AWS GovCloud (US) now offers Claude Sonnet 5 on Amazon Bedrock. Claude Sonnet 5 delivers strong performance across coding, professional work, and agentic tasks while maintaining the balance of capability, cost, and speed. For coding, it navigates large codebases, lands multi-file changes, and carries debugging and refactoring tasks through to completion with fewer rounds of correction. For agents, it calls tools precisely, holds state across many steps, and recovers from errors so more runs finish correctly the first time. For knowledge work, it builds spreadsheets, drafts documents, and turns unstructured material into structured analysis. 

With this launch, Claude Opus 4.8 and Claude Sonnet 5 are available on bedrock-runtime endpoints in AWS GovCloud (US-West and US-East) and bedrock-mantle endpoints in AWS GovCloud (US-West) for performing inference. Bedrock Mantle, Amazon Bedorck’s next-generation inference engine, supports the Anthropic Messages API. Amazon Bedrock keeps your data within AWS infrastructure and provides access to Claude Sonnet 5 through a unified service with AWS-managed features like Guardrails, Knowledge Bases, and regional data residency. To learn more, see the Amazon Bedrock documentation and regional availability. 

 

​AWS GovCloud (US) now offers Claude Sonnet 5 on Amazon Bedrock. Claude Sonnet 5 delivers strong performance across coding, professional work, and agentic tasks while maintaining the balance of capability, cost, and speed. For coding, it navigates large codebases, lands multi-file changes, and carries debugging and refactoring tasks through to completion with fewer rounds of correction. For agents, it calls tools precisely, holds state across many steps, and recovers from errors so more runs finish correctly the first time. For knowledge work, it builds spreadsheets, drafts documents, and turns unstructured material into structured analysis. 
With this launch, Claude Opus 4.8 and Claude Sonnet 5 are available on bedrock-runtime endpoints in AWS GovCloud (US-West and US-East) and bedrock-mantle endpoints in AWS GovCloud (US-West) for performing inference. Bedrock Mantle, Amazon Bedorck’s next-generation inference engine, supports the Anthropic Messages API. Amazon Bedrock keeps your data within AWS infrastructure and provides access to Claude Sonnet 5 through a unified service with AWS-managed features like Guardrails, Knowledge Bases, and regional data residency. To learn more, see the Amazon Bedrock documentation and regional availability.   

We are pleased to announce the availability of Amazon EC2 G7e instances in Asia Pacific (Seoul), Europe (London), and Asia Pacific (Tokyo) on Amazon SageMaker AI inference. G7e instances feature up to 8 NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs with 96 GB of memory per GPU, 5th Generation Intel Xeon processors, and up to 1,600 Gbps of Elastic Fabric Adapter networking bandwidth, delivering up to 2.3x inference performance compared to previous-generation G6e instances.

With this region expansion, you can now deploy inference endpoints on G7e instances closer to your end users in Asia and Europe, reducing latency for generative AI workloads. G7e instances provide up to 768 GB of total GPU memory on a single instance, enabling you to serve medium-to-large language models of up to 70B parameters with FP8 precision without multi-node configurations. These instances are well suited for LLM inference, image and video generation, spatial computing, and scientific computing workloads that require high GPU memory capacity and bandwidth.

G7e instances for SageMaker AI inference are now available in Asia Pacific (Seoul), Europe (London), and Asia Pacific (Tokyo), in addition to previously supported regions. For pricing information on these instances, please visit our pricing page.

 

​We are pleased to announce the availability of Amazon EC2 G7e instances in Asia Pacific (Seoul), Europe (London), and Asia Pacific (Tokyo) on Amazon SageMaker AI inference. G7e instances feature up to 8 NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs with 96 GB of memory per GPU, 5th Generation Intel Xeon processors, and up to 1,600 Gbps of Elastic Fabric Adapter networking bandwidth, delivering up to 2.3x inference performance compared to previous-generation G6e instances. With this region expansion, you can now deploy inference endpoints on G7e instances closer to your end users in Asia and Europe, reducing latency for generative AI workloads. G7e instances provide up to 768 GB of total GPU memory on a single instance, enabling you to serve medium-to-large language models of up to 70B parameters with FP8 precision without multi-node configurations. These instances are well suited for LLM inference, image and video generation, spatial computing, and scientific computing workloads that require high GPU memory capacity and bandwidth. G7e instances for SageMaker AI inference are now available in Asia Pacific (Seoul), Europe (London), and Asia Pacific (Tokyo), in addition to previously supported regions. For pricing information on these instances, please visit our pricing page.  

We are pleased to announce the availability of Amazon EC2 G6 instances in the AWS GovCloud (US-East) region on Amazon SageMaker AI inference. G6 instances are powered by up to 8 NVIDIA L4 Tensor Core GPUs, each with 24 GB of memory, and third-generation AMD EPYC processors, delivering up to 2x the deep learning inference performance compared to G4dn instances.

