on serverless, Amazon Elastic Kubernetes Service (Amazon EKS), security, generative AI, and more.

Last week’s launches
Here are some launches that caught my attention. Not surprisingly, a lot of interesting generative AI features!

Amazon Titan Text Premier is now available in Amazon Bedrock – This is the latest addition to the Amazon Titan family of large language models (LLMs) and offers optimized performance for key features like Retrieval Augmented Generation (RAG) on Knowledge Bases for Amazon Bedrock, and function calling on Agents for Amazon Bedrock.

Amazon Bedrock Studio is now available in public previewAmazon Bedrock Studio offers a web-based experience to accelerate the development of generative AI applications by providing a rapid prototyping environment with key Amazon Bedrock features, including Knowledge Bases, Agents, and Guardrails.

Amazon Bedrock Studio

Agents for Amazon Bedrock now supports Provisioned Throughput pricing model – As agentic applications scale, they require higher input and output model throughput compared to on-demand limits. The Provisioned Throughput pricing model makes it possible to purchase model units for the specific base model.

MongoDB Atlas is now available as a vector store in Knowledge Bases for Amazon Bedrock – With MongoDB Atlas vector store integration, you can build RAG solutions to securely connect your organization’s private data sources to foundation models (FMs) in Amazon Bedrock.

Amazon RDS for PostgreSQL supports pgvector 0.7.0 – You can use the open-source PostgreSQL extension for storing vector embeddings and add retrieval-augemented generation (RAG) capability in your generative AI applications. This release includes features that increase the number of dimensions of vectors you can index, reduce index size, and includes additional support for using CPU SIMD in distance computations. Also Amazon RDS Performance Insights now supports the Oracle Multitenant configuration on Amazon RDS for Oracle.

Amazon EC2 Inf2 instances are now available in new regions – These instances are optimized for generative AI workloads and are generally available in the Asia Pacific (Sydney), Europe (London), Europe (Paris), Europe (Stockholm), and South America (Sao Paulo) Regions.

New Generative Engine in Amazon Polly is now generally available – The generative engine in Amazon Polly is it’s most advanced text-to-speech (TTS) model and currently includes two American English voices, Ruth and Matthew, and one British English voice, Amy.

AWS Amplify Gen 2 is now generally availableAWS Amplify offers a code-first developer experience for building full-stack apps using TypeScript and enables developers to express app requirements like the data models, business logic, and authorization rules in TypeScript. AWS Amplify Gen 2 has added a number of features since the preview, including a new Amplify console with features such as custom domains, data management, and pull request (PR) previews.

Amazon EMR Serverless now includes performance monitoring of Apache Spark jobs with Amazon Managed Service for Prometheus – This lets you analyze, monitor, and optimize your jobs using job-specific engine metrics and information about Spark event timelines, stages, tasks, and executors. Also, Amazon EMR Studio is now available in the Asia Pacific (Melbourne) and Israel (Tel Aviv) Regions.

Amazon MemoryDB launched two new condition keys for IAM policies – The new condition keys let you create AWS Identity and Access Management (IAM) policies or Service Control Policies (SCPs) to enhance security and meet compliance requirements. Also, Amazon ElastiCache has updated it’s minimum TLS version to 1.2.

Amazon Lightsail now offers a larger instance bundle – This includes 16 vCPUs and 64 GB memory. You can now scale your web applications and run more compute and memory-intensive workloads in Lightsail.

Amazon Elastic Container Registry (ECR) adds pull through cache support for GitLab Container Registry – ECR customers can create a pull through cache rule that maps an upstream registry to a namespace in their private ECR registry. Once rule is configured, images can be pulled through ECR from GitLab Container Registry. ECR automatically creates new repositories for cached images and keeps them in-sync with the upstream registry.

AWS Resilience Hub expands application resilience drift detection capabilities – This new enhancement detects changes, such as the addition or deletion of resources within the application’s input sources.

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

Other AWS news
Here are some additional projects and blog posts that you might find interesting.

Building games with LLMs – Check out this fun experiment by Banjo Obayomi to generate Super Mario levels using different LLMs on Amazon Bedrock!

Troubleshooting with Amazon Q –  Ricardo Ferreira walks us through how he solved a nasty data serialization problem while working with Apache Kafka, Go, and Protocol Buffers.

Getting started with Amazon Q in VS Code – Check out this excellent step-by-step guide by Rohini Gaonkar that covers installing the extension for features like code completion chat, and productivity-boosting capabilities powered by generative AI.

AWS open source news and updates – My colleague Ricardo writes about open source projects, tools, and events from the AWS Community. Check out Ricardo’s page for the latest updates.

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

AWS Summits – Join free online and in-person events that bring the cloud computing community together to connect, collaborate, and learn about AWS. Register in your nearest city: Bengaluru (May 15–16), Seoul (May 16–17), Hong Kong (May 22), Milan (May 23), Stockholm (June 4), and Madrid (June 5).

AWS re:Inforce – Explore 2.5 days of immersive cloud security learning in the age of generative AI at AWS re:Inforce, June 10–12 in Pennsylvania.

AWS Community Days – Join community-led conferences that feature technical discussions, workshops, and hands-on labs led by expert AWS users and industry leaders from around the world: Turkey (May 18), Midwest | Columbus (June 13), Sri Lanka (June 27), Cameroon (July 13), Nigeria (August 24), and New York (August 28).

Browse all upcoming AWS led in-person and virtual events and developer-focused events.

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

— Abhishek

This post is part of our Weekly Roundup series. Check back each week for a quick roundup of interesting news and announcements from AWS!

AWS Weekly Roundup — Amazon API Gateway, AWS Step Functions, Amazon ECS, Amazon EKS, Amazon LightSail, Amazon VPC, and more — January 29, 2024

Post Syndicated from Sébastien Stormacq original https://aws.amazon.com/blogs/aws/aws-weekly-roundup-amazon-api-gateway-aws-step-functions-amazon-ecs-amazon-eks-amazon-lightsail-amazon-vpc-and-more-january-29-2024/

This past week our service teams continue to innovate on your behalf, and a lot has happened in the Amazon Web Services (AWS) universe. I’ll also share about all the AWS Community events and initiatives that are happening around the world.

Let’s dive in!

Last week’s launches
Here are some launches that got my attention:

AWS Step Functions adds integration for 33 services including Amazon Q – AWS Step Functions is a visual workflow service capable of orchestrating over 11,000+ API actions from over 220 AWS services to help customers build distributed applications at scale. This week, AWS Step Functions expands its AWS SDK integrations with support for 33 additional AWS services, including Amazon Q, AWS B2B Data Interchange, and Amazon CloudFront KeyValueStore.

Amazon Elastic Container Service (Amazon ECS) Service Connect introduces support for automatic traffic encryption with TLS Certificates – Amazon ECS launches support for automatic traffic encryption with Transport Layer Security (TLS) certificates for its networking capability called ECS Service Connect. With this support, ECS Service Connect allows your applications to establish a secure connection by encrypting your network traffic.

Amazon Elastic Kubernetes Service (Amazon EKS) and Amazon EKS Distro support Kubernetes version 1.29Kubernetes version 1.29 introduced several new features and bug fixes. You can create new EKS clusters using v1.29 and upgrade your existing clusters to v1.29 using the Amazon EKS console, the eksctl command line interface, or through an infrastructure-as-code (IaC) tool.

IPv6 instance bundles on Amazon Lightsail – With these new instance bundles, you can get up and running quickly on IPv6-only without the need for a public IPv4 address with the ease of use and simplicity of Amazon Lightsail. If you have existing Lightsail instances with a public IPv4 address, you can migrate your instances to IPv6-only in a few simple steps.

Amazon Virtual Private Cloud (Amazon VPC) supports idempotency for route table and network ACL creationIdempotent creation of route tables and network ACLs is intended for customers that use network orchestration systems or automation scripts that create route tables and network ACLs as part of a workflow. It allows you to safely retry creation without additional side effects.

Amazon Interactive Video Service (Amazon IVS) announces audio-only pricing for Low-Latency Streaming – Amazon IVS is a managed live streaming solution that is designed to make low-latency or real-time video available to viewers around the world. It now offers audio-only pricing for its Low-Latency Streaming capability at 1/10th of the existing HD video rate.

Sellers can resell third-party professional services in AWS Marketplace – AWS Marketplace sellers, including independent software vendors (ISVs), consulting partners, and channel partners, can now resell third-party professional services in AWS Marketplace. Services can include implementation, assessments, managed services, training, or premium support.

Introducing the AWS Small and Medium Business (SMB) Competency – This is the first go-to-market AWS Specialization designed for partners who deliver to small and medium-sized customers. The SMB Competency provides enhanced benefits for AWS Partners to invest and focus on SMB customer business, such as becoming the go-to standard for participation in new pilots and sales initiatives and receiving unique access to scale demand generation engines.

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

X in Y – We launched existing services and instance types in additional Regions:

Other AWS news
Here are some additional projects, programs, and news items that you might find interesting:

Get The NewsExport a Software Bill of Materials using Amazon Inspector – Generating an SBOM gives you critical security information that offers you visibility into specifics about your software supply chain, including the packages you use the most frequently and the related vulnerabilities that might affect your whole company. My colleague Varun Sharma in South Africa shows how to export a consolidated SBOM for the resources monitored by Amazon Inspector across your organization in industry standard formats, including CycloneDx and SPDX. It also shares insights and approaches for analyzing SBOM artifacts using Amazon Athena.

AWS open source news and updates – My colleague Ricardo writes this weekly open source newsletter in which he highlights new open source projects, tools, and demos from the AWS Community.

Upcoming AWS events
Check your calendars and sign up for these AWS events:

AWS InnovateAWS Innovate: AI/ML and Data Edition – Register now for the Asia Pacific & Japan AWS Innovate online conference on February 22, 2024, to explore, discover, and learn how to innovate with artificial intelligence (AI) and machine learning (ML). Choose from over 50 sessions in three languages and get hands-on with technical demos aimed at generative AI builders.

AWS Summit Paris 2024AWS Summit Paris  – The AWS Summit Paris is an annual event that is held in Paris, France. It is a great opportunity for cloud computing professionals from all over the world to learn about the latest AWS technologies, network with other professionals, and collaborate on projects. The Summit is free to attend and features keynote presentations, breakout sessions, and hands-on labs. Registrations are open!

AWS Community re:Invent re:CapsAWS Community re:Invent re:Caps – Join a Community re:Cap event organized by volunteers from AWS User Groups and AWS Cloud Clubs around the world to learn about the latest announcements from AWS re:Invent.

You can browse all upcoming in-person and virtual events.

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

— seb

This post is part of our Weekly Roundup series. Check back each week for a quick roundup of interesting news and announcements from AWS!

Announcing IPv6 instance bundles and pricing update on Amazon Lightsail

Post Syndicated from Macey Neff original https://aws.amazon.com/blogs/compute/announcing-ipv6-instance-bundles-and-pricing-update-on-amazon-lightsail/

Amazon Lightsail is the easiest way to get started on AWS, allowing you to get your application running on your own virtual server in a matter of minutes. Lightsail bundles all the resources you need like memory, vCPU, solid-state drive (SSD), and data transfer allowance into a predictable monthly price, so budgeting is easy and straightforward.

IPv6 instance bundles

Announcing the availability of new IPv6 instance bundles on Lightsail. With the new bundles, you can now create and use Lightsail instances without a public IPv4 address. These bundles include an IPv6 address for use cases that do not require a public IPv4 address. Both Linux and Windows IPv6 bundles are available. See the full list of Amazon Lightsail instance blueprints compatible with IPv6 instances. If you have existing Lightsail instances with a public IPv4 address, you can migrate the instance to IPv6-only in a couple of steps: Create a snapshot of an existing instance, then create a new instance from the snapshot and select IPv6-only networking when choosing your instance plan.

To learn more about IPv6 bundles, read Lightsail documentation.

IPv4 instance bundles

Lightsail will continue to offer bundles that include one public IPv4 address and IPv6 address. Following AWS’s announcement on public IPv4 address charge, the prices of Lightsail bundles offered with a public IPv4 address will reflect the charge associated with the public IPv4 address.

Revised prices for bundles that include a public IPv4 address will be effective on all new and existing Lightsail bundles starting May 1, 2024.

The tables below outline all Lightsail instance bundles and pricing.

Linux-based bundles:

Windows-based bundles:

*Bundles in the Asia Pacific (Mumbai) and Asia Pacific (Sydney) AWS Regions include lower data transfer allowances than other regions.

To learn more about Lightsail’s bundled offerings and pricing, please see the Lightsail pricing page.

Integrating AWS WAF with your Amazon Lightsail instance

Post Syndicated from Macey Neff original https://aws.amazon.com/blogs/compute/integrating-aws-waf-with-your-amazon-lightsail-instance/

This blog post is written by Riaz Panjwani, Solutions Architect, Canada CSC and Dylan Souvage, Solutions Architect, Canada CSC.

Security is the top priority at AWS. This post shows how you can level up your application security posture on your Amazon Lightsail instances with an AWS Web Application Firewall (AWS WAF) integration. Amazon Lightsail offers easy-to-use virtual private server (VPS) instances and more at a cost-effective monthly price.

Lightsail provides security functionality built-in with every instance through the Lightsail Firewall. Lightsail Firewall is a network-level firewall that enables you to define rules for incoming traffic based on IP addresses, ports, and protocols. Developers looking to help protect against attacks such as SQL injection, cross-site scripting (XSS), and distributed denial of service (DDoS) can leverage AWS WAF on top of the Lightsail Firewall.

As of this post’s publishing, AWS WAF can only be deployed on Amazon CloudFront, Application Load Balancer (ALB), Amazon API Gateway, and AWS AppSync. However, Lightsail can’t directly act as a target for these services because Lightsail instances run within an AWS managed Amazon Virtual Private Cloud (Amazon VPC). By leveraging VPC peering, you can deploy the aforementioned services in front of your Lightsail instance, allowing you to integrate AWS WAF with your Lightsail instance.

Solution Overview

This post shows you two solutions to integrate AWS WAF with your Lightsail instance(s). The first uses AWS WAF attached to an Internet-facing ALB. The second uses AWS WAF attached to CloudFront. By following one of these two solutions, you can utilize rule sets provided in AWS WAF to secure your application running on Lightsail.

Solution 1: ALB and AWS WAF

This first solution uses VPC peering and ALB to allow you to use AWS WAF to secure your Lightsail instances. This section guides you through the steps of creating a Lightsail instance, configuring VPC peering, creating a security group, setting up a target group for your load balancer, and integrating AWS WAF with your load balancer.

AWS architecture diagram showing Amazon Lightsail integration with WAF using VPC peering across two separate VPCs. The Lightsail application is in a private subnet inside the managed VPC(vpc-b), with peering connection to your VPC(vpc-a) which has an ALB in a public subnet with WAF attached to it.

Creating the Lightsail Instance

For this walkthrough, you can utilize an AWS Free Tier Linux-based WordPress blueprint.

1. Navigate to the Lightsail console and create the instance.

2. Verify that your Lightsail instance is online and obtain its private IP, which you will need when configuring the Target Group later.

Screenshot of Lightsail console with a WordPress application set up showcasing the networking tab.

Attaching an ALB to your Lightsail instance

You must enable VPC peering as you will be utilizing an ALB in a separate VPC.

1. To enable VPC peering, navigate to your account in the top-right corner, select the Account dropdown, select Account, then select Advanced, and select Enable VPC Peering. Note the AWS Region being selected, as it is necessary later. For this example, select “us-east-2”. Screenshot of Lightsail console in the settings menu under the advanced section showcasing VPC peering.2. In the AWS Management Console, navigate to the VPC service in the search bar, select VPC Peering Connections and verify the created peering connection.

Screenshot of the AWS Console showing the VPC Peering Connections menu with an active peering connection.

3. In the left navigation pane, select Security groups, and create a Security group that allows HTTP traffic (port 80). This is used later to allow public HTTP traffic to the ALB.

4. Navigate to the Amazon Elastic Compute Cloud (Amazon EC2) service, and in the left pane under Load Balancing select Target Groups. Proceed to create a Target Group, choosing IP addresses as the target type.Screenshot of the AWS console setting up target groups with the IP address target type selected.

5. Proceed to the Register targets section, and select Other private IP address. Add the private IP address of the Lightsail instance that you created before. Select Include as Pending below and then Create target group (note that if your Lightsail instance is re-launched the target group must be updated as the private IP address may change).

6. In the left pane, select Load Balancers, select Create load balancers and choose Application Load Balancer. Ensure that you select the “Internet-facing” scheme, otherwise, you will not be able to connect to your instance over the internet.Screenshot of the AWS console setting up target groups with the IP address target type selected.

7. Select the VPC in which you want your ALB to reside. In this example, select the default VPC and all the Availability Zones (AZs) to make sure of the high availability of the load balancer.

8. Select the Security Group created in Step 3 to make sure that public Internet traffic can pass through the load balancer.

9. Select the target group under Listeners and routing to the target group you created earlier (in Step 5). Proceed to Create load balancer.Screenshot of the AWS console creating an ALB with the target group created earlier in the blog, selected as the listener.

10. Retrieve the DNS name from your load balancer again by navigating to the Load Balancers menu under the EC2 service.Screenshot of the AWS console with load balancer created.

11. Verify that you can access your Lightsail instance using the Load Balancer’s DNS by copying the DNS name into your browser.

Screenshot of basic WordPress app launched accessed via a web browser.

Integrating AWS WAF with your ALB

Now that you have ALB successfully routing to the Lightsail instance, you can restrict the instance to only accept traffic from the load balancer, and then create an AWS WAF web Access Control List (ACL).

1. Navigate back to the Lightsail service, select the Lightsail instance previously created, and select Networking. Delete all firewall rules that allow public access, and under IPv4 Firewall add a rule that restricts traffic to the IP CIDR range of the VPC of the previously created ALB.

Screenshot of the Lightsail console showing the IPv4 firewall.

2. Now you can integrate the AWS WAF to the ALB. In the Console, navigate to the AWS WAF console, or simply navigate to your load balancer’s integrations section, and select Create web ACL.

Screenshot of the AWS console showing the WAF configuration in the integrations tab of the ALB.

3. Choose Create a web ACL, and then select Add AWS resources to add the previously created ALB.Screenshot of creating and assigning a web ACL to the ALB.

4. Add any rules you want to your ACL, these rules will govern the traffic allowed or denied to your resources. In this example, you can add the WordPress application managed rules.Screenshot of adding the AWS WAF managed rule for WordPress applications.

5. Leave all other configurations as default and create the AWS WAF.

6. You can verify your firewall is attached to the ALB in the load balancer Integrations section.Screenshot of the AWS console showing the WAF integration detected in the integrations tab of the ALB.

Solution 2: CloudFront and AWS WAF

Now that you have set up ALB and VPC peering to your Lightsail instance, you can optionally choose to add CloudFront to the solution. This can be done by setting up a custom HTTP header rule in the Listener of your ALB, setting up the CloudFront distribution to use the ALB as an origin, and setting up an AWS WAF web ACL for your new CloudFront distribution. This configuration makes traffic limited to only accessing your application through CloudFront, and is still protected by WAF.AWS architecture diagram showing Amazon Lightsail integration with WAF using VPC peering across two separate VPCs. The Lightsail application is in a public subnet inside VPC-B, with peering connection to VPC-A which has an ALB in a private subnet fronted with CloudFront that has WAF attached.

1. Navigate to the CloudFront service, and click Create distribution.

2. Under Origin domain, select the load balancer that you had created previously.Screenshot of creating a distribution in CloudFront.

3. Scroll down to the Add custom header field, and click Add header.

4. Create your header name and value. Note the header name and value as you will need it later in the walkthrough.Screenshot of adding the custom header to your CloudFront distribution.

5. Scroll down to the Cache key and origin requests section. Under Cache policy, choose CachingDisabled.Screenshot of selecting the CachingDisabled cache policy inside the creation of the CloudFront distribution.

6. Scroll to the Web Application Firewall (WAF) section, and select Enable security protections.Screenshot of selecting “Enable security protections” inside the creation of the CloudFront distribution.

7. Leave all other configurations as default, and click Create distribution.

8. Wait until your CloudFront distribution has been deployed, and verify that you can access your Lightsail application using the DNS under Domain name.

Screenshot of the CloudFront distribution created with the status as enabled and the deployment finished.

9. Navigate to the EC2 service, and in the left pane under Load Balancing, select Load Balancers.

10. Select the load balancer you created previously, and under the Listeners tab, select the Listener you had created previously. Select Actions in the top right and then select Manage rules.Screenshot of the Listener section of the ALB with the Manage rules being selected.

11. Select the edit icon at the top, and then select the edit icon beside the Default rule.

Screenshot of the edit section inside managed rules.

12. Select the delete icon to delete the Default Action.

Screenshot of highlighting the delete button inside the edit rules section.

13. Choose Add action and then select Return fixed response.

Screenshot of adding a new rule “Return fixed response…”.

14. For Response code, enter 403, this will restrict access to CloudFront.

15. For Response body, enter “Access Denied”.

16. Select Update in the top right corner to update the Default rule.

Screenshot of the rule being successfully updated.

17. Select the insert icon at the top, then select Insert Rule.

Screenshot of inserting a new rule to the Listener.

18. Choose Add Condition, then select Http header. For Header type, enter the Header name, and then for Value enter the Header Value chosen previously.

19. Choose Add Action, then select Forward to and select the target group you had created in the previous section.

20. Choose Save at the top right corner to create the rule.

Screenshot of adding a new rule to the Listener, with the Http header selected as the custom-header and custom-value from the previous creation of the CloudFront distribution, with the Load Balancer selected as the target group.

21. Retrieve the DNS name from your load balancer again by navigating to the Load Balancers menu under the EC2 service.

22. Verify that you can no longer access your Lightsail application using the Load Balancer’s DNS.

Screenshot of the Lightsail application being accessed through the Load Balancer via a web browser with Access Denied being shown..

23. Navigate back to the CloudFront service and select the Distribution you had created. Under the General tab, select the Web ACL link under the AWS WAF section. Modify the Web ACL to leverage any managed or custom rule sets.

Screenshot of the CloudFront distribution focusing on the AWS WAF integration under the General tab Settings.

You have successfully integrated AWS WAF to your Lightsail instance! You can access your Lightsail instance via your CloudFront distribution domain name!

Clean Up Lightsail console resources

To start, you will delete your Lightsail instance.

  1. Sign in to the Lightsail console.
  2. For the instance you want to delete, choose the actions menu icon (⋮), then choose Delete.
  3. Choose Yes to confirm the deletion.

Next you will delete your provisioned static IP.

  1. Sign in to the Lightsail console.
  2. On the Lightsail home page, choose the Networking tab.
  3. On the Networking page choose the vertical ellipsis icon next to the static IP address that you want to delete, and then choose Delete.

Finally you will disable VPC peering.

  1. In the Lightsail console, choose Account on the navigation bar.
  2. Choose Advanced.
  3. In the VPC peering section, clear Enable VPC peering for all AWS Regions.

Clean Up AWS console resources

To start, you will delete your Load balancer.

  1. Navigate to the EC2 console, choose Load balancers on the navigation bar.
  2. Select the load balancer you created previously.
  3. Under Actions, select Delete load balancer.

Next, you will delete your target group.

  1. Navigate to the EC2 console, choose Target Groups on the navigation bar.
  2. Select the target group you created previously.
  3. Under Actions, select Delete.

Now you will delete your CloudFront distribution.

  1. Navigate to the CloudFront console, choose Distributions on the navigation bar.
  2. Select the distribution you created earlier and select Disable.
  3. Wait for the distribution to finish deploying.
  4. Select the same distribution after it is finished deploying and select Delete.

Finally, you will delete your WAF ACL.

  1. Navigate to the WAF console, and select Web ACLS on the navigation bar.
  2. Select the web ACL you created previously, and select Delete.

Conclusion

Adding AWS WAF to your Lightsail instance enhances the security of your application by providing a robust layer of protection against common web exploits and vulnerabilities. In this post, you learned how to add AWS WAF to your Lightsail instance through two methods: Using AWS WAF attached to an Internet-facing ALB and using AWS WAF attached to CloudFront.

Security is top priority at AWS and security is an ongoing effort. AWS strives to help you build and operate architectures that protect information, systems, and assets while delivering business value. To learn more about Lightsail security, check out the AWS documentation for Security in Amazon Lightsail.

Create, Use, and Troubleshoot Launch Scripts on Amazon Lightsail

Post Syndicated from Macey Neff original https://aws.amazon.com/blogs/compute/create-use-and-troubleshoot-launch-scripts-on-amazon-lightsail/

This blog post is written by Brian Graf, Senior Developer Advocate, Amazon Lightsail and Sophia Parafina, Senior Developer Advocate. 

Amazon Lightsail is a virtual private server (VPS) for deploying both operating systems (OS) and pre-packaged applications, such as WordPress, Plesk, cPanel, PrestaShop, and more. When deploying these instances, you can run launch scripts with additional commands such as installation of applications, configuration of system files, or installing pre-requisites for your application.

Where do I add a launch script?

If you’re deploying an instance with the Lightsail console, launch scripts can be added to an instance at deployment. They are added in the ‘deploy instance’ page:

Image of Amazon Lightsail deploy an instance page

The launch script must be added before the instance is deployed, because launch scripts can’t retroactively run after deployment.

Anatomy of a Windows Launch Script

When deploying a Lightsail Windows instance, you can use a batch script or a PowerShell script in the ‘launch script’ textbox.  Of the two options, PowerShell is more extensible and provides greater flexibility for configuration and control.

If you choose to write your launch script as a batch file, you must add <script> </script> tags at the beginning and end of your code respectively. Alternatively, a launch script in PowerShell, must use the <powershell></powershell> tags in a similar fashion.

After the closing </script> or </powershell> tag, you must add a <persist></persist> tag on the following line. The persist tag is used to determine if this is a run-once command or if it should run every time your instance is rebooted or changed from the ‘Stop’ to ‘Start’ state. If you want your script to run every time the instance is rebooted or started, then you must set the persist tag to ‘true’. If you want your launch script to just run once, then you would set your persist tag to ‘false’.

Anatomy of a Linux Launch Script

Like a Windows launch script, a Linux launch script requires specific code on the first row of the textbox to successfully execute during deployment. You must place ‘#!/bin/bash’ as the first line of code to set the shell that executes the rest of the script. After first line of code, you can continue adding additional commands to achieve the results you want.

How do I know if my Launch Script ran successfully?

Although running launch scripts is convenient to create a baseline instance, it’s possible that your instance doesn’t achieve the desired end-state because of an error in your script or permissions issues. You must troubleshoot to see why the launch script didn’t complete successfully. To find if the launch script ran successfully, refer to the instance logs to determine whether your launch script was successful or not.

For Windows, the launch log can be found in: C:\ProgramData\Amazon\EC2-Windows\launch\Log\UserdataExecution.log. Note that ProgramData is a hidden folder, and unless you access the file from PowerShell or Command Prompt, you must use Windows File Explorer (`View > Show > Hidden items`) folders to see it.

For Linux, the launch log can be found in: /var/log/cloud-init-output.log and can be monitored after your instance launches by tailing the log by typing the following in the terminal:

tail -f /var/log/cloud-init-output.log

If you want to see the entire log file including commands that have already run before you opened the log file, then you can type the following in the terminal:

less +F /var/log/cloud-init-output.log

On a Windows instance, an easy way to monitor the UserdataExecution.log is to add the following code in your launch script, which creates a shortcut to tail or watch the log as commands are executing:

# Create a log-monitoring script to monitor the progress of the launch script execution

$monitorlogs = @"
get-content C:\ProgramData\Amazon\EC2-Windows\launch\Log\UserdataExecution.log -wait
"@

# Save the log-monitoring script to the desktop for the user

$monitorlogs | out-file -FilePath C:\Users\Administrator\Desktop\MonitorLogs.ps1 -Encoding utf8 -Force

</powershell>
<persist>false</persist>

If the script was executed, then the last line of the log should say ‘{Timestamp}: User data script completed’.

However, if you want more detail, you can build the logging into your launch script. For example, you can append a text or log file with each command so that you can read the output in an easy-to-access location:

<powershell>
# Set the location for the log file. In this case,
# it will appear on the desktop of your Lightsail instance
$loc = "c:\Users\Administrator\Desktop\mylog.txt"

# Write text to the log file
Write-Output "Starting Script" >> $loc

# Download and install Chocolatey to do unattended installations of the rest of the apps.
iex ((New-Object System.Net.WebClient).DownloadString('https://chocolatey.org/install.ps1'))

# You could run commands like this to output the progress to the log file:

# Install vscode and all dependencies
choco install -y vscode --force --force-dependencies --verbose >> $loc

# Install git and all dependencies
choco install -y git --force --force-dependencies --verbose >> $loc

# Completed
Write-Output "Completed" >> $loc
</powershell>
<persist>false</persist>

This code creates a log file, outputs data, and appends it along the way. If there is an issue, then you can see where the logs stopped or errors appeared.

For Ubuntu and Amazon Linux 2

If the cloud-init-output.log isn’t comprehensive enough, then you can re-direct the output from your commands to a log file of your choice. In this example, we create a log file in the /tmp/ directory and push all output from our commands to this file.

# Create the log file
touch /tmp/launchscript.log

# Add text to the log file if you so choose
echo 'Starting' >> /tmp/launchscript.log

# Update package index
sudo apt update >> /tmp/launchscript.log

# Install software to manage independent software vendor sources
sudo apt -y install software-properties-common >> /tmp/launchscript.log

# Add the repository for all PHP versions
sudo add-apt-repository -y ppa:ondrej/php >> /tmp/launchscript.log

# Install Web server, mySQL client, PHP (and packages), unzip, and curl
sudo apt -y install apache2 mysql-client-core-8.0 php8.0 libapache2-mod-php8.0 php8.0-common php8.0-imap php8.0-mbstring php8.0-xmlrpc php8.0-soap php8.0-gd php8.0-xml php8.0-intl php8.0-mysql php8.0-cli php8.0-bcmath php8.0-ldap php8.0-zip php8.0-curl unzip curl >> /tmp/launchscript.log

# Any final text you want to include
echo 'Completed' >> /tmp/launchscript.log

It’s possible to check the logs before the launch script has finished executing. One way to follow along is to ‘tail’ the log file. This lets you stream all updates as they occur. You can monitor the log using:

‘tail -f /tmp/launchscript.log’. </code>

Using Launch Scripts from AWS Command Line Interface (AWS CLI)

You can deploy their Lightsail instances from the AWS Command Line Interface (AWS CLI) instead of the Lightsail console. You can add launch scripts to the AWS CLI command as a parameter by creating a variable with the script and referencing the variable, or by saving the launch script as a file and referencing the local file location on your computer.

The launch script is still written the same way as the previous examples. For a Windows instance with a PowerShell launch script, you can deploy a Lightsail instance with a launch script with the following code:

# PowerShell script saved in the Downloads folder:

$loc = "c:\Users\Administrator\Desktop\mylog.txt"

# Write text to the log file

Write-Output "Starting Script" >> $loc

# Download and install Chocolatey to do unattended installations of the rest of the apps.

iex ((New-Object System.Net.WebClient).DownloadString('https://chocolatey.org/install.ps1'))

# You could run commands like this to output the progress to the log file:

# Install vscode and all dependencies

choco install -y vscode --force --force-dependencies --verbose >> $loc

# Install git and all dependencies

choco install -y git --force --force-dependencies --verbose >> $loc

# Completed

Write-Output "Completed" >> $loc

AWS CLI code to deploy a Windows Server 2019 medium instance in the us-west-2a Availability Zone:

aws lightsail create-instances \

--instance-names "my-windows-instance-1" \

--availability-zone us-west-2a \

--blueprint-id windows_server_2019 \

--bundle-id medium_win_2_0 \

--region us-west-2 \

--user-data file://~/Downloads/powershell_script.ps1

Clean up

Remember to delete resources when you are finished using them to avoid incurring future costs.

Conclusion

You now have the understanding and examples of how to create and troubleshoot Lightsail launch scripts both through the Lightsail console and AWS CLI. As demonstrated in this blog, using launch scripts, you can increase your productivity and decrease the deployment time and configuration of your applications. For more examples of using launch scripts, check out the aws-samples GitHub repository. You now have all the foundational building blocks you need to successfully script automated instance configuration. To learn more about Lightsail, visit the Lightsail service page.

New – Amazon Lightsail for Research with All-in-One Research Environments

Post Syndicated from Channy Yun original https://aws.amazon.com/blogs/aws/new-amazon-lightsail-for-research-with-all-in-one-research-environments/

Today we are announcing the general availability of Amazon Lightsail for Research, a new offering that makes it easy for researchers and students to create and manage a high-performance CPU or a GPU research computer in just a few clicks on the cloud. You can use your preferred integrated development environments (IDEs) like preinstalled Jupyter, RStudio, Scilab, VSCodium, or native Ubuntu operating system on your research computer.

You no longer need to use your own research laptop or shared school computers for analyzing larger datasets or running complex simulations. You can create your own research environments and directly access the application running on the research computer remotely via a web browser. Also, you can easily upload data to and download from your research computer via a simple web interface.

You pay only for the duration the computers are in use and can delete them at any time. You can also use budgeting controls that can automatically stop your computer when it’s not in use. Lightsail for Research also includes all-inclusive prices of compute, storage, and data transfer, so you know exactly how much you will pay for the duration you use the research computer.

Get Started with Amazon Lightsail for Research
To get started, navigate to the Lightsail for Research console, and choose Virtual computers in the left menu. You can see my research computers naming “channy-jupyter” or “channy-rstudio” already created.

Choose Create virtual computer to create a new research computer, and select which software you’d like preinstalled on your computer and what type of research computer you’d like to create.

In the first step, choose the application you want installed on your computer and the AWS Region to be located in. We support Jupyter, RStudio, Scilab, and VSCodium. You can install additional packages and extensions through the interface of these IDE applications.

Next, choose the desired virtual hardware type, including a fixed amount of compute (vCPUs or GPUs), memory (RAM), SSD-based storage volume (disk) space, and a monthly data transfer allowance. Bundles are charged on an hourly and on-demand basis.

Standard types are compute-optimized and ideal for compute-bound applications that benefit from high-performance processors.

Name vCPUs Memory Storage Monthly data
transfer allowance*
Standard XL 4 8 GB 50 GB 0.5TB
Standard 2XL 8 16 GB 50 GB 0.5TB
Standard 4XL 16 32 GB 50 GB 0.5TB

GPU types provide a high-performance platform for general-purpose GPU computing. You can use these bundles to accelerate scientific, engineering, and rendering applications and workloads.

Name GPU vCPUs Memory Storage Monthly data
transfer allowance*
GPU XL 1 4 16 GB 50 GB 1 TB
GPU 2XL 1 8 32 GB 50 GB 1 TB
GPU 4XL 1 16 64 GB 50 GB 1 TB

* AWS created the Global Data Egress Waiver (GDEW) program to help eligible researchers and academic institutions use AWS services by waiving data egress fees. To learn more, see the blog post.

After making your selections, name your computer and choose Create virtual computer to create your research computer. Once your computer is created and running, choose the Launch application button to open a new window that will display the preinstalled application you selected.

Lightsail for Research Features
As with existing Lightsail instances, you can create additional block-level storage volumes (disks) that you can attach to a running Lightsail for Research virtual computer. You can use a disk as a primary storage device for data that requires frequent and granular updates. To create your own storage, choose Storage and Create disk.

You can also create Snapshots, a point-in-time copy of your data. You can create a snapshot of your Lightsail for Research virtual computers and use it as baselines to create new computers or for data backup. A snapshot contains all of the data that is needed to restore your computer from the moment when the snapshot was taken.

When you restore a computer by creating it from a snapshot, you can easily create a new one or upgrade your computer to a larger size using a snapshot backup. Create snapshots frequently to protect your data from corrupt applications or user errors.

You can use Cost control rules that you define to help manage the usage and cost of your Lightsail for Research virtual computers. You can create rules that stop running computers when average CPU utilization over a selected time period falls below a prescribed level.

For example, you can configure a rule that automatically stops a specific computer when its CPU utilization is equal to or less than 1 percent for a 30-minute period. Lightsail for Research will then automatically stop the computer so that you don’t incur charges for running computers.

In the Usage menu, you can view the cost estimate and usage hours for your resources during a specified time period.

Now Available
Amazon Lightsail for Research is now available in the US East (Ohio), US West (Oregon), Asia Pacific (Mumbai), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Paris), Europe (Stockholm), and Europe (Sweden) Regions.

Now you can start using it today. To learn more, see the Amazon Lightsail for Research User Guide, and please send feedback to AWS re:Post for Amazon Lightsail or through your usual AWS support contacts.

Channy

AWS Week in Review – November 14, 2022

Post Syndicated from Steve Roberts original https://aws.amazon.com/blogs/aws/aws-week-in-review-november-14-2022/

It’s now just two weeks to AWS re:Invent in Las Vegas, and the pace is picking up, both here on the News Blog, and throughout AWS as everyone get ready for the big event! I hope you get the chance to join us, and have shared links and other information at the bottom of this post. First, though, let’s dive straight in to this week’s review of news and announcements from AWS.

Last Week’s Launches
As usual, let’s start with a summary of some launches from the last week that I want to remind you of:

New Switzerland Region – First and foremost, AWS has opened a new Region, this time in Switzerland. Check out Seb’s post here on the News Blog announcing the launch.

New AWS Resource Explorer – if you’ve ever spent time searching for specific resources in your AWS account, especially across Regions, be sure to take a look at the new AWS Resource Explorer, described in this post by Danilo. Once enabled, indexes of the resources in your account are built and maintained (you have control over which resources are indexed). Once the indexes are built, you can issue queries to more quickly arrive at the required resource without jumping between different Regions and service dashboards in the Management Console.

Amazon Lightsail domain registration and DNS autoconfigurationAmazon Lightsail users can now take advantage of new support for registering domain names with automatic configuration of DNS records. Within the Lightsail console, you’re now able to create and register an Amazon Route 53 domain with just a few clicks. 

New models for Amazon SageMaker JumpStart – Two new state-of-the-art models have been released for Amazon SageMaker JumpStart. SageMaker JumpStart provides pretrained, open-source models covering a wide variety of problem types that help you get started with machine learning. The first new model, Bloom, can be used to complete sentences or generate long paragraphs of text in 46 different languages. The second model, Stable Diffusion, generates realistic images from given text. Find out more about the new models in this What’s New post.

Mac instances and macOS VenturaAmazon Elastic Compute Cloud (Amazon EC2) now has support for running the latest version of macOS, Ventura (13.0), for both EC2 x86 Mac and EC2 M1 Mac instances. These instances enable you to provision and run macOS environments in the AWS Cloud, for developers creating apps for iPhone, iPad, Mac, Apple Watch, Apple TV, and Safari.

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

Other AWS News
Some other news items you may want to explore:

AWS Open Source News and Updates – This blog is published each week, and Installment 135 is now available, highlighting new open-source projects, tools, and demos from the AWS community.

Upcoming AWS Events
AWS re:Invent 2022 – As I noted at the top of this post, we’re now just two weeks away from the event! Join us live in Las Vegas November 28–December 2 for keynotes, opportunities for training and certification, and over 1,500 technical sessions. If you are joining us, be sure to check out the re:Invent 2022 Attendee Guides, each curated by an AWS Hero, AWS industry team, or AWS partner.

If you can’t join us live in Las Vegas, be sure to join us online to watch the keynotes and leadership sessions. My cohosts and I on the AWS on Air show will also be livestreaming daily from the event, chatting with service teams and special guests about all the launches and other announcements. You can find us on Twitch.tv (we’ll be on the front page throughout the event), the AWS channel on LinkedIn Live, Twitter.com/awsonair, and YouTube Live.

And one final update for the event – if you’re a .NET developer, be sure to check out the XNT track in the session catalog to find details on the seven breakouts, three chalk talks, and the workshop we have available for you at the conference!

Check back next Monday for our last week in review before the start of re:Invent!

— Steve

This post is part of our Week in Review series. Check back each week for a quick roundup of interesting news and announcements from AWS.

Choosing an AWS container service to run your modern application

Post Syndicated from Lewis Tang original https://aws.amazon.com/blogs/architecture/choosing-an-aws-container-service-to-run-your-modern-application/

Businesses want to innovate quickly and deliver value even faster. To achieve these goals, the platform needs to enable teams to focus on delivering applications that are reliable, secure, highly available, cost-efficient, and scalable to required sizes.

Consider including containers on AWS in your platform, whether you are trying containers for the first time, spinning out parts of an on-premises solution to microservices in the cloud, or are new to the cloud. Containers can help you achieving a range of business benefits, including increased scalability, agility, flexibility, and cost efficiency.

In this post, we discuss three sets of builder expectations and how AWS container services can help to meet with your application delivery requirements and choose the appropriate container platform service on AWS.

Decrease container platform operations management overhead

If managing a platform is not your business’s strategic focus (for example, if most of your engineers are code developers), it can be preferable to only manage application development.

Amazon Lightsail containers offer a simple way for developers to deploy their containers to the cloud. With a Docker image you provide for your containers, AWS automatically deploys containerized workloads for you.

Lightsail assigns an HTTPS endpoint that is ready to serve your web application running in the cloud container. It automatically sets up a load-balanced Transport Layer Security (TLS) endpoint and takes care of the TLS certificate. This service replaces unresponsive containers for you automatically; by assigning a Domain Name System to your endpoint, Lightsail maintains the old version until the new version is healthy and ready to go live (Figure 1).

Amazon Lightsail containers

Figure 1. Amazon Lightsail containers

Another simple way to build and run your containerized web application in AWS is using AWS App Runner, which provides a fully managed container-native service.

Without orchestrators to configure, build pipelines to set up, or load balancers to optimize, you can bring existing containers or use the integrated container build service to go directly from the code repository to deployed application.

The build service can connect to a GitHub repository, providing a Git push workflow that deploys changes automatically. App Runner orchestration workflow take cares of the build, deployment, and configuration tasks, such as host, runtime patching, monitoring load balancing, and auto scaling (Figure 2). Explore AWS App Runner documentation and workshop for more details about the service.

AWS App Runner

Figure 2. AWS App Runner

When designing an application, you often start with a whiteboard or mental model that has representations of each service and lines for how they interact with each other. When considering an application’s platform architecture, the cloud components are not limited to virtual private cloud (VPC) subnets, load balancers, deployment pipelines, and durable storage for your application’s stateful data. Bringing all underlying cloud components together and making sure the design is well architected can be challenging.

AWS Copilot can provide guided best practices when deploying a microservice architecture that includes multiple services deployed as containers. You can use Copliot to handle cloud component details for you. By providing a container image, Copilot works with App Runner or Amazon Elastic Container Service (Amazon ECS) to provision cloud components, like VPC and having Copilot handle high-availability deployment, load balancer creation, and configuration.

To automate application deployment and new version release, Copilot can create a deployment pipeline so that the latest version of your application is automatically deployed every time you push a new commit to your code repository (as demonstrated in Figure 3).

AWS Copilot pipeline

Figure 3. AWS Copilot pipeline

Full-control application deployment with container orchestration

As business grows, your application portfolio grows. Some applications may require the selection of Microsoft Windows containers or deep customizations on container-resource scheduling, monitoring, and logging. To accommodate this, you need the flexibility of configuring the required underlying container services while still using the efficient container orchestrator to automate the common processes to achieve operation efficiency. This is where Amazon ECS and Amazon Elastic Kubernetes Service (Amazon EKS) can help.

Using Amazon ECS

As demonstrated in Figure 4, Amazon ECS is a highly scalable, high-performance container management service that supports containers and allows you to easily run applications on a managed cluster of Amazon Elastic Compute Cloud instances with Amazon Fargate (a serverless compute engine for containers). With this, you can launch and stop containerized applications and query the complete state of your cluster. You have the ability to access and configure many familiar features, like security groups and Elastic Load Balancing (ELB), by sending simple API calls.

Amazon ECS can be used to schedule container placement across your cluster based on resource needs and availability requirements. You can also integrate your own scheduler or third-party schedulers to meet business- or application-specific requirements.

Amazon ECS using AWS Fargate

Figure 4. Amazon ECS using AWS Fargate

Using Amazon EKS

Amazon EKS is a managed service that can be used to run Kubernetes on AWS, without installing, operating, and maintaining your own Kubernetes control plane or nodes. For many developers who have experience using Kubernetes, running Amazon EKS for application container workload is a preferred option because Amazon EKS provides the flexibility of Kubernetes with the scalability, security and resiliency of being an AWS managed service.

Amazon EKS runs and automatically scales the Kubernetes control plane across multiple AWS availability zones to ensure high availability, as in Figure 5. The control plane instances are automatically scaled based on load. Amazon EKS detects and replaces unhealthy control plane instances and provides automated version updates and patching. Amazon EKS enables developers to run up-to-date versions of the open-source Kubernetes software, the existing or new third-party plugins, and tooling. This means you can more easily migrate any standard Kubernetes application to Amazon EKS without code modification.

Scalability and security are essential to your business-critical workloads. Amazon EKS is integrated with many AWS services, including Amazon Elastic Container Registry for container images, ELB for load distribution, IAM for authentication, and Amazon Virtual Private Cloud for isolation.

Amazon EKS scales Kubernetes across multiple availability zones

Figure 5. Amazon EKS scales Kubernetes across multiple availability zones

Conclusion

To innovate and respond to changes faster, businesses need to build modern applications quickly and manage them efficiently. AWS provides container services to run your most sensitive, secure, and business-critical workloads reliably and to-scale.

With little-to-no prior container experience, developers can use Lightsail containers to run web application container workloads with easy-to-use interface. App Runner simplifies application deployment and management down into one particular service for running web applications. With Copilot, you can get step-by-step best practice guidance when you need to deploy microservice architecture with multiple services deployed as containers. Amazon ECS and Amazon EKS give the flexibility of configuring container workloads while maintaining the application deployment and operational efficiency.

Further reading

Monitoring memory usage in Amazon Lightsail instance

Post Syndicated from Emma White original https://aws.amazon.com/blogs/compute/monitoring-memory-usage-lightsail-instance/

This post is written by Sebastian Lee, Solution Architect, Startup Singapore.

Amazon Lightsail is a great starting point for those looking to get started on AWS. Lightsail is ideal for startups, SMBs, and hobbyist developers because it simplifies the deployment of instances, databases, load-balancers, CDNs, and even containers. However, you cannot track metrics beyond  CPU utilization, network utilization, and error messages. Many startups and small businesses need to review more metrics like memory usage and disk usage.

In this blog, I walk through the steps to configure a Lightsail instance to send memory usage to Amazon CloudWatch for monitoring, alarming and notifications.

architecture overview

Product and Solution Overview

Amazon CloudWatch is a monitoring and observability service built for DevOps engineers, developers, site-reliability engineers and IT managers. CloudWatch collects monitoring and operational data in the form of logs, metrics, and events. It provides a unified view of your AWS resources, applications and services that run on AWS and on-premise servers. You can configure your Lightsail resources to work with Amazon CloudWatch to receive more metrics.

The following sections include steps to install a Cloudwatch agent on your Amazon Lightsail instance and configure it to have the necessary permission to send memory usage metrics to Amazon Cloudwatch.

Prerequisites

Before you begin the walkthrough, you must have an instance running in your Lightsail account. You can follow the steps here if you need help creating an instance.

Walkthrough

1. Create IAM user

First, you must create an IAM user to provide permission to send data to CloudWatch.

  1. Sign in to the AWS Management Console and open the IAM console.
  2. In the navigation pane, choose Users, and then choose Add user.
  3. Enter “lightsail-cloudwatch-agent” in the User name text box.
  4. For Access type, select Programmatic access, and then choose Next: Permissions.
  5. For Set permissions, choose Attach existing policies directly.
    1. In the list of policies, select the check box next to CloudWatchAgentServerPolicy. You can use the search text box to find the policy.
  6. Choose Next: Tags.
  7. Optionally, you can add one or more tag-key value pairs to organize, track, or control access for this role, and then choose Next: Review.
  8. Confirm that the correct policies are listed, and then choose Create user.
  9. In the row for the new user, choose Show. Copy the access key and secret key to a file so that you can use them when installing the agent.
    1. Important: You will not be able to copy the secret key after leaving this page. If you lose it, you will have to create a new oneconsole screenshot
  10. Choose Close.

Now that you created an IAM user, you can SSH into your Lightsail instance.

2. SSH into Amazon Lightsail instance

You can connect to your instance using the browser-based SSH client available in the Lightsail console, or by using your own SSH client with the SSH key of your instance.

Complete the following steps to connect to your instance using the browser-based SSH client in the Lightsail console:

  1. Open the Lightsail console.
  2. Click the terminal icon, next to the instance, as shown in the following screenshot.amazon lightsail console

3. Installing the CloudWatch agent

Now that you have SSH’d into your instance, you are ready to install the CloudWatch agent. The CloudWatch agent is available as a package on Amazon Linux 2 instances. For other operating systems, see Download and configure the CloudWatch agent using the command line.

Enter the following command to install the CloudWatch agent on a linux instance.

> sudo yum -y install amazon-cloudwatch-agent

========================================================================
Install 1 Package
…
Installed:
amazon-cloudwatch-agent.x86_64 0:1.247347.4-1.amzn2  

Complete!

4. Setup credentials

Now that you installed the CloudWatch Agent, you must allow it to access your AWS resources. First, setup the necessary credentials.

Enter the following command to create a credentials profile in the AWS Command Line Interface (AWS CLI).

Follow the prompts to enter the access key ID and secret access key you copied in the preceding steps.

> sudo aws configure --profile AmazonCloudWatchAgent

Follow the prompts to enter the access key ID and secret access key you copied earlier in this tutorial

AWS Access Key ID [None]: <Enter the access key from step 1>
AWS Secret Access Key [None]: <Enter the secret key from step 1>
Default region name [None]:
Default output format [None]:

5. Create CloudWatch configuration file to collect memory usage metrics

To tell CloudWatch agent to collect memory usage metrics, you will need to create a CloudWatch config file.

Enter the following command to create a config file for the CloudWatch agent.

> sudo vim /opt/aws/amazon-cloudwatch-agent/bin/config.json

Press “I” to enter insert mode in Vim, and paste the following text into the file.

{
    "agent": {
        "metrics_collection_interval": 60,
        "run_as_user": "root"
    },
    "metrics": {
	"append_dimensions": {
	    "ImageID": "${aws:ImageId}",
	    "InstanceId":"${aws:InstanceId}",
	    "InstanceType":"${aws:InstanceType}"
	},
        "metrics_collected": {
            "mem": {
                "measurement": [
                    "mem_used_percent"
                ],
                "metrics_collection_interval": 60
            }
        }
    }
}

Press “ESC”, and then type “:wq!” to save the file and exit Vim.

6. Configure CloudWatch agent

In this section, you configure the CloudWatch agent to use the shared credential profile created earlier.

Enter the following command to create a common configuration file for the CloudWatch agent.

> sudo vim /opt/aws/amazon-cloudwatch-agent/etc/common-config.toml

Press “I” to enter insert mode in Vim, and paste the following text into the file.

[credentials]
shared_credential_profile = "AmazonCloudWatchAgent"

Press “ESC”, and then type “:wq!” to save the file and exit Vim.

7. Start CloudWatch agent

Now the necessary configuration for CloudWatch agent is setup. Let’s start the agent.

Enter the following command to start the CloudWatch agent.

> sudo amazon-cloudwatch-agent-ctl -c file:/opt/aws/amazon-cloudwatch-agent/bin/config.json -a fetch-config -s 

****** processing cwagent-otel-collector ******
cwagent-otel-collector will not be started as it has not been configured yet.

****** processing amazon-cloudwatch-agent ******
…
Redirecting to /bin/systemctl restart amazon-cloudwatch-agent.service

Enter the following command to verify that the CloudWatch agent is running.

> sudo amazon-cloudwatch-agent-ctl -a status
{
  "status": "running",
  "starttime": "2021-04-16T10:34:27+0000",
  "configstatus": "configured",
  "cwoc_status": "stopped",
  "cwoc_starttime": "",
  "cwoc_configstatus": "not configured",
  "version": "1.247347.4"
}

8. Verify metrics in CloudWatch

At this point, you should be able to view your metrics in CloudWatch.

  1. Navigate to the CloudWatch console.
  2. On the left navigation panel, choose Metrics.
  3. Under “Custom Namespaces”, You should see a link for “CWAgent”.
  4. Choose CWAgent.
  5. Choose ImageId, InstanceId, InstanceType.
  6. Select checkbox to display metrics on graph.

cloudwatch metrics

In addition, you can create a CloudWatch alarm to monitor the memory usage metrics to automatically send you a notification when the metric reaches a threshold you specify. To create an alarm in CloudWatch, you can follow this guide.

Conclusion

In this blog, I covered how you can install the CloudWatch agent on your Amazon Lightsail instance to send memory metrics to Amazon CloudWatch. For more information on additional metrics and logs supported by CloudWatch Agent, see the CloudWatch User Guide

To get started with Amazon Lightsail, check out our getting started page for more tutorial and resources.

 

Frictionless hosting of containerized ASP.NET web apps using Amazon Lightsail

Post Syndicated from Emma White original https://aws.amazon.com/blogs/compute/frictionless-hosting-of-containerized-asp-net-web-apps-using-amazon-lightsail/

This post is written by Fahad Mustafa, Cloud Application Architect, AWS Professional Services

There are many ways to deploy ASP.NET web apps to AWS. Each with its own use cases and differing pricing models. But what if you have a small website and database that you must deploy rapidly, manage, and scale? What if you want a cost-effective simple monthly plan? In these cases, Amazon Lightsail is a great choice. This post shows you how to take a containerized ASP.NET web application that connects to a PostgreSQL database and deploy it to Lightsail. So that you can get your ASP.NET web app up and running.

Product Overview

Amazon Lightsail is an easy way to get started on AWS. It gives you building blocks to deploy an application or website and provision a database at an affordable, monthly price.

Lightsail is perfect for students, small businesses, and startups to get their website or application up and running in the cloud. By providing a secure, highly available, and managed environment Lightsail does all the heavy lifting like setting up IAM roles and policies.

Lightsail can also run containers! By pointing Lightsail to a public image on Amazon ECR or Docker Hub, or uploading an image from your local machine, you can easily run the container, scale it, monitor it and use a custom domain.

Overview of solution

To deploy an ASP.NET app that connects to a PostgreSQL database, you create a Lightsail container service and PostgreSQL database through the AWS Management Console. Create your app and container image. Push the image to Lightsail and finally create the Lightsail deployment to run the container.

solution diagram

Overview of steps

In this post, you create a sample ASP.NET web app through the .NET CLI. Alternatively, you can use Visual Studio to create the app.

This is the sequence of steps I review in this post:

  • Create a PostgreSQL database
  • Create a Lightsail container service
  • Create an ASP.NET web app
  • Create a Dockerfile and build image
  • Upload the image to Lightsail
  • Deploy and run the image

Prerequisites

For this walkthrough, you should have the following prerequisites:

Walkthrough

Create a PostgreSQL database

In this step, you create a PostgreSQL database through the Lightsail console.

Create the database

  1. Sign in to the Lightsail console.
  2. On the Lightsail home page, choose the Database
  3. Choose Create database.
  4. Choose the Database location by changing the AWS Region and Availability Zone.
  5. Choose the database engine. In this example, select PostgreSQL 12.6.
  6. Optional – Specify login credentials. If not changed, AWS generates a default secure password.
  7. Optional – Specify the master database name. If not changed, AWS will use “dbmaster” as the default.
  8. Choose the database plan. Compare the plan’s memory, CPU, storage, and transfer quota to decide which best fits your needs. The smallest database plan is Free Tier eligible.
  9. Identify your database by giving it a unique name.
  10. Choose Create database.

Creating and configuring the database can take a few minutes. Once ready, the status changes to Available. For more information and options on creating a database in Lightsail, see Creating a database in Amazon Lightsail.

available database

Now you are ready to connect to the database and create a table. To connect, see Connecting to your PostgreSQL database in Amazon Lightsail. This sample uses a database named aspnetlightsaildb and a table named Person that you can create by running the following script using PgAdmin. Note that the Owner value is dbmasteruser. This is the default username AWS generates. If you changed the default, then use the username you specified in step 6.

-- Database: aspnetlightsaildb
CREATE DATABASE aspnetlightsaildb
    WITH 
    OWNER = dbmasteruser
    ENCODING = 'UTF8'
    LC_COLLATE = 'en_US.UTF-8'
    LC_CTYPE = 'en_US.UTF-8'
    TABLESPACE = pg_default
    CONNECTION LIMIT = -1;	
-- Table: public.Person
CREATE TABLE IF NOT EXISTS public."Person"
(
    "Id" integer NOT NULL GENERATED ALWAYS AS IDENTITY ( INCREMENT 1 START 1 MINVALUE 1 MAXVALUE 2147483647 CACHE 1 ),
    "Name" text COLLATE pg_catalog."default",
    "DateOfBirth" date,
    "Address" text COLLATE pg_catalog."default",
    CONSTRAINT "Person_pkey" PRIMARY KEY ("Id")
)
TABLESPACE pg_default;
ALTER TABLE public."Person"
    OWNER to dbmasteruser;

Now your database and table is created and you can create a container service.

Create a Lightsail container service

In this step, you create a Lightsail container service that is ready to accept your container images.

Create the container service

  1. Sign in to the Lightsail console.
  2. On the Lightsail home page, choose the Containers Tab
  3. Choose Create container service.
  4. In the Create a container service page, choose Change AWS Region, then choose an AWS Region for your container service.
  5. Choose a capacity for your container service. For more information, see Container service capacity (scale and power).
  6. Skip the Set up your first deployment step as you’ll create the deployment after creating the container image on your dev machine.
  7. Enter a name for your container service. Take note of this name, you’ll need it later to deploy the container to Lightsail.
  8. Click Create container service.

After a few minutes, your container service status changes from Pending to Ready. This indicates you can now deploy images. If this is the first time you created a service, it can take 10–15 minutes for the status to become Ready.

container service

Create an ASP.NET web app

Using the .NET CLI, you’ll create a sample ASP.NET web app. In an empty directory run the following command:

dotnet new webapp --name HelloWorldLightsail

The “webapp” segment of the commands specifies the project template to use. In this case, it’s a default ASP.NET web app. The “name” parameter is the name of the ASP.NET project.

To connect to your PostgreSQL Db from ASP.NET, you must install the “Npgsql” Nuget package. In the root directory of the project run the following command in the terminal:

dotnet add package Npgsql.EntityFrameworkCore.PostgreSQL –-version 5.0.6

Once installed, you create a Model class to represent the data and a DbContext class to connect and query the database.

public class Person
    {
        public int Id { get; set; }

        public string Name { get; set; }

        public DateTime DateOfBirth { get; set; }

        public string Address { get; set; }
    }

public class PostgreSqlContext : DbContext
    {
        public PostgreSqlContext(DbContextOptions<PostgreSqlContext> options) : base(options)
        {
        }

        public DbSet<Person> Person { get; set; }
    }

The next step is to add the connection string to appSettings.json. In the root of the settings file add a new ConnectionStrings property as shown below. The following properties are required:

  • lightsail-endpoint: The database endpoint as shown in the Lightsail console.
  • db-name: The name of the database you want to connect to.
  • db-username: The username as shown in the Lightsail console.
  • db-password: The password as shown in the Lightsail console.
"ConnectionStrings": {
    "AspnetLightsailDb": "Server=<lightsail-endpoint>;Port=5432;Database=<db-name>;User Id=<db-username>;Password=<db-password>;"
  }

Next step is to tell ASP.NET where to find the connection string and which DbContext class to use. This is done by configuring the DbContext in Startup.cs. Under the ConfigureServices method add the following line of code:

  services.AddDbContext<PostgreSqlContext>(options => options.UseNpgsql(Configuration.GetConnectionString("AspnetLightsailDb")));

 

Now, you are ready to perform operations against the database. This is done by performing operations against the Person property of the PostgreSqlContext instance.

For example to fetch all records form the Person table:

public IList<Person> Person { get;set; }

        public async Task OnGetAsync()
        {
            Person = await _context.Person.ToListAsync();
        }

You now have an ASP.NET web application that can query the “Person” table against the PostgreSQL database.

Create a Dockerfile and build image

In order to containerize the web app, you must create a Dockerfile. This file provides instructions to Docker on how to build the container image.

To create a Dockerfile and build image

  1. In the root directory of the project, you created (where the .csproj file lives) create an empty file named “Dockerfile”. Note this file does not have an extension.
  2. Open the file with a text editor or IDE and insert the following:
# https://hub.docker.com/_/microsoft-dotnet
FROM mcr.microsoft.com/dotnet/sdk:5.0 AS build
WORKDIR /source

# copy csproj and restore as distinct layers
COPY *.csproj .
RUN dotnet restore

# copy everything else and build app
COPY . .
RUN dotnet publish -c release -o /app --no-restore

# final stage/image
FROM mcr.microsoft.com/dotnet/aspnet:5.0
WORKDIR /app
COPY --from=build /app ./
ENTRYPOINT ["dotnet", "HelloWorldLightsail.dll"]
  1. To build the image, open a terminal in the same directory as the Dockerfile. Run the following command to build the image.
    docker build -t helloworldlightsail .
    The “-t” parameter is a human readable tag you give the image to make it easy to identify.
  2. After the command completes, you can verify that the image exists by running
    docker images
    You should see the newly created image.newly created image

Upload the image to Lightsail

In this step, you upload the newly built image to the Lightsail container service that you created earlier.

To upload the image to Lightsail

  1. Ensure you have configured the AWS CLI to access AWS.
  2. In a terminal enter the following command:
    aws lightsail push-container-image --region ap-southeast-2 --service-name aspnet-helloworld --label helloworldlightsail --image helloworldlightsail:latest
    The –-region and –-service-name parameters should match the container service you created through the AWS Management Console. The –-label parameter is a descriptive name you give the image when it’s stored in the container service. This will help you track the different versions of the image. The –-image parameter consists of the image name and tag on your local machine that you want to push to Lightsail. Read more about how to push images to Lightsail.
  3. After the command runs successfully browse your container service in the Lightsail console and click the “Images” tab. You should see the uploaded image.

3. After the command runs successfully browse your container service in the Lightsail console and click the “Images” tab

Deploy and run the image

Now that your image is uploaded to the container service it’s time to create a deployment to run the app.

To create a deployment

  1. Go to the Deployments tab in the Lightsail console.
  2. Click on Create your first deployment.
  3. Enter the Container name.
  4. Click Choose stored image and select the image you uploaded in the previous step.
  5. Click on Add open ports to add a port mapping to the container. This allows Lightsail to forward web traffic to your ASP.NET web app. By default ASP.NET web server will listen to port 80.
  6. Under the Public endpoint section, select the container from the drop-down. This specifies which container Lightsail will forward traffic to since a single deployment can have more than one container.
  7. Click Save and deploy

Your configuration should looks like this. Read more about creating container services deployments in Lightsail.

configuration overview

After the deployment is complete, you can navigate to the Public domain of your container service. You will see your ASP.NET web app in action!

public domain

Conclusion

In this post, I demonstrated how easy it is to create a PostgreSQL DB and deploy an ASP.NET web app to Amazon Lightsail. Going from a container on your dev machine to a publicly accessible, scalable, and secure cloud environment within minutes.

You can now add a custom domain to your web app through the Lightsail console. Additionally, you can increase the scale of your container to keep up with demand based on the useful CPU and memory metrics provided in the console.

If you have more advanced needs for your web app, you have the whole robust ecosystem of AWS at your disposal. You can deploy your ASP.NET web app to Amazon Elastic Container Service (Amazon ECS) or even decide to go completely serverless and utilize AWS Lambda and API Gateway.

Visit the Amazon Lightsail homepage to get started with your next idea and read the docs for more details about container services on Amazon Lightsail.

 

Lightsail Containers: An Easy Way to Run your Containers in the Cloud

Post Syndicated from Sébastien Stormacq original https://aws.amazon.com/blogs/aws/lightsail-containers-an-easy-way-to-run-your-containers-in-the-cloud/

When I am delivering an introduction to the AWS Cloud for developers, I usually spend a bit of time to mention and to demonstrate Amazon Lightsail. It is by far the easiest way to get started on AWS. It allows you to get your application running on your own virtual server in a matter of minutes. Today, we are adding the possibility to deploy your container-based workloads on Amazon Lightsail. You can now deploy your container images to the cloud with the same simplicity and the same bundled pricing Amazon Lightsail provides for your virtual servers.

Amazon Lightsail is an easy-to-use cloud service that offers you everything needed to deploy an application or website, for a cost effective and easy to understand monthly plan. It is ideal to deploy simple workloads, websites, or to get started with AWS. The typical Lightsail customers range from developers to small businesses or startups who are looking to get quickly started in the cloud and AWS. At any time, you can later adopt the broad AWS Services when you are getting more familiar with the AWS cloud.

Under the hood, Lightsail is powered by Amazon Elastic Compute Cloud (EC2), Amazon Relational Database Service (RDS), Application Load Balancer, and other AWS services. It offers the level of security, reliability, and scalability you are expecting from AWS.

When deploying to Lightsail, you can choose between six operating systems (4 Linux distributions, FreeBSD, or Windows), seven applications (such as WordPress, Drupal, Joomla, Plesk…), and seven stacks (such as Node.js, Lamp, GitLab, Django…). But what about Docker containers?

Starting today, Amazon Lightsail offers an simple way for developers to deploy their containers to the cloud. All you need to provide is a Docker image for your containers and we automatically containerize it for you. Amazon Lightsail gives you an HTTPS endpoint that is ready to serve your application running in the cloud container. It automatically sets up a load balanced TLS endpoint, and take care of the TLS certificate. It replaces unresponsive containers for you automatically, it assigns a DNS name to your endpoint, it maintains the old version till the new version is healthy and ready to go live, and more.

Let’s see how it works by deploying a simple Python web app as a container. I assume you have the AWS Command Line Interface (CLI) and Docker installed on your laptop. Python is not required, it will be installed in the container only.

I first create a Python REST API, using the Flask simple application framework. Any programming language and any framework that can run inside a container works too. I just choose Python and Flask because they are simple and elegant.

You can safely copy /paste the following commands:

mkdir helloworld-python
cd helloworld-python
# create a simple Flask application in helloworld.py
echo "

from flask import Flask, request
from flask_restful import Resource, Api

app = Flask(__name__)
api = Api(app)

class Greeting (Resource):
   def get(self):
      return { "message" : "Hello Flask API World!" }
api.add_resource(Greeting, '/') # Route_1

if __name__ == '__main__':
   app.run('0.0.0.0','8080')

"  > helloworld.py

Then I create a Dockerfile that contains the steps and information required to build the container image:

# create a Dockerfile
echo '
FROM python:3
ADD helloworld.py /
RUN pip install flask
RUN pip install flask_restful
EXPOSE 8080
CMD [ "python", "./helloworld.py"]
 '  > Dockerfile

Now I can build my container:

docker build -t lightsail-hello-world .

The build command outputs many lines while it builds the container, it eventually terminates with the following message (actual ID differs):

Successfully built 7848e055edff
Successfully tagged lightsail-hello-world:latest

I test the container by launching it on my laptop:

docker run -it --rm -p 8080:8080 lightsail-hello-world

and connect a browser to localhost:8080

Testing Flask API in the container

When I am satisfied with my app, I push the container to Docker Hub.

docker tag lightsail-hello-world sebsto/lightsail-hello-world
docker login
docker push sebsto/lightsail-hello-world

Now that I have a container ready on Docker Hub, let’s create a Lightsail Container Service.

I point my browser to the Amazon Lightsail console. I can see container services already deployed and I can manage them. To create a new service, I click Create container service:Lighsail Container Console

On the next screen, I select the size of the container I want to use, in terms of vCPU and memory available to my application. I also select the number of container instances I want to run in parallel for high availability or scalability reasons. I can change the number of container instances or their power (vCPU and RAM) at any time, without interrupting the service. Both these parameters impact the price AWS charges you per month. The price is indicated and dynamically adjusted on the screen, as shown on the following video.

Lightsail choose capacity

Slightly lower on the screen, I choose to skip the deployment for now. I give a name for the service (“hello-world“). I click Create container service.

Lightsail container name

Once the service is created, I click Create your first deployment to create a deployment. A deployment is a combination of a specific container image and version to be deployed on the service I just created.

I chose a name for my image and give the address of the image on Docker Hub, using the format user/<my container name>:tag. This is also where I have the possibility to enter environment variables, port mapping, or a launch command.

My container is offering a network service on port TCP 8080, so I add that port to the deployment configuration. The Open Ports configuration specifies which ports and protocols are open to other systems in my container’s network. Other containers or virtual machines can only connect to my container when the port is explicitly configured in the console or EXPOSE‘d in my Dockerfile. None of these ports are exposed to the public internet.

But in this example, I also want Lightsail to route the traffic from the public internet to this container. So, I add this container as an endpoint of the hello-world service I just created. The endpoint is automatically configured for TLS, there is no certificate to install or manage.

I can add up to 10 containers for one single deployment. When ready, I click Save and deploy.

Lightsail Deployment

After a while, my deployment is active and I can test the endpoint.

Lightsail Deployment Active

The endpoint DNS address is available on the top-right side of the console. If I must, I can configure my own DNS domain name.

Lightsail endpoint DNSI open another tab in my browser and point it at the https endpoint URL:

Testing Container DeploymentWhen I must deploy a new version, I use the console again to modify the deployment. I spare you the details of modifying the application code, build, and push a new version of the container. Let’s say I have my second container image version available under the name sebsto/lightsail-hello-world:v2. Back to Amazon Lightsail console, I click Deployments, then Modify your Deployments. I enter the full name, including the tag, of the new version of the container image and click Save and Deploy.

Lightsail Deploy updated VersionAfter a while, the new version is deployed and automatically activated.

Lightsail deployment sucesful

I open a new tab in my browser and I point it to the endpoint URI available on the top-right corner of Amazon Lightsail console. I observe the JSON version is different. It now has a version attribute with a value of 2.

lightsail v2 is deployed

When something goes wrong during my deployment, Amazon Lightsail automatically keeps the last deployment active, to avoid any service interruption. I can also manually activate a previous deployment version to reverse any undesired changes.

I just deployed my first container image from Docker Hub. I can also manage my services and deploy local container images from my laptop using the AWS Command Line Interface (CLI). To push container images to my Amazon Lightsail container service directly from my laptop, I must install the LightSail Controler Plugin. (TL;DR curl, cp and chmod are your friends here, I also maintain a DockerFile to use the CLI inside a container.)

To create, list, or delete a container service, I type:

aws lightsail create-container-service --service-name myservice --power nano --scale 1

aws lightsail get-container-services
{
   "containerServices": [{
      "containerServiceName": "myservice",
      "arn": "arn:aws:lightsail:us-west-2:012345678901:ContainerService/1b50c121-eac7-4ee2-9078-425b0665b3d7",
      "createdAt": "2020-07-31T09:36:48.226999998Z",
      "location": {
         "availabilityZone": "all",
         "regionName": "us-west-2"
      },
      "resourceType": "ContainerService",
      "power": "nano",
      "powerId": "",
      "state": "READY",
      "scale": 1,
      "privateDomainName": "",
      "isDisabled": false,
      "roleArn": ""
   }]
}

aws lightsail delete-container-service --service myservice

I can also use the CLI to deploy container images directly from my laptop. Be sure lightsailctl is installed.

# Build the new version of my image (v3)
docker build -t sebsto/lightsail-hello-world:v3 .

# Push the new image.
aws lightsail push-container-image --service-name hello-world --label hello-world --image sebsto/lightsail-hello-world:v3

After a while, I see the output:

Image "sebsto/lightsail-hello-world:v3" registered.
Refer to this image as ":hello-world.hello-world.1" in deployments.

I create a lc.json file to hold the details of the deployment configuration. it is aligned to the options I see on the console. I report the name given by the previous command on the image property:

{
  "serviceName": "hello-world",
  "containers": {
     "hello-world": {
        "image": ":hello-world.hello-world.1",
        "ports": {
           "8080": "HTTP"
        }
     }
  },
  "publicEndpoint": {
     "containerName": "hello-world",
     "containerPort": 8080
  }
}

Finally, I create a new service version with:
aws lightsail create-container-service-deployment --cli-input-json file://lc.json

I can query the deployment status with
aws lightsail get-container-services

...
"nextDeployment": {
   "version": 4,
   "state": "ACTIVATING",
   "containers": {
      "hello-world": {
      "image": ":hello-world.hello-world.1",
      "command": [],
      "environment": {},
      "ports": {
         "8080": "HTTP"
      }
     }
},
...

After a while, the status  becomes  ACTIVE, and I can test my endpoint.

curl https://hello-world.nxxxxxxxxxxx.lightsail.ec2.aws.dev/
{"message": "Hello Flask API World!", "version": 3}

If you plan to later deploy your container to Amazon ECS or Amazon Elastic Kubernetes Service, no changes are required. You can pull the container image from your repository, just like you do with Amazon Lightsail.

You can deploy your containers on Lightsail in all AWS Regions where Amazon Lightsail is available. As of today, this is US East (Ohio), US East (N. Virginia), US West (Oregon), Asia Pacific (Mumbai), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), Europe (Ireland), Europe (London), and Europe (Paris).

As usual when using Amazon Lightsail, pricing is easy to understand and predictable. Amazon Lightsail Containers have a fixed price per month per container, depending on the size of the container (the vCPU/memory combination you use). You are charged on the prorated hours you keep the service running. The price per month is the maximum price you will be charged for running your service 24h/7. The prices are identical in all AWS Regions. They are ranging from $7 / month for a Nano container (512MB memory and 0.25 vCPU) to $160 / month for a X-Large container (8GB memory and 4 vCPU cores). This price not only includes the container itself, but also the load balancer, the DNS, and a generous data transfer tier. The details and prices for other AWS Regions are on the Lightsail pricing page.

I can’t wait to discover what solutions you will build and deploy on Amazon Lightsail Containers!

— seb