Tag Archives: load balancing

AWS Achieves Spain’s ENS High Certification Across 29 Services

Post Syndicated from Oliver Bell original https://aws.amazon.com/blogs/security/aws-achieves-spains-ens-high-certification-across-29-services/

AWS has achieved Spain’s Esquema Nacional de Seguridad (ENS) High certification across 29 services. To successfully achieve the ENS High Standard, BDO España conducted an independent audit and attested that AWS meets confidentiality, integrity, and availability standards. This provides the assurance needed by Spanish Public Sector organizations wanting to build secure applications and services on AWS.

The National Security Framework, regulated under Royal Decree 3/2010, was developed through close collaboration between ENAC (Entidad Nacional de Acreditación), the Ministry of Finance and Public Administration and the CCN (National Cryptologic Centre), and other administrative bodies.

The following AWS Services are ENS High accredited across our Dublin and Frankfurt Regions:

  • Amazon API Gateway
  • Amazon DynamoDB
  • Amazon Elastic Container Service
  • Amazon Elastic Block Store
  • Amazon Elastic Compute Cloud
  • Amazon Elastic File System
  • Amazon Elastic MapReduce
  • Amazon ElastiCache
  • Amazon Glacier
  • Amazon Redshift
  • Amazon Relational Database Service
  • Amazon Simple Queue Service
  • Amazon Simple Storage Service
  • Amazon Simple Workflow Service
  • Amazon Virtual Private Cloud
  • Amazon WorkSpaces
  • AWS CloudFormation
  • AWS CloudTrail
  • AWS Config
  • AWS Database Migration Service
  • AWS Direct Connect
  • AWS Directory Service
  • AWS Elastic Beanstalk
  • AWS Key Management Service
  • AWS Lambda
  • AWS Snowball
  • AWS Storage Gateway
  • Elastic Load Balancing
  • VM Import/Export

New AWS Auto Scaling – Unified Scaling For Your Cloud Applications

Post Syndicated from Jeff Barr original https://aws.amazon.com/blogs/aws/aws-auto-scaling-unified-scaling-for-your-cloud-applications/

I’ve been talking about scalability for servers and other cloud resources for a very long time! Back in 2006, I wrote “This is the new world of scalable, on-demand web services. Pay for what you need and use, and not a byte more.” Shortly after we launched Amazon Elastic Compute Cloud (EC2), we made it easy for you to do this with the simultaneous launch of Elastic Load Balancing, EC2 Auto Scaling, and Amazon CloudWatch. Since then we have added Auto Scaling to other AWS services including ECS, Spot Fleets, DynamoDB, Aurora, AppStream 2.0, and EMR. We have also added features such as target tracking to make it easier for you to scale based on the metric that is most appropriate for your application.

Introducing AWS Auto Scaling
Today we are making it easier for you to use the Auto Scaling features of multiple AWS services from a single user interface with the introduction of AWS Auto Scaling. This new service unifies and builds on our existing, service-specific, scaling features. It operates on any desired EC2 Auto Scaling groups, EC2 Spot Fleets, ECS tasks, DynamoDB tables, DynamoDB Global Secondary Indexes, and Aurora Replicas that are part of your application, as described by an AWS CloudFormation stack or in AWS Elastic Beanstalk (we’re also exploring some other ways to flag a set of resources as an application for use with AWS Auto Scaling).

You no longer need to set up alarms and scaling actions for each resource and each service. Instead, you simply point AWS Auto Scaling at your application and select the services and resources of interest. Then you select the desired scaling option for each one, and AWS Auto Scaling will do the rest, helping you to discover the scalable resources and then creating a scaling plan that addresses the resources of interest.

If you have tried to use any of our Auto Scaling options in the past, you undoubtedly understand the trade-offs involved in choosing scaling thresholds. AWS Auto Scaling gives you a variety of scaling options: You can optimize for availability, keeping plenty of resources in reserve in order to meet sudden spikes in demand. You can optimize for costs, running close to the line and accepting the possibility that you will tax your resources if that spike arrives. Alternatively, you can aim for the middle, with a generous but not excessive level of spare capacity. In addition to optimizing for availability, cost, or a blend of both, you can also set a custom scaling threshold. In each case, AWS Auto Scaling will create scaling policies on your behalf, including appropriate upper and lower bounds for each resource.

AWS Auto Scaling in Action
I will use AWS Auto Scaling on a simple CloudFormation stack consisting of an Auto Scaling group of EC2 instances and a pair of DynamoDB tables. I start by removing the existing Scaling Policies from my Auto Scaling group:

Then I open up the new Auto Scaling Console and selecting the stack:

Behind the scenes, Elastic Beanstalk applications are always launched via a CloudFormation stack. In the screen shot above, awseb-e-sdwttqizbp-stack is an Elastic Beanstalk application that I launched.

I can click on any stack to learn more about it before proceeding:

I select the desired stack and click on Next to proceed. Then I enter a name for my scaling plan and choose the resources that I’d like it to include:

I choose the scaling strategy for each type of resource:

After I have selected the desired strategies, I click Next to proceed. Then I review the proposed scaling plan, and click Create scaling plan to move ahead:

The scaling plan is created and in effect within a few minutes:

I can click on the plan to learn more:

I can also inspect each scaling policy:

I tested my new policy by applying a load to the initial EC2 instance, and watched the scale out activity take place:

I also took a look at the CloudWatch metrics for the EC2 Auto Scaling group:

Available Now
We are launching AWS Auto Scaling today in the US East (Northern Virginia), US East (Ohio), US West (Oregon), EU (Ireland), and Asia Pacific (Singapore) Regions today, with more to follow. There’s no charge for AWS Auto Scaling; you pay only for the CloudWatch Alarms that it creates and any AWS resources that you consume.

As is often the case with our new services, this is just the first step on what we hope to be a long and interesting journey! We have a long roadmap, and we’ll be adding new features and options throughout 2018 in response to your feedback.

Jeff;

Scale Your Web Application — One Step at a Time

Post Syndicated from Saurabh Shrivastava original https://aws.amazon.com/blogs/architecture/scale-your-web-application-one-step-at-a-time/

I often encounter people experiencing frustration as they attempt to scale their e-commerce or WordPress site—particularly around the cost and complexity related to scaling. When I talk to customers about their scaling plans, they often mention phrases such as horizontal scaling and microservices, but usually people aren’t sure about how to dive in and effectively scale their sites.

Now let’s talk about different scaling options. For instance if your current workload is in a traditional data center, you can leverage the cloud for your on-premises solution. This way you can scale to achieve greater efficiency with less cost. It’s not necessary to set up a whole powerhouse to light a few bulbs. If your workload is already in the cloud, you can use one of the available out-of-the-box options.

Designing your API in microservices and adding horizontal scaling might seem like the best choice, unless your web application is already running in an on-premises environment and you’ll need to quickly scale it because of unexpected large spikes in web traffic.

So how to handle this situation? Take things one step at a time when scaling and you may find horizontal scaling isn’t the right choice, after all.

For example, assume you have a tech news website where you did an early-look review of an upcoming—and highly-anticipated—smartphone launch, which went viral. The review, a blog post on your website, includes both video and pictures. Comments are enabled for the post and readers can also rate it. For example, if your website is hosted on a traditional Linux with a LAMP stack, you may find yourself with immediate scaling problems.

Let’s get more details on the current scenario and dig out more:

  • Where are images and videos stored?
  • How many read/write requests are received per second? Per minute?
  • What is the level of security required?
  • Are these synchronous or asynchronous requests?

We’ll also want to consider the following if your website has a transactional load like e-commerce or banking:

How is the website handling sessions?

  • Do you have any compliance requests—like the Payment Card Industry Data Security Standard (PCI DSS compliance) —if your website is using its own payment gateway?
  • How are you recording customer behavior data and fulfilling your analytics needs?
  • What are your loading balancing considerations (scaling, caching, session maintenance, etc.)?

So, if we take this one step at a time:

Step 1: Ease server load. We need to quickly handle spikes in traffic, generated by activity on the blog post, so let’s reduce server load by moving image and video to some third -party content delivery network (CDN). AWS provides Amazon CloudFront as a CDN solution, which is highly scalable with built-in security to verify origin access identity and handle any DDoS attacks. CloudFront can direct traffic to your on-premises or cloud-hosted server with its 113 Points of Presence (102 Edge Locations and 11 Regional Edge Caches) in 56 cities across 24 countries, which provides efficient caching.
Step 2: Reduce read load by adding more read replicas. MySQL provides a nice mirror replication for databases. Oracle has its own Oracle plug for replication and AWS RDS provide up to five read replicas, which can span across the region and even the Amazon database Amazon Aurora can have 15 read replicas with Amazon Aurora autoscaling support. If a workload is highly variable, you should consider Amazon Aurora Serverless database  to achieve high efficiency and reduced cost. While most mirror technologies do asynchronous replication, AWS RDS can provide synchronous multi-AZ replication, which is good for disaster recovery but not for scalability. Asynchronous replication to mirror instance means replication data can sometimes be stale if network bandwidth is low, so you need to plan and design your application accordingly.

I recommend that you always use a read replica for any reporting needs and try to move non-critical GET services to read replica and reduce the load on the master database. In this case, loading comments associated with a blog can be fetched from a read replica—as it can handle some delay—in case there is any issue with asynchronous reflection.

Step 3: Reduce write requests. This can be achieved by introducing queue to process the asynchronous message. Amazon Simple Queue Service (Amazon SQS) is a highly-scalable queue, which can handle any kind of work-message load. You can process data, like rating and review; or calculate Deal Quality Score (DQS) using batch processing via an SQS queue. If your workload is in AWS, I recommend using a job-observer pattern by setting up Auto Scaling to automatically increase or decrease the number of batch servers, using the number of SQS messages, with Amazon CloudWatch, as the trigger.  For on-premises workloads, you can use SQS SDK to create an Amazon SQS queue that holds messages until they’re processed by your stack. Or you can use Amazon SNS  to fan out your message processing in parallel for different purposes like adding a watermark in an image, generating a thumbnail, etc.

Step 4: Introduce a more robust caching engine. You can use Amazon Elastic Cache for Memcached or Redis to reduce write requests. Memcached and Redis have different use cases so if you can afford to lose and recover your cache from your database, use Memcached. If you are looking for more robust data persistence and complex data structure, use Redis. In AWS, these are managed services, which means AWS takes care of the workload for you and you can also deploy them in your on-premises instances or use a hybrid approach.

Step 5: Scale your server. If there are still issues, it’s time to scale your server.  For the greatest cost-effectiveness and unlimited scalability, I suggest always using horizontal scaling. However, use cases like database vertical scaling may be a better choice until you are good with sharding; or use Amazon Aurora Serverless for variable workloads. It will be wise to use Auto Scaling to manage your workload effectively for horizontal scaling. Also, to achieve that, you need to persist the session. Amazon DynamoDB can handle session persistence across instances.

If your server is on premises, consider creating a multisite architecture, which will help you achieve quick scalability as required and provide a good disaster recovery solution.  You can pick and choose individual services like Amazon Route 53, AWS CloudFormation, Amazon SQS, Amazon SNS, Amazon RDS, etc. depending on your needs.

Your multisite architecture will look like the following diagram:

In this architecture, you can run your regular workload on premises, and use your AWS workload as required for scalability and disaster recovery. Using Route 53, you can direct a precise percentage of users to an AWS workload.

If you decide to move all of your workloads to AWS, the recommended multi-AZ architecture would look like the following:

In this architecture, you are using a multi-AZ distributed workload for high availability. You can have a multi-region setup and use Route53 to distribute your workload between AWS Regions. CloudFront helps you to scale and distribute static content via an S3 bucket and DynamoDB, maintaining your application state so that Auto Scaling can apply horizontal scaling without loss of session data. At the database layer, RDS with multi-AZ standby provides high availability and read replica helps achieve scalability.

This is a high-level strategy to help you think through the scalability of your workload by using AWS even if your workload in on premises and not in the cloud…yet.

I highly recommend creating a hybrid, multisite model by placing your on-premises environment replica in the public cloud like AWS Cloud, and using Amazon Route53 DNS Service and Elastic Load Balancing to route traffic between on-premises and cloud environments. AWS now supports load balancing between AWS and on-premises environments to help you scale your cloud environment quickly, whenever required, and reduce it further by applying Amazon auto-scaling and placing a threshold on your on-premises traffic using Route 53.

Now Open AWS EU (Paris) Region

Post Syndicated from Jeff Barr original https://aws.amazon.com/blogs/aws/now-open-aws-eu-paris-region/

Today we are launching our 18th AWS Region, our fourth in Europe. Located in the Paris area, AWS customers can use this Region to better serve customers in and around France.

The Details
The new EU (Paris) Region provides a broad suite of AWS services including Amazon API Gateway, Amazon Aurora, Amazon CloudFront, Amazon CloudWatch, CloudWatch Events, Amazon CloudWatch Logs, Amazon DynamoDB, Amazon Elastic Compute Cloud (EC2), EC2 Container Registry, Amazon ECS, Amazon Elastic Block Store (EBS), Amazon EMR, Amazon ElastiCache, Amazon Elasticsearch Service, Amazon Glacier, Amazon Kinesis Streams, Polly, Amazon Redshift, Amazon Relational Database Service (RDS), Amazon Route 53, Amazon Simple Notification Service (SNS), Amazon Simple Queue Service (SQS), Amazon Simple Storage Service (S3), Amazon Simple Workflow Service (SWF), Amazon Virtual Private Cloud, Auto Scaling, AWS Certificate Manager (ACM), AWS CloudFormation, AWS CloudTrail, AWS CodeDeploy, AWS Config, AWS Database Migration Service, AWS Direct Connect, AWS Elastic Beanstalk, AWS Identity and Access Management (IAM), AWS Key Management Service (KMS), AWS Lambda, AWS Marketplace, AWS OpsWorks Stacks, AWS Personal Health Dashboard, AWS Server Migration Service, AWS Service Catalog, AWS Shield Standard, AWS Snowball, AWS Snowball Edge, AWS Snowmobile, AWS Storage Gateway, AWS Support (including AWS Trusted Advisor), Elastic Load Balancing, and VM Import.

The Paris Region supports all sizes of C5, M5, R4, T2, D2, I3, and X1 instances.

There are also four edge locations for Amazon Route 53 and Amazon CloudFront: three in Paris and one in Marseille, all with AWS WAF and AWS Shield. Check out the AWS Global Infrastructure page to learn more about current and future AWS Regions.

The Paris Region will benefit from three AWS Direct Connect locations. Telehouse Voltaire is available today. AWS Direct Connect will also become available at Equinix Paris in early 2018, followed by Interxion Paris.

All AWS infrastructure regions around the world are designed, built, and regularly audited to meet the most rigorous compliance standards and to provide high levels of security for all AWS customers. These include ISO 27001, ISO 27017, ISO 27018, SOC 1 (Formerly SAS 70), SOC 2 and SOC 3 Security & Availability, PCI DSS Level 1, and many more. This means customers benefit from all the best practices of AWS policies, architecture, and operational processes built to satisfy the needs of even the most security sensitive customers.

AWS is certified under the EU-US Privacy Shield, and the AWS Data Processing Addendum (DPA) is GDPR-ready and available now to all AWS customers to help them prepare for May 25, 2018 when the GDPR becomes enforceable. The current AWS DPA, as well as the AWS GDPR DPA, allows customers to transfer personal data to countries outside the European Economic Area (EEA) in compliance with European Union (EU) data protection laws. AWS also adheres to the Cloud Infrastructure Service Providers in Europe (CISPE) Code of Conduct. The CISPE Code of Conduct helps customers ensure that AWS is using appropriate data protection standards to protect their data, consistent with the GDPR. In addition, AWS offers a wide range of services and features to help customers meet the requirements of the GDPR, including services for access controls, monitoring, logging, and encryption.

From Our Customers
Many AWS customers are preparing to use this new Region. Here’s a small sample:

Societe Generale, one of the largest banks in France and the world, has accelerated their digital transformation while working with AWS. They developed SG Research, an application that makes reports from Societe Generale’s analysts available to corporate customers in order to improve the decision-making process for investments. The new AWS Region will reduce latency between applications running in the cloud and in their French data centers.

SNCF is the national railway company of France. Their mobile app, powered by AWS, delivers real-time traffic information to 14 million riders. Extreme weather, traffic events, holidays, and engineering works can cause usage to peak at hundreds of thousands of users per second. They are planning to use machine learning and big data to add predictive features to the app.

Radio France, the French public radio broadcaster, offers seven national networks, and uses AWS to accelerate its innovation and stay competitive.

Les Restos du Coeur, a French charity that provides assistance to the needy, delivering food packages and participating in their social and economic integration back into French society. Les Restos du Coeur is using AWS for its CRM system to track the assistance given to each of their beneficiaries and the impact this is having on their lives.

AlloResto by JustEat (a leader in the French FoodTech industry), is using AWS to to scale during traffic peaks and to accelerate their innovation process.

AWS Consulting and Technology Partners
We are already working with a wide variety of consulting, technology, managed service, and Direct Connect partners in France. Here’s a partial list:

AWS Premier Consulting PartnersAccenture, Capgemini, Claranet, CloudReach, DXC, and Edifixio.

AWS Consulting PartnersABC Systemes, Atos International SAS, CoreExpert, Cycloid, Devoteam, LINKBYNET, Oxalide, Ozones, Scaleo Information Systems, and Sopra Steria.

AWS Technology PartnersAxway, Commerce Guys, MicroStrategy, Sage, Software AG, Splunk, Tibco, and Zerolight.

AWS in France
We have been investing in Europe, with a focus on France, for the last 11 years. We have also been developing documentation and training programs to help our customers to improve their skills and to accelerate their journey to the AWS Cloud.

As part of our commitment to AWS customers in France, we plan to train more than 25,000 people in the coming years, helping them develop highly sought after cloud skills. They will have access to AWS training resources in France via AWS Academy, AWSome days, AWS Educate, and webinars, all delivered in French by AWS Technical Trainers and AWS Certified Trainers.

Use it Today
The EU (Paris) Region is open for business now and you can start using it today!

Jeff;

 

Now Open – AWS China (Ningxia) Region

Post Syndicated from Jeff Barr original https://aws.amazon.com/blogs/aws/now-open-aws-china-ningxia-region/

Today we launched our 17th Region globally, and the second in China. The AWS China (Ningxia) Region, operated by Ningxia Western Cloud Data Technology Co. Ltd. (NWCD), is generally available now and provides customers another option to run applications and store data on AWS in China.

The Details
At launch, the new China (Ningxia) Region, operated by NWCD, supports Auto Scaling, AWS Config, AWS CloudFormation, AWS CloudTrail, Amazon CloudWatch, CloudWatch Events, Amazon CloudWatch Logs, AWS CodeDeploy, AWS Direct Connect, Amazon DynamoDB, Amazon Elastic Compute Cloud (EC2), Amazon Elastic Block Store (EBS), Amazon EC2 Systems Manager, AWS Elastic Beanstalk, Amazon ElastiCache, Amazon Elasticsearch Service, Elastic Load Balancing, Amazon EMR, Amazon Glacier, AWS Identity and Access Management (IAM), Amazon Kinesis Streams, Amazon Redshift, Amazon Relational Database Service (RDS), Amazon Simple Storage Service (S3), Amazon Simple Notification Service (SNS), Amazon Simple Queue Service (SQS), AWS Support API, AWS Trusted Advisor, Amazon Simple Workflow Service (SWF), Amazon Virtual Private Cloud, and VM Import. Visit the AWS China Products page for additional information on these services.

The Region supports all sizes of C4, D2, M4, T2, R4, I3, and X1 instances.

Check out the AWS Global Infrastructure page to learn more about current and future AWS Regions.

Operating Partner
To comply with China’s legal and regulatory requirements, AWS has formed a strategic technology collaboration with NWCD to operate and provide services from the AWS China (Ningxia) Region. Founded in 2015, NWCD is a licensed datacenter and cloud services provider, based in Ningxia, China. NWCD joins Sinnet, the operator of the AWS China China (Beijing) Region, as an AWS operating partner in China. Through these relationships, AWS provides its industry-leading technology, guidance, and expertise to NWCD and Sinnet, while NWCD and Sinnet operate and provide AWS cloud services to local customers. While the cloud services offered in both AWS China Regions are the same as those available in other AWS Regions, the AWS China Regions are different in that they are isolated from all other AWS Regions and operated by AWS’s Chinese partners separately from all other AWS Regions. Customers using the AWS China Regions enter into customer agreements with Sinnet and NWCD, rather than with AWS.

Use it Today
The AWS China (Ningxia) Region, operated by NWCD, is open for business, and you can start using it now! Starting today, Chinese developers, startups, and enterprises, as well as government, education, and non-profit organizations, can leverage AWS to run their applications and store their data in the new AWS China (Ningxia) Region, operated by NWCD. Customers already using the AWS China (Beijing) Region, operated by Sinnet, can select the AWS China (Ningxia) Region directly from the AWS Management Console, while new customers can request an account at www.amazonaws.cn to begin using both AWS China Regions.

Jeff;

 

 

Now Available: A New AWS Quick Start Reference Deployment for CJIS

Post Syndicated from Emil Lerch original https://aws.amazon.com/blogs/security/now-available-a-new-aws-quick-start-reference-deployment-for-cjis/

CJIS logo

As part of the AWS Compliance Quick Start program, AWS has published a new Quick Start reference deployment for customers who need to align with Criminal Justice Information Services (CJIS) Security Policy 5.6 and process Criminal Justice Information (CJI) in accordance with this policy. The new Quick Start is AWS Enterprise Accelerator – Compliance: CJIS, and it makes it easier for you to address the list of supported controls you will find in the security controls matrix that accompanies the Quick Start.

As all AWS Quick Starts do, this Quick Start helps you automate the building of a recommended architecture that, when deployed as a package, provides a baseline AWS configuration. The Quick Start uses sets of nested AWS CloudFormation templates and user data scripts to create an example environment with a two-VPC, multi-tiered web service.

The new Quick Start also includes:

The recommended architecture built by the Quick Start supports a wide variety of AWS best practices (all of which are detailed in the Quick Start), including the use of multiple Availability Zones, isolation using public and private subnets, load balancing, and Auto Scaling.

The Quick Start package also includes a deployment guide with detailed instructions and a security controls matrix that describes how the deployment addresses CJIS Security Policy 5.6 controls. You should have your IT security assessors and risk decision makers review the security controls matrix so that they can understand the extent of the implementation of the controls within the architecture. The matrix also identifies the specific resources in the CloudFormation templates that affect each control, and contains cross-references to the CJIS Security Policy 5.6 security controls.

If you have questions about this new Quick Start, contact the AWS Compliance Quick Start team. For more information about the AWS CJIS program, see CJIS Compliance.

– Emil

Running Windows Containers on Amazon ECS

Post Syndicated from Nathan Taber original https://aws.amazon.com/blogs/compute/running-windows-containers-on-amazon-ecs/

This post was developed and written by Jeremy Cowan, Thomas Fuller, Samuel Karp, and Akram Chetibi.

Containers have revolutionized the way that developers build, package, deploy, and run applications. Initially, containers only supported code and tooling for Linux applications. With the release of Docker Engine for Windows Server 2016, Windows developers have started to realize the gains that their Linux counterparts have experienced for the last several years.

This week, we’re adding support for running production workloads in Windows containers using Amazon Elastic Container Service (Amazon ECS). Now, Amazon ECS provides an ECS-Optimized Windows Server Amazon Machine Image (AMI). This AMI is based on the EC2 Windows Server 2016 AMI, and includes Docker 17.06 Enterprise Edition and the ECS Agent 1.16. This AMI provides improved instance and container launch time performance. It’s based on Windows Server 2016 Datacenter and includes Docker 17.06.2-ee-5, along with a new version of the ECS agent that now runs as a native Windows service.

In this post, I discuss the benefits of this new support, and walk you through getting started running Windows containers with Amazon ECS.

When AWS released the Windows Server 2016 Base with Containers AMI, the ECS agent ran as a process that made it difficult to monitor and manage. As a service, the agent can be health-checked, managed, and restarted no differently than other Windows services. The AMI also includes pre-cached images for Windows Server Core 2016 and Windows Server Nano Server 2016. By caching the images in the AMI, launching new Windows containers is significantly faster. When Docker images include a layer that’s already cached on the instance, Docker re-uses that layer instead of pulling it from the Docker registry.

The ECS agent and an accompanying ECS PowerShell module used to install, configure, and run the agent come pre-installed on the AMI. This guarantees there is a specific platform version available on the container instance at launch. Because the software is included, you don’t have to download it from the internet. This saves startup time.

The Windows-compatible ECS-optimized AMI also reports CPU and memory utilization and reservation metrics to Amazon CloudWatch. Using the CloudWatch integration with ECS, you can create alarms that trigger dynamic scaling events to automatically add or remove capacity to your EC2 instances and ECS tasks.

Getting started

To help you get started running Windows containers on ECS, I’ve forked the ECS reference architecture, to build an ECS cluster comprised of Windows instances instead of Linux instances. You can pull the latest version of the reference architecture for Windows.

The reference architecture is a layered CloudFormation stack, in that it calls other stacks to create the environment. Within the stack, the ecs-windows-cluster.yaml file contains the instructions for bootstrapping the Windows instances and configuring the ECS cluster. To configure the instances outside of AWS CloudFormation (for example, through the CLI or the console), you can add the following commands to your instance’s user data:

Import-Module ECSTools
Initialize-ECSAgent

Or

Import-Module ECSTools
Initialize-ECSAgent –Cluster MyCluster -EnableIAMTaskRole

If you don’t specify a cluster name when you initialize the agent, the instance is joined to the default cluster.

Adding -EnableIAMTaskRole when initializing the agent adds support for IAM roles for tasks. Previously, enabling this setting meant running a complex script and setting an environment variable before you could assign roles to your ECS tasks.

When you enable IAM roles for tasks on Windows, it consumes port 80 on the host. If you have tasks that listen on port 80 on the host, I recommend configuring a service for them that uses load balancing. You can use port 80 on the load balancer, and the traffic can be routed to another host port on your container instances. For more information, see Service Load Balancing.

Create a cluster

To create a new ECS cluster, choose Launch stack, or pull the GitHub project to your local machine and run the following command:

aws cloudformation create-stack –template-body file://<path to master-windows.yaml> --stack-name <name>

Upload your container image

Now that you have a cluster running, step through how to build and push an image into a container repository. You use a repository hosted in Amazon Elastic Container Registry (Amazon ECR) for this, but you could also use Docker Hub. To build and push an image to a repository, install Docker on your Windows* workstation. You also create a repository and assign the necessary permissions to the account that pushes your image to Amazon ECR. For detailed instructions, see Pushing an Image.

* If you are building an image that is based on Windows layers, then you must use a Windows environment to build and push your image to the registry.

Write your task definition

Now that your image is built and ready, the next step is to run your Windows containers using a task.

Start by creating a new task definition based on the windows-simple-iis image from Docker Hub.

  1. Open the ECS console.
  2. Choose Task Definitions, Create new task definition.
  3. Scroll to the bottom of the page and choose Configure via JSON.
  4. Copy and paste the following JSON into that field.
  5. Choose Save, Create.
{
   "family": "windows-simple-iis",
   "containerDefinitions": [
   {
     "name": "windows_sample_app",
     "image": "microsoft/iis",
     "cpu": 100,
     "entryPoint":["powershell", "-Command"],
     "command":["New-Item -Path C:\\inetpub\\wwwroot\\index.html -Type file -Value '<html><head><title>Amazon ECS Sample App</title> <style>body {margin-top: 40px; background-color: #333;} </style> </head><body> <div style=color:white;text-align:center><h1>Amazon ECS Sample App</h1> <h2>Congratulations!</h2> <p>Your application is now running on a container in Amazon ECS.</p></body></html>'; C:\\ServiceMonitor.exe w3svc"],
     "portMappings": [
     {
       "protocol": "tcp",
       "containerPort": 80,
       "hostPort": 8080
     }
     ],
     "memory": 500,
     "essential": true
   }
   ]
}

You can now go back into the Task Definition page and see windows-simple-iis as an available task definition.

There are a few important aspects of the task definition file to note when working with Windows containers. First, the hostPort is configured as 8080, which is necessary because the ECS agent currently uses port 80 to enable IAM roles for tasks required for least-privilege security configurations.

There are also some fairly standard task parameters that are intentionally not included. For example, network mode is not available with Windows at the time of this release, so keep that setting blank to allow Docker to configure WinNAT, the only option available today.

Also, some parameters work differently with Windows than they do with Linux. The CPU limits that you define in the task definition are absolute, whereas on Linux they are weights. For information about other task parameters that are supported or possibly different with Windows, see the documentation.

Run your containers

At this point, you are ready to run containers. There are two options to run containers with ECS:

  1. Task
  2. Service

A task is typically a short-lived process that ECS creates. It can’t be configured to actively monitor or scale. A service is meant for longer-running containers and can be configured to use a load balancer, minimum/maximum capacity settings, and a number of other knobs and switches to help ensure that your code keeps running. In both cases, you are able to pick a placement strategy and a specific IAM role for your container.

  1. Select the task definition that you created above and choose Action, Run Task.
  2. Leave the settings on the next page to the default values.
  3. Select the ECS cluster created when you ran the CloudFormation template.
  4. Choose Run Task to start the process of scheduling a Docker container on your ECS cluster.

You can now go to the cluster and watch the status of your task. It may take 5–10 minutes for the task to go from PENDING to RUNNING, mostly because it takes time to download all of the layers necessary to run the microsoft/iis image. After the status is RUNNING, you should see the following results:

You may have noticed that the example task definition is named windows-simple-iis:2. This is because I created a second version of the task definition, which is one of the powerful capabilities of using ECS. You can make the task definitions part of your source code and then version them. You can also roll out new versions and practice blue/green deployment, switching to reduce downtime and improve the velocity of your deployments!

After the task has moved to RUNNING, you can see your website hosted in ECS. Find the public IP or DNS for your ECS host. Remember that you are hosting on port 8080. Make sure that the security group allows ingress from your client IP address to that port and that your VPC has an internet gateway associated with it. You should see a page that looks like the following:

This is a nice start to deploying a simple single instance task, but what if you had a Web API to be scaled out and in based on usage? This is where you could look at defining a service and collecting CloudWatch data to add and remove both instances of the task. You could also use CloudWatch alarms to add more ECS container instances and keep up with the demand. The former is built into the configuration of your service.

  1. Select the task definition and choose Create Service.
  2. Associate a load balancer.
  3. Set up Auto Scaling.

The following screenshot shows an example where you would add an additional task instance when the CPU Utilization CloudWatch metric is over 60% on average over three consecutive measurements. This may not be aggressive enough for your requirements; it’s meant to show you the option to scale tasks the same way you scale ECS instances with an Auto Scaling group. The difference is that these tasks start much faster because all of the base layers are already on the ECS host.

Do not confuse task dynamic scaling with ECS instance dynamic scaling. To add additional hosts, see Tutorial: Scaling Container Instances with CloudWatch Alarms.

Conclusion

This is just scratching the surface of the flexibility that you get from using containers and Amazon ECS. For more information, see the Amazon ECS Developer Guide and ECS Resources.

– Jeremy, Thomas, Samuel, Akram

AWS Systems Manager – A Unified Interface for Managing Your Cloud and Hybrid Resources

Post Syndicated from Randall Hunt original https://aws.amazon.com/blogs/aws/aws-systems-manager/

AWS Systems Manager is a new way to manage your cloud and hybrid IT environments. AWS Systems Manager provides a unified user interface that simplifies resource and application management, shortens the time to detect and resolve operational problems, and makes it easy to operate and manage your infrastructure securely at scale. This service is absolutely packed full of features. It defines a new experience around grouping, visualizing, and reacting to problems using features from products like Amazon EC2 Systems Manager (SSM) to enable rich operations across your resources.

As I said above, there are a lot of powerful features in this service and we won’t be able to dive deep on all of them but it’s easy to go to the console and get started with any of the tools.

Resource Groupings

Resource Groups allow you to create logical groupings of most resources that support tagging like: Amazon Elastic Compute Cloud (EC2) instances, Amazon Simple Storage Service (S3) buckets, Elastic Load Balancing balancers, Amazon Relational Database Service (RDS) instances, Amazon Virtual Private Cloud, Amazon Kinesis streams, Amazon Route 53 zones, and more. Previously, you could use the AWS Console to define resource groupings but AWS Systems Manager provides this new resource group experience via a new console and API. These groupings are a fundamental building block of Systems Manager in that they are frequently the target of various operations you may want to perform like: compliance management, software inventories, patching, and other automations.

You start by defining a group based on tag filters. From there you can view all of the resources in a centralized console. You would typically use these groupings to differentiate between applications, application layers, and environments like production or dev – but you can make your own rules about how to use them as well. If you imagine a typical 3 tier web-app you might have a few EC2 instances, an ELB, a few S3 buckets, and an RDS instance. You can define a grouping for that application and with all of those different resources simultaneously.

Insights

AWS Systems Manager automatically aggregates and displays operational data for each resource group through a dashboard. You no longer need to navigate through multiple AWS consoles to view all of your operational data. You can easily integrate your exiting Amazon CloudWatch dashboards, AWS Config rules, AWS CloudTrail trails, AWS Trusted Advisor notifications, and AWS Personal Health Dashboard performance and availability alerts. You can also easily view your software inventories across your fleet. AWS Systems Manager also provides a compliance dashboard allowing you to see the state of various security controls and patching operations across your fleets.

Acting on Insights

Building on the success of EC2 Systems Manager (SSM), AWS Systems Manager takes all of the features of SSM and provides a central place to access them. These are all the same experiences you would have through SSM with a more accesible console and centralized interface. You can use the resource groups you’ve defined in Systems Manager to visualize and act on groups of resources.

Automation


Automations allow you to define common IT tasks as a JSON document that specify a list of tasks. You can also use community published documents. These documents can be executed through the Console, CLIs, SDKs, scheduled maintenance windows, or triggered based on changes in your infrastructure through CloudWatch events. You can track and log the execution of each step in the documents and prompt for additional approvals. It also allows you to incrementally roll out changes and automatically halt when errors occur. You can start executing an automation directly on a resource group and it will be able to apply itself to the resources that it understands within the group.

Run Command

Run Command is a superior alternative to enabling SSH on your instances. It provides safe, secure remote management of your instances at scale without logging into your servers, replacing the need for SSH bastions or remote powershell. It has granular IAM permissions that allow you to restrict which roles or users can run certain commands.

Patch Manager, Maintenance Windows, and State Manager

I’ve written about Patch Manager before and if you manage fleets of Windows and Linux instances it’s a great way to maintain a common baseline of security across your fleet.

Maintenance windows allow you to schedule instance maintenance and other disruptive tasks for a specific time window.

State Manager allows you to control various server configuration details like anti-virus definitions, firewall settings, and more. You can define policies in the console or run existing scripts, PowerShell modules, or even Ansible playbooks directly from S3 or GitHub. You can query State Manager at any time to view the status of your instance configurations.

Things To Know

There’s some interesting terminology here. We haven’t done the best job of naming things in the past so let’s take a moment to clarify. EC2 Systems Manager (sometimes called SSM) is what you used before today. You can still invoke aws ssm commands. However, AWS Systems Manager builds on and enhances many of the tools provided by EC2 Systems Manager and allows those same tools to be applied to more than just EC2. When you see the phrase “Systems Manager” in the future you should think of AWS Systems Manager and not EC2 Systems Manager.

AWS Systems Manager with all of this useful functionality is provided at no additional charge. It is immediately available in all public AWS regions.

The best part about these services is that even with their tight integrations each one is designed to be used in isolation as well. If you only need one component of these services it’s simple to get started with only that component.

There’s a lot more than I could ever document in this post so I encourage you all to jump into the console and documentation to figure out where you can start using AWS Systems Manager.

Randall

AWS Fargate: A Product Overview

Post Syndicated from Deepak Dayama original https://aws.amazon.com/blogs/compute/aws-fargate-a-product-overview/

It was just about three years ago that AWS announced Amazon Elastic Container Service (Amazon ECS), to run and manage containers at scale on AWS. With Amazon ECS, you’ve been able to run your workloads at high scale and availability without having to worry about running your own cluster management and container orchestration software.

Today, AWS announced the availability of AWS Fargate – a technology that enables you to use containers as a fundamental compute primitive without having to manage the underlying instances. With Fargate, you don’t need to provision, configure, or scale virtual machines in your clusters to run containers. Fargate can be used with Amazon ECS today, with plans to support Amazon Elastic Container Service for Kubernetes (Amazon EKS) in the future.

Fargate has flexible configuration options so you can closely match your application needs and granular, per-second billing.

Amazon ECS with Fargate

Amazon ECS enables you to run containers at scale. This service also provides native integration into the AWS platform with VPC networking, load balancing, IAM, Amazon CloudWatch Logs, and CloudWatch metrics. These deep integrations make the Amazon ECS task a first-class object within the AWS platform.

To run tasks, you first need to stand up a cluster of instances, which involves picking the right types of instances and sizes, setting up Auto Scaling, and right-sizing the cluster for performance. With Fargate, you can leave all that behind and focus on defining your application and policies around permissions and scaling.

The same container management capabilities remain available so you can continue to scale your container deployments. With Fargate, the only entity to manage is the task. You don’t need to manage the instances or supporting software like Docker daemon or the Amazon ECS agent.

Fargate capabilities are available natively within Amazon ECS. This means that you don’t need to learn new API actions or primitives to run containers on Fargate.

Using Amazon ECS, Fargate is a launch type option. You continue to define the applications the same way by using task definitions. In contrast, the EC2 launch type gives you more control of your server clusters and provides a broader range of customization options.

For example, a RunTask command example is pasted below with the Fargate launch type:

ecs run-task --launch-type FARGATE --cluster fargate-test --task-definition nginx --network-configuration
"awsvpcConfiguration={subnets=[subnet-b563fcd3]}"

Key features of Fargate

Resource-based pricing and per second billing
You pay by the task size and only for the time for which resources are consumed by the task. The price for CPU and memory is charged on a per-second basis. There is a one-minute minimum charge.

Flexible configurations options
Fargate is available with 50 different combinations of CPU and memory to closely match your application needs. You can use 2 GB per vCPU anywhere up to 8 GB per vCPU for various configurations. Match your workload requirements closely, whether they are general purpose, compute, or memory optimized.

Networking
All Fargate tasks run within your own VPC. Fargate supports the recently launched awsvpc networking mode and the elastic network interface for a task is visible in the subnet where the task is running. This provides the separation of responsibility so you retain full control of networking policies for your applications via VPC features like security groups, routing rules, and NACLs. Fargate also supports public IP addresses.

Load Balancing
ECS Service Load Balancing  for the Application Load Balancer and Network Load Balancer is supported. For the Fargate launch type, you specify the IP addresses of the Fargate tasks to register with the load balancers.

Permission tiers
Even though there are no instances to manage with Fargate, you continue to group tasks into logical clusters. This allows you to manage who can run or view services within the cluster. The task IAM role is still applicable. Additionally, there is a new Task Execution Role that grants Amazon ECS permissions to perform operations such as pushing logs to CloudWatch Logs or pulling image from Amazon Elastic Container Registry (Amazon ECR).

Container Registry Support
Fargate provides seamless authentication to help pull images from Amazon ECR via the Task Execution Role. Similarly, if you are using a public repository like DockerHub, you can continue to do so.

Amazon ECS CLI
The Amazon ECS CLI provides high-level commands to help simplify to create and run Amazon ECS clusters, tasks, and services. The latest version of the CLI now supports running tasks and services with Fargate.

EC2 and Fargate Launch Type Compatibility
All Amazon ECS clusters are heterogeneous – you can run both Fargate and Amazon ECS tasks in the same cluster. This enables teams working on different applications to choose their own cadence of moving to Fargate, or to select a launch type that meets their requirements without breaking the existing model. You can make an existing ECS task definition compatible with the Fargate launch type and run it as a Fargate service, and vice versa. Choosing a launch type is not a one-way door!

Logging and Visibility
With Fargate, you can send the application logs to CloudWatch logs. Service metrics (CPU and Memory utilization) are available as part of CloudWatch metrics. AWS partners for visibility, monitoring and application performance management including Datadog, Aquasec, Splunk, Twistlock, and New Relic also support Fargate tasks.

Conclusion

Fargate enables you to run containers without having to manage the underlying infrastructure. Today, Fargate is availabe for Amazon ECS, and in 2018, Amazon EKS. Visit the Fargate product page to learn more, or get started in the AWS Console.

–Deepak Dayama

Amazon EC2 Bare Metal Instances with Direct Access to Hardware

Post Syndicated from Jeff Barr original https://aws.amazon.com/blogs/aws/new-amazon-ec2-bare-metal-instances-with-direct-access-to-hardware/

When customers come to us with new and unique requirements for AWS, we listen closely, ask lots of questions, and do our best to understand and address their needs. When we do this, we make the resulting service or feature generally available; we do not build one-offs or “snowflakes” for individual customers. That model is messy and hard to scale and is not the way we work.

Instead, every AWS customer has access to whatever it is that we build, and everyone benefits. VMware Cloud on AWS is a good example of this strategy in action. They told us that they wanted to run their virtualization stack directly on the hardware, within the AWS Cloud, giving their customers access to the elasticity, security, and reliability (not to mention the broad array of services) that AWS offers.

We knew that other customers also had interesting use cases for bare metal hardware and didn’t want to take the performance hit of nested virtualization. They wanted access to the physical resources for applications that take advantage of low-level hardware features such as performance counters and Intel® VT that are not always available or fully supported in virtualized environments, and also for applications intended to run directly on the hardware or licensed and supported for use in non-virtualized environments.

Our multi-year effort to move networking, storage, and other EC2 features out of our virtualization platform and into dedicated hardware was already well underway and provided the perfect foundation for a possible solution. This work, as I described in Now Available – Compute-Intensive C5 Instances for Amazon EC2, includes a set of dedicated hardware accelerators.

Now that we have provided VMware with the bare metal access that they requested, we are doing the same for all AWS customers. I’m really looking forward to seeing what you can do with them!

New Bare Metal Instances
Today we are launching a public preview the i3.metal instance, the first in a series of EC2 instances that offer the best of both worlds, allowing the operating system to run directly on the underlying hardware while still providing access to all of the benefits of the cloud. The instance gives you direct access to the processor and other hardware, and has the following specifications:

  • Processing – Two Intel Xeon E5-2686 v4 processors running at 2.3 GHz, with a total of 36 hyperthreaded cores (72 logical processors).
  • Memory – 512 GiB.
  • Storage – 15.2 terabytes of local, SSD-based NVMe storage.
  • Network – 25 Gbps of ENA-based enhanced networking.

Bare Metal instances are full-fledged members of the EC2 family and can take advantage of Elastic Load Balancing, Auto Scaling, Amazon CloudWatch, Auto Recovery, and so forth. They can also access the full suite of AWS database, IoT, mobile, analytics, artificial intelligence, and security services.

Previewing Now
We are launching a public preview of the Bare Metal instances today; please sign up now if you want to try them out.

You can now bring your specialized applications or your own stack of virtualized components to AWS and run them on Bare Metal instances. If you are using or thinking about using containers, these instances make a great host for CoreOS.

An AMI that works on one of the new C5 instances should also work on an I3 Bare Metal Instance. It must have the ENA and NVMe drivers, and must be tagged for ENA.

Jeff;

 

Now You Can Use AWS Shield Advanced to Help Protect Your Amazon EC2 Instances and Network Load Balancers

Post Syndicated from Ritwik Manan original https://aws.amazon.com/blogs/security/now-you-can-use-aws-shield-advanced-to-protect-your-amazon-ec2-instances-and-network-load-balancers/

AWS Shield image

Starting today, AWS Shield Advanced can help protect your Amazon EC2 instances and Network Load Balancers against infrastructure-layer Distributed Denial of Service (DDoS) attacks. Enable AWS Shield Advanced on an AWS Elastic IP address and attach the address to an internet-facing EC2 instance or Network Load Balancer. AWS Shield Advanced automatically detects the type of AWS resource behind the Elastic IP address and mitigates DDoS attacks.

AWS Shield Advanced also ensures that all your Amazon VPC network access control lists (ACLs) are automatically executed on AWS Shield at the edge of the AWS network, giving you access to additional bandwidth and scrubbing capacity as well as mitigating large volumetric DDoS attacks. You also can customize additional mitigations on AWS Shield by engaging the AWS DDoS Response Team, which can preconfigure the mitigations or respond to incidents as they happen. For every incident detected by AWS Shield Advanced, you also get near-real-time visibility via Amazon CloudWatch metrics and details about the incident, such as the geographic origin and source IP address of the attack.

AWS Shield Advanced for Elastic IP addresses extends the coverage of DDoS cost protection, which safeguards against scaling charges as a result of a DDoS attack. DDoS cost protection now allows you to request service credits for Elastic Load Balancing, Amazon CloudFront, Amazon Route 53, and your EC2 instance hours in the event that these increase as the result of a DDoS attack.

Get started protecting EC2 instances and Network Load Balancers

To get started:

  1. Sign in to the AWS Management Console and navigate to the AWS WAF and AWS Shield console.
  2. Activate AWS Shield Advanced by choosing Activate AWS Shield Advanced and accepting the terms.
  3. Navigate to Protected Resources through the navigation pane.
  4. Choose the Elastic IP addresses that you want to protect (these can point to EC2 instances or Network Load Balancers).

If AWS Shield Advanced detects a DDoS attack, you can get details about the attack by checking CloudWatch, or the Incidents tab on the AWS WAF and AWS Shield console. To learn more about this new feature and AWS Shield Advanced, see the AWS Shield home page.

If you have comments or questions about this post, submit them in the “Comments” section below, start a new thread in the AWS Shield forum, or contact AWS Support.

– Ritwik

Access Resources in a VPC from AWS CodeBuild Builds

Post Syndicated from John Pignata original https://aws.amazon.com/blogs/devops/access-resources-in-a-vpc-from-aws-codebuild-builds/

John Pignata, Startup Solutions Architect, Amazon Web Services

In this blog post we’re going to discuss a new AWS CodeBuild feature that is available starting today. CodeBuild builds can now access resources in a VPC directly without these resources being exposed to the public internet. These resources include Amazon Relational Database Service (Amazon RDS) databases, Amazon ElastiCache clusters, internal services running on Amazon Elastic Compute Cloud (Amazon EC2), and Amazon EC2 Container Service (Amazon ECS), or any service endpoints that are only reachable from within a specific VPC.

CodeBuild is a fully managed build service that compiles source code, runs tests, and produces software packages that are ready to deploy. As part of the build process, developers often require access to resources that should be isolated from the public Internet. Now CodeBuild builds can be optionally configured to have VPC connectivity and access these resources directly.

Accessing Resources in a VPC

You can configure builds to have access to a VPC when you create a CodeBuild project or you can update an existing CodeBuild project with VPC configuration attributes. Here’s how it looks in the console:

 

To configure VPC connectivity: select a VPC, one or more subnets within that VPC, and one or more VPC security groups that CodeBuild should apply when attaching to your VPC. Once configured, commands running as part of your build will be able to access resources in your VPC without transiting across the public Internet.

Use Cases

The availability of VPC connectivity from CodeBuild builds unlocks many potential uses. For example, you can:

  • Run integration tests from your build against data in an Amazon RDS instance that’s isolated on a private subnet.
  • Query data in an ElastiCache cluster directly from tests.
  • Interact with internal web services hosted on Amazon EC2, Amazon ECS, or services that use internal Elastic Load Balancing.
  • Retrieve dependencies from self-hosted, internal artifact repositories such as PyPI for Python, Maven for Java, npm for Node.js, and so on.
  • Access objects in an Amazon S3 bucket configured to allow access only through a VPC endpoint.
  • Query external web services that require fixed IP addresses through the Elastic IP address of the NAT gateway associated with your subnet(s).

… and more! Your builds can now access any resource that’s hosted in your VPC without any compromise on network isolation.

Internet Connectivity

CodeBuild requires access to resources on the public Internet to successfully execute builds. At a minimum, it must be able to reach your source repository system (such as AWS CodeCommit, GitHub, Bitbucket), Amazon Simple Storage Service (Amazon S3) to deliver build artifacts, and Amazon CloudWatch Logs to stream logs from the build process. The interface attached to your VPC will not be assigned a public IP address so to enable Internet access from your builds, you will need to set up a managed NAT Gateway or NAT instance for the subnets you configure. You must also ensure your security groups allow outbound access to these services.

IP Address Space

Each running build will be assigned an IP address from one of the subnets in your VPC that you designate for CodeBuild to use. As CodeBuild scales to meet your build volume, ensure that you select subnets with enough address space to accommodate your expected number of concurrent builds.

Service Role Permissions

CodeBuild requires new permissions in order to manage network interfaces on your VPCs. If you create a service role for your new projects, these permissions will be included in that role’s policy automatically. For existing service roles, you can edit the policy document to include the additional actions. For the full policy document to apply to your service role, see Advanced Setup in the CodeBuild documentation.

For more information, see VPC Support in the CodeBuild documentation. We hope you find the ability to access internal resources on a VPC useful in your build processes! If you have any questions or feedback, feel free to reach out to us through the AWS CodeBuild forum or leave a comment!

AWS Achieves FedRAMP JAB Moderate Provisional Authorization for 20 Services in the AWS US East/West Region

Post Syndicated from Chris Gile original https://aws.amazon.com/blogs/security/aws-achieves-fedramp-jab-moderate-authorization-for-20-services-in-us-eastwest/

The AWS US East/West Region has received a Provisional Authority to Operate (P-ATO) from the Joint Authorization Board (JAB) at the Federal Risk and Authorization Management Program (FedRAMP) Moderate baseline.

Though AWS has maintained an AWS US East/West Region Agency-ATO since early 2013, this announcement represents AWS’s carefully deliberated move to the JAB for the centralized maintenance of our P-ATO for 10 services already authorized. This also includes the addition of 10 new services to our FedRAMP program (see the complete list of services below). This doubles the number of FedRAMP Moderate services available to our customers to enable increased use of the cloud and support modernized IT missions. Our public sector customers now can leverage this FedRAMP P-ATO as a baseline for their own authorizations and look to the JAB for centralized Continuous Monitoring reporting and updates. In a significant enhancement for our partners that build their solutions on the AWS US East/West Region, they can now achieve FedRAMP JAB P-ATOs of their own for their Platform as a Service (PaaS) and Software as a Service (SaaS) offerings.

In line with FedRAMP security requirements, our independent FedRAMP assessment was completed in partnership with a FedRAMP accredited Third Party Assessment Organization (3PAO) on our technical, management, and operational security controls to validate that they meet or exceed FedRAMP’s Moderate baseline requirements. Effective immediately, you can begin leveraging this P-ATO for the following 20 services in the AWS US East/West Region:

  • Amazon Aurora (MySQL)*
  • Amazon CloudWatch Logs*
  • Amazon DynamoDB
  • Amazon Elastic Block Store
  • Amazon Elastic Compute Cloud
  • Amazon EMR*
  • Amazon Glacier*
  • Amazon Kinesis Streams*
  • Amazon RDS (MySQL, Oracle, Postgres*)
  • Amazon Redshift
  • Amazon Simple Notification Service*
  • Amazon Simple Queue Service*
  • Amazon Simple Storage Service
  • Amazon Simple Workflow Service*
  • Amazon Virtual Private Cloud
  • AWS CloudFormation*
  • AWS CloudTrail*
  • AWS Identity and Access Management
  • AWS Key Management Service
  • Elastic Load Balancing

* Services with first-time FedRAMP Moderate authorizations

We continue to work with the FedRAMP Project Management Office (PMO), other regulatory and compliance bodies, and our customers and partners to ensure that we are raising the bar on our customers’ security and compliance needs.

To learn more about how AWS helps customers meet their security and compliance requirements, see the AWS Compliance website. To learn about what other public sector customers are doing on AWS, see our Government, Education, and Nonprofits Case Studies and Customer Success Stories. To review the public posting of our FedRAMP authorizations, see the FedRAMP Marketplace.

– Chris Gile, Senior Manager, AWS Public Sector Risk and Compliance