With this region expansion, government agencies and organizations operating in GovCloud can deploy inference endpoints on G6 instances to serve generative AI workloads—including small-to-medium language models, image generation, and computer vision tasks—while meeting strict compliance and data residency requirements. G6 instances offer strong price-performance for production inference workloads that fit within 24 GB of GPU memory.

G6 instances for SageMaker AI inference are now available in AWS GovCloud (US-East), in addition to previously supported regions. For pricing information on these instances, please visit our pricing page.

 

​We are pleased to announce the availability of Amazon EC2 G6 instances in the AWS GovCloud (US-East) region on Amazon SageMaker AI inference. G6 instances are powered by up to 8 NVIDIA L4 Tensor Core GPUs, each with 24 GB of memory, and third-generation AMD EPYC processors, delivering up to 2x the deep learning inference performance compared to G4dn instances. With this region expansion, government agencies and organizations operating in GovCloud can deploy inference endpoints on G6 instances to serve generative AI workloads—including small-to-medium language models, image generation, and computer vision tasks—while meeting strict compliance and data residency requirements. G6 instances offer strong price-performance for production inference workloads that fit within 24 GB of GPU memory. G6 instances for SageMaker AI inference are now available in AWS GovCloud (US-East), in addition to previously supported regions. For pricing information on these instances, please visit our pricing page.  

Starting today, the compute optimized Amazon EC2 C7a instances are now available in AWS US West (N. California) Region. C7a 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 C6a instances.

C7a instances offer new processor capabilities such as AVX-512, VNNI, and bfloat16. They feature Double Data Rate 5 (DDR5) memory to enable high-speed access to data in memory and 2.25x more memory bandwidth compared to C6a instances, making these instances ideal for even latency sensitive workloads. C7a instances offer 12 sizes from medium to 48xlarge, including a bare-metal size. And with the launch of C7a instances, customers can attach up to 128 EBS volumes to an EC2 instance — by comparison, C6a instances allow up to 28 EBS volume attachments to an EC2 instance. These instances are built on the AWS Nitro System and ideal for high performance, compute-intensive workloads such as batch processing, distributed analytics, high performance computing (HPC), ad serving, highly-scalable multiplayer gaming, and video encoding.

C7a instances are available through On-Demand, Spot Instances, and Savings Plans. To get started, visit the AWS Management Console, AWS Command Line Interface (CLI), and AWS SDKs. To learn more, see C7a instances.

 

​Starting today, the compute optimized Amazon EC2 C7a instances are now available in AWS US West (N. California) Region. C7a 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 C6a instances. C7a instances offer new processor capabilities such as AVX-512, VNNI, and bfloat16. They feature Double Data Rate 5 (DDR5) memory to enable high-speed access to data in memory and 2.25x more memory bandwidth compared to C6a instances, making these instances ideal for even latency sensitive workloads. C7a instances offer 12 sizes from medium to 48xlarge, including a bare-metal size. And with the launch of C7a instances, customers can attach up to 128 EBS volumes to an EC2 instance — by comparison, C6a instances allow up to 28 EBS volume attachments to an EC2 instance. These instances are built on the AWS Nitro System and ideal for high performance, compute-intensive workloads such as batch processing, distributed analytics, high performance computing (HPC), ad serving, highly-scalable multiplayer gaming, and video encoding. C7a instances are available through On-Demand, Spot Instances, and Savings Plans. To get started, visit the AWS Management Console, AWS Command Line Interface (CLI), and AWS SDKs. To learn more, see C7a instances.  

Starting today, the general-purpose Amazon EC2 M8a instances are available in AWS Asia Pacific (Hyderabad) region. M8a instances are powered by 5th Gen AMD EPYC processors (formerly code named Turin) with a maximum frequency of 4.5 GHz, deliver up to 30% higher performance, and up to 19% better price-performance compared to M7a instances.

M8a instances deliver 45% more memory bandwidth compared to M7a instances, making these instances ideal for even latency sensitive workloads. M8a instances deliver even higher performance gains for specific workloads. M8a instances are up to 60% faster for GroovyJVM benchmark, and up to 39% faster for Cassandra benchmark compared to Amazon EC2 M7a instances. M8a instances are SAP-certified and offer 12 sizes including 2 bare metal sizes. This range of instance sizes allows customers to precisely match their workload requirements.

M8a instances are built using the latest sixth generation AWS Nitro Cards and ideal for applications that benefit from high performance and high throughput such as financial applications, gaming, rendering, application servers, simulation modeling, mid-size data stores, application development environments, and caching fleets.

To get started, sign in to the AWS Management Console. Customers can purchase these instances via Savings Plans, On-Demand instances, and Spot instances. For more information visit the Amazon EC2 M8a instance page.

 

​Starting today, the general-purpose Amazon EC2 M8a instances are available in AWS Asia Pacific (Hyderabad) region. M8a instances are powered by 5th Gen AMD EPYC processors (formerly code named Turin) with a maximum frequency of 4.5 GHz, deliver up to 30% higher performance, and up to 19% better price-performance compared to M7a instances. M8a instances deliver 45% more memory bandwidth compared to M7a instances, making these instances ideal for even latency sensitive workloads. M8a instances deliver even higher performance gains for specific workloads. M8a instances are up to 60% faster for GroovyJVM benchmark, and up to 39% faster for Cassandra benchmark compared to Amazon EC2 M7a instances. M8a instances are SAP-certified and offer 12 sizes including 2 bare metal sizes. This range of instance sizes allows customers to precisely match their workload requirements. M8a instances are built using the latest sixth generation AWS Nitro Cards and ideal for applications that benefit from high performance and high throughput such as financial applications, gaming, rendering, application servers, simulation modeling, mid-size data stores, application development environments, and caching fleets. To get started, sign in to the AWS Management Console. Customers can purchase these instances via Savings Plans, On-Demand instances, and Spot instances. For more information visit the Amazon EC2 M8a instance page.  

AWS Entity Resolution now supports real-time matching with advanced matching workflows, enabling customers to match records in milliseconds using complex rulesets through the GenerateMatchId API. Previously, real-time matching was limited to simple rule-based workflows, while advanced rulesets—which support operators like Exact and ExactManyToMany combined with AND/OR logic—could only be used for batch processing that took minutes to hours. This created a critical gap for customers needing real-time entity resolution with sophisticated matching logic.

With this launch, customers performing fraud detection, real-time account lookup, or website personalization can define advanced matching rules and get results in real-time without maintaining separate matching infrastructure or re-architecting applications. To enable advanced real-time matching, customers set the enableRealTimeMatching parameter to true on their matching workflow, then call the existing GenerateMatchId API—no new endpoints or migration required.

Advanced real-time matching is available in all AWS Regions where AWS Entity Resolution is available. 

To get started, see Using GenerateMatchId in the AWS Entity Resolution User Guide.  

For more information about AWS Entity Resolution, visit the product page.

 

​AWS Entity Resolution now supports real-time matching with advanced matching workflows, enabling customers to match records in milliseconds using complex rulesets through the GenerateMatchId API. Previously, real-time matching was limited to simple rule-based workflows, while advanced rulesets—which support operators like Exact and ExactManyToMany combined with AND/OR logic—could only be used for batch processing that took minutes to hours. This created a critical gap for customers needing real-time entity resolution with sophisticated matching logic.
With this launch, customers performing fraud detection, real-time account lookup, or website personalization can define advanced matching rules and get results in real-time without maintaining separate matching infrastructure or re-architecting applications. To enable advanced real-time matching, customers set the enableRealTimeMatching parameter to true on their matching workflow, then call the existing GenerateMatchId API—no new endpoints or migration required.
Advanced real-time matching is available in all AWS Regions where AWS Entity Resolution is available. 
To get started, see Using GenerateMatchId in the AWS Entity Resolution User Guide.  
For more information about AWS Entity Resolution, visit the product page.  

Network Load Balancer (NLB) now supports listener rules allowing you to route connections to different target groups based on the source IP address type. With listener rules, a single dual-stack NLB sends IPv6 client traffic to IPv6 targets and IPv4 client traffic to IPv4 targets, preserving the original client IP address end to end for both address families.

Previously, serving both IPv4 and IPv6 clients from one NLB meant accepting a tradeoff: either run two separate load balancers (one per IP version) and split clients with DNS, or send all traffic to one target group and lose the original client IP through protocol translation. Listener rules remove that tradeoff by enabling conditional routing at Layer 3, directing each connection to a same-family target group with no translation and no additional infrastructure.

You can add listener rules to existing dual-stack NLBs without recreating them. Rules are supported on TCP, UDP, TCP_UDP, and TLS listeners and work alongside existing NLB features including connection draining, target group stickiness, cross-zone load balancing, weighted target groups, and client IP preservation.

Listener rules for Network Load Balancer are available in all AWS commercial Regions and the AWS GovCloud (US) Regions at no additional charge. Standard NLB pricing for load balancer hours and LCUs applies. To get started, see this AWS blog, and the Network Load Balancer User Guide.

 

​Network Load Balancer (NLB) now supports listener rules allowing you to route connections to different target groups based on the source IP address type. With listener rules, a single dual-stack NLB sends IPv6 client traffic to IPv6 targets and IPv4 client traffic to IPv4 targets, preserving the original client IP address end to end for both address families. Previously, serving both IPv4 and IPv6 clients from one NLB meