We are excited to announce that Amazon OpenSearch Serverless is expanding availability to the Amazon OpenSearch Serverless to AWS Europe (Milan) Region. OpenSearch Serverless is a serverless deployment option for Amazon OpenSearch Service that makes it simple to run search and analytics workloads without the complexities of infrastructure management. OpenSearch Serverless’ compute capacity used for data ingestion, search, and query is measured in OpenSearch Compute Units (OCUs). To control costs, customers can configure maximum number of OCUs per account.

Please refer to the AWS Regional Services List for more information about Amazon OpenSearch Service availability. To learn more about OpenSearch Serverless, see the documentation.

 

​We are excited to announce that Amazon OpenSearch Serverless is expanding availability to the Amazon OpenSearch Serverless to AWS Europe (Milan) Region. OpenSearch Serverless is a serverless deployment option for Amazon OpenSearch Service that makes it simple to run search and analytics workloads without the complexities of infrastructure management. OpenSearch Serverless’ compute capacity used for data ingestion, search, and query is measured in OpenSearch Compute Units (OCUs). To control costs, customers can configure maximum number of OCUs per account. Please refer to the AWS Regional Services List for more information about Amazon OpenSearch Service availability. To learn more about OpenSearch Serverless, see the documentation.  

We are excited to announce that Amazon OpenSearch Serverless is expanding availability to AWS US West (SFO, N. California) and Europe (ARN, Stockholm) Regions. OpenSearch Serverless is a serverless deployment option for Amazon OpenSearch Service that makes it simple to run search and analytics workloads without the complexities of infrastructure management. OpenSearch Serverless’ compute capacity used for data ingestion, search, and query is measured in OpenSearch Compute Units (OCUs). To control costs, customers can configure maximum number of OCUs per account.

Please refer to the AWS Regional Services List for more information about Amazon OpenSearch Service availability. To learn more about OpenSearch Serverless, see the documentation.

 

​We are excited to announce that Amazon OpenSearch Serverless is expanding availability to AWS US West (SFO, N. California) and Europe (ARN, Stockholm) Regions. OpenSearch Serverless is a serverless deployment option for Amazon OpenSearch Service that makes it simple to run search and analytics workloads without the complexities of infrastructure management. OpenSearch Serverless’ compute capacity used for data ingestion, search, and query is measured in OpenSearch Compute Units (OCUs). To control costs, customers can configure maximum number of OCUs per account. Please refer to the AWS Regional Services List for more information about Amazon OpenSearch Service availability. To learn more about OpenSearch Serverless, see the documentation.  

Today, Amazon Q Developer announced an enhanced CLI agent within the Amazon Q command line interface (CLI) that allows you to have more dynamic conversations. With this update, Amazon Q Developer can now use the information in your CLI environment to help you read and write files locally, query AWS resources or create code.

You can now ask Q Developer to write code, test it, help debug issues, and Q Developer will iteratively make adjustments based on your feedback and approval. This allows you to efficiently complete tasks, improving and streamlining the development process, without needing to leave your terminal.

The enhanced CLI agent, powered by Anthropic’s most intelligent model to date, Claude 3.7 Sonnet, is available on Amazon Q Developer Free, and Pro tiers and in all AWS regions where Q Developer is available. Learn more.

 

​Today, Amazon Q Developer announced an enhanced CLI agent within the Amazon Q command line interface (CLI) that allows you to have more dynamic conversations. With this update, Amazon Q Developer can now use the information in your CLI environment to help you read and write files locally, query AWS resources or create code. You can now ask Q Developer to write code, test it, help debug issues, and Q Developer will iteratively make adjustments based on your feedback and approval. This allows you to efficiently complete tasks, improving and streamlining the development process, without needing to leave your terminal. The enhanced CLI agent, powered by Anthropic’s most intelligent model to date, Claude 3.7 Sonnet, is available on Amazon Q Developer Free, and Pro tiers and in all AWS regions where Q Developer is available. Learn more.  

Starting today, the general-purpose Amazon EC2 M7a instances are now available in AWS Asia Pacific (Sydney) Region. M7a instances, powered by 4th Gen AMD EPYC processors (code-named Genoa) with a maximum frequency of 3.7 GHz, deliver up to 50% higher performance compared to M6a instances.

With this additional region, M7a instances are available in the following AWS Regions: US East (Ohio), US East (N. Virginia), US West (Oregon), Asia Pacific (Sydney, Tokyo), and Europe (Frankfurt, Ireland, Spain, Stockholm). These instances can be purchased as Savings Plans, Reserved, On-Demand, and Spot instances. To get started, visit the AWS Management Console, AWS Command Line Interface (CLI), and AWS SDKs. To learn more, visit the M7a instances page.

 

​Starting today, the general-purpose Amazon EC2 M7a instances are now available in AWS Asia Pacific (Sydney) Region. M7a instances, powered by 4th Gen AMD EPYC processors (code-named Genoa) with a maximum frequency of 3.7 GHz, deliver up to 50% higher performance compared to M6a instances. With this additional region, M7a instances are available in the following AWS Regions: US East (Ohio), US East (N. Virginia), US West (Oregon), Asia Pacific (Sydney, Tokyo), and Europe (Frankfurt, Ireland, Spain, Stockholm). These instances can be purchased as Savings Plans, Reserved, On-Demand, and Spot instances. To get started, visit the AWS Management Console, AWS Command Line Interface (CLI), and AWS SDKs. To learn more, visit the M7a instances page.  

AWS CodeConnections now allows you to securely share your Connection resource across individual AWS accounts or within your AWS Organization. Previously, to create a Connection, you installed the AWS connector App for GitHub or GitLab or Bitbucket for each AWS account from which source access was required.

You can now use AWS Resource Access Manager (RAM) to securely share a Connection to your third-party source provider across AWS accounts. By using AWS RAM to share your Connection resource, you no longer need to create a Connection in each AWS account. Instead, you can create a Connection in an AWS account, and then share the Connection across multiple AWS accounts. By using AWS RAM, you can also automate sharing the connection across AWS accounts, reducing the operational overhead to support a multi-account deployment strategy. To apply fine grained access control, in the AWS account with which a Connection is shared, you can use IAM policies to manage what operations an IAM role can perform.

To learn more about sharing connections, visit our documentation. To learn more about what Connections in AWS CodeConnections are and how they work, visit our documentation.

 

​AWS CodeConnections now allows you to securely share your Connection resource across individual AWS accounts or within your AWS Organization. Previously, to create a Connection, you installed the AWS connector App for GitHub or GitLab or Bitbucket for each AWS account from which source access was required. You can now use AWS Resource Access Manager (RAM) to securely share a Connection to your third-party source provider across AWS accounts. By using AWS RAM to share your Connection resource, you no longer need to create a Connection in each AWS account. Instead, you can create a Connection in an AWS account, and then share the Connection across multiple AWS accounts. By using AWS RAM, you can also automate sharing the connection across AWS accounts, reducing the operational overhead to support a multi-account deployment strategy. To apply fine grained access control, in the AWS account with which a Connection is shared, you can use IAM policies to manage what operations an IAM role can perform. To learn more about sharing connections, visit our documentation. To learn more about what Connections in AWS CodeConnections are and how they work, visit our documentation.  

Amazon GameLift Streams is a new managed capability that allows developers to stream games at up to 1080p resolution and 60 frames per second to any device with a WebRTC-enabled browser. In just a few clicks, you can upload games built with a variety of 3D engines with little to no modification, provision streaming capacity in specific AWS Regions, and immediately start test streaming. Players can start playing AAA, AA, and Indie games over the internet in just a few seconds on their PCs, phones, tablets, and smart TVs without waiting hours for a download.

With Amazon GameLift Streams, you can create new direct-to-player distribution channels, launch instant-play game demos, conduct secure playtesting, and expand monetization opportunities. With support for Windows, Linux, and Proton runtimes, Amazon GameLift Streams helps you avoid the expense and complexity of modifying and rebuilding game code for streaming. You can flexibly scale streaming up or down based on player demand, and only provision and pay for the capacity you need. You can choose from six AWS Regions to deliver low-latency game play closer to players around the world. This new capability opens opportunities for you to expand the reach, engagement, and sales of your games while maintaining full control over the player relationship, experience, branding, and business model.

Amazon GameLift Streams is a new capability of Amazon GameLift, a fully managed service on AWS empowering developers to build and deliver the world’s most demanding games. The new capability is available in the following AWS Regions: US East (N. Virginia), US East (Ohio), US West (Oregon), Asia Pacific (Tokyo), Europe (Frankfurt), and Europe (Ireland).

To learn more, visit the Amazon GameLift Streams website, read the Developer Guide, or explore the AWS News Blog post. 

 

​Amazon GameLift Streams is a new managed capability that allows developers to stream games at up to 1080p resolution and 60 frames per second to any device with a WebRTC-enabled browser. In just a few clicks, you can upload games built with a variety of 3D engines with little to no modification, provision streaming capacity in specific AWS Regions, and immediately start test streaming. Players can start playing AAA, AA, and Indie games over the internet in just a few seconds on their PCs, phones, tablets, and smart TVs without waiting hours for a download.
With Amazon GameLift Streams, you can create new direct-to-player distribution channels, launch instant-play game demos, conduct secure playtesting, and expand monetization opportunities. With support for Windows, Linux, and Proton runtimes, Amazon GameLift Streams helps you avoid the expense and complexity of modifying and rebuilding game code for streaming. You can flexibly scale streaming up or down based on player demand, and only provision and pay for the capacity you need. You can choose from six AWS Regions to deliver low-latency game play closer to players around the world. This new capability opens opportunities for you to expand the reach, engagement, and sales of your games while maintaining full control over the player relationship, experience, branding, and business model.
Amazon GameLift Streams is a new capability of Amazon GameLift, a fully managed service on AWS empowering developers to build and deliver the world’s most demanding games. The new capability is available in the following AWS Regions: US East (N. Virginia), US East (Ohio), US West (Oregon), Asia Pacific (Tokyo), Europe (Frankfurt), and Europe (Ireland).
To learn more, visit the Amazon GameLift Streams website, read the Developer Guide, or explore the AWS News Blog post.   

Amazon Connect, Amazon WorkSpaces, and Amazon AppStream 2.0 have earned Chrome Enterprise Recommended (CER) certification. This designation validates that these services are fully optimized for ChromeOS, ChromeOS Flex, and Chrome browser environments, ensuring seamless integration and performance for businesses using Chrome devices.

These Chrome-optimized services deliver significant advantages for organizations with users gaining browser-based access to contact center capabilities through Amazon Connect, Windows or Linux virtual desktops through Amazon WorkSpaces, and streaming applications without refactoring with Amazon AppStream 2.0. Customers can take advantage of security features built into ChromeOS, while enabling cost savings through efficient scaling and elimination of traditional infrastructure. Organizations can get more out of their hardware investments by installing ChromeOS Flex on aging devices, repurposing them to run Windows 11 on Amazon WorkSpaces and bringing existing Microsoft 365 Apps for enterprise licenses to run on WorkSpaces.

Amazon Connect, Amazon WorkSpaces, and Amazon AppStream 2.0 are available in multiple AWS Regions worldwide, allowing organizations to deploy these services closer to their end-users for optimal performance and compliance with data residency requirements.

To learn more about leveraging these Chrome Enterprise Recommended services, visit Amazon Connect, Amazon WorkSpaces, or Amazon AppStream 2.0 . Contact your AWS account team to discuss your specific requirements and discover how these CER-certified solutions can transform your ChromeOS deployment.

 

​Amazon Connect, Amazon WorkSpaces, and Amazon AppStream 2.0 have earned Chrome Enterprise Recommended (CER) certification. This designation validates that these services are fully optimized for ChromeOS, ChromeOS Flex, and Chrome browser environments, ensuring seamless integration and performance for businesses using Chrome devices. These Chrome-optimized services deliver significant advantages for organizations with users gaining browser-based access to contact center capabilities through Amazon Connect, Windows or Linux virtual desktops through Amazon WorkSpaces, and streaming applications without refactoring with Amazon AppStream 2.0. Customers can take advantage of security features built into ChromeOS, while enabling cost savings through efficient scaling and elimination of traditional infrastructure. Organizations can get more out of their hardware investments by installing ChromeOS Flex on aging devices, repurposing them to run Windows 11 on Amazon WorkSpaces and bringing existing Microsoft 365 Apps for enterprise licenses to run on WorkSpaces. Amazon Connect, Amazon WorkSpaces, and Amazon AppStream 2.0 are available in multiple AWS Regions worldwide, allowing organizations to deploy these services closer to their end-users for optimal performance and compliance with data residency requirements. To learn more about leveraging these Chrome Enterprise Recommended services, visit Amazon Connect, Amazon WorkSpaces, or Amazon AppStream 2.0 . Contact your AWS account team to discuss your specific requirements and discover how these CER-certified solutions can transform your ChromeOS deployment.  

Today, AWS announced that Bottlerocket, the Linux-based operating system purpose-built for containers, now supports AWS Neuron-powered instances with its Amazon Elastic Kubernetes Service (EKS) and Amazon Elastic Container Service (ECS) AMIs. Customers using Bottlerocket AMIs can now deploy and manage machine learning inference and training workloads on AWS Neuron accelerated instance types, including Inf1, Inf2, Trn1, and Trn2. EKS customers can use these Bottlerocket AMIs with Karpenter version 1.2.2 and above.

This integration enables automated device management and scheduling capabilities while maintaining Bottlerocket’s focus on security and operational simplicity. Customers can leverage the standard Bottlerocket AMIs to deploy workloads on Neuron instances, with the ability to configure device ownership and resource allocation through familiar container orchestration interfaces.

Bottlerocket support for AWS Neuron-powered instances is available in all AWS Regions where Inf1, Inf2, Trn1, and Trn2 instances are offered. To get started, see the Bottlerocket User Guide. You can also visit the Bottlerocket product page and explore the Bottlerocket GitHub repository for more information.

 

​Today, AWS announced that Bottlerocket, the Linux-based operating system purpose-built for containers, now supports AWS Neuron-powered instances with its Amazon Elastic Kubernetes Service (EKS) and Amazon Elastic Container Service (ECS) AMIs. Customers using Bottlerocket AMIs can now deploy and manage machine learning inference and training workloads on AWS Neuron accelerated instance types, including Inf1, Inf2, Trn1, and Trn2. EKS customers can use these Bottlerocket AMIs with Karpenter version 1.2.2 and above. This integration enables automated device management and scheduling capabilities while maintaining Bottlerocket’s focus on security and operational simplicity. Customers can leverage the standard Bottlerocket AMIs to deploy workloads on Neuron instances, with the ability to configure device ownership and resource allocation through familiar container orchestration interfaces. Bottlerocket support for AWS Neuron-powered instances is available in all AWS Regions where Inf1, Inf2, Trn1, and Trn2 instances are offered. To get started, see the Bottlerocket User Guide. You can also visit the Bottlerocket product page and explore the Bottlerocket GitHub repository for more information.  

Today, AWS has announced that Bottlerocket, the Linux-based operating system purpose-built for containers, now provides a default bootstrap container image that simplifies system setup tasks, eliminating the need for most customers to maintain their own container images for initial configuration. Bootstrap containers are special-purpose containers that handle pre-startup operations such as directory creation, environment variable setup, and node-specific configurations before the main application containers start.

This enhancement allows customers to focus on their startup scripts rather than container image maintenance and regional availability. Previously, customers needed to create, maintain, and update their own container images while managing separate image repositories for each AWS Region. By using Bottlerocket’s default bootstrap container image, customers can specify their configuration tasks through simple user data, while the system automatically handles image updates. The default image is maintained by AWS, reducing operational overhead and improving system security.

The simplified bootstrap container configuration in Bottlerocket is available in all commercial and AWS GovCloud (US) Regions. To learn more, see the Bottlerocket User Guide. You can also visit the Bottlerocket product page and explore the Bottlerocket GitHub repository for more information.
 

 

​Today, AWS has announced that Bottlerocket, the Linux-based operating system purpose-built for containers, now provides a default bootstrap container image that simplifies system setup tasks, eliminating the need for most customers to maintain their own container images for initial configuration. Bootstrap containers are special-purpose containers that handle pre-startup operations such as directory creation, environment variable setup, and node-specific configurations before the main application containers start. This enhancement allows customers to focus on their startup scripts rather than container image maintenance and regional availability. Previously, customers needed to create, maintain, and update their own container images while managing separate image repositories for each AWS Region. By using Bottlerocket’s default bootstrap container image, customers can specify their configuration tasks through simple user data, while the system automatically handles image updates. The default image is maintained by AWS, reducing operational overhead and improving system security. The simplified bootstrap container configuration in Bottlerocket is available in all commercial and AWS GovCloud (US) Regions. To learn more, see the Bottlerocket User Guide. You can also visit the Bottlerocket product page and explore the Bottlerocket GitHub repository for more information.    

Today, AWS has announced that Bottlerocket, the Linux-based operating system purpose-built for containers, now supports NVIDIA’s Multi-Instance GPU (MIG) feature, enabling customers to partition NVIDIA GPUs into multiple GPU instances on Kubernetes nodes. This capability allows system administrators to maximize GPU resource utilization by running multiple workloads simultaneously on a single GPU while maintaining hardware-level isolation between workloads.

With MIG support, customers can optimize GPU resource allocation for workloads that don’t fully utilize the GPU’s compute capacity, such as machine learning inference tasks. Each GPU partition operates with complete hardware-level memory and fault isolation, providing workload separation and reliable performance.

NVIDIA Multi-Instance GPU support in Bottlerocket is available in all commercial and AWS GovCloud (US) Regions where compatible NVIDIA GPU-enabled instances are offered. To learn more about MIG with the Bottlerocket NVIDIA variants, see the Bottlerocket User Guide. You can also visit the Bottlerocket product page and explore the Bottlerocket GitHub repository for more information.

 

​Today, AWS has announced that Bottlerocket, the Linux-based operating system purpose-built for containers, now supports NVIDIA’s Multi-Instance GPU (MIG) feature, enabling customers to partition NVIDIA GPUs into multiple GPU instances on Kubernetes nodes. This capability allows system administrators to maximize GPU resource utilization by running multiple workloads simultaneously on a single GPU while maintaining hardware-level isolation between workloads. With MIG support, customers can optimize GPU resource allocation for workloads that don’t fully utilize the GPU’s compute capacity, such as machine learning inference tasks. Each GPU partition operates with complete hardware-level memory and fault isolation, providing workload separation and reliable performance. NVIDIA Multi-Instance GPU support in Bottlerocket is available in all commercial and AWS GovCloud (US) Regions where compatible NVIDIA GPU-enabled instances are offered. To learn more about MIG with the Bottlerocket NVIDIA variants, see the Bottlerocket User Guide. You can also visit the Bottlerocket product page and explore the Bottlerocket GitHub repository for more information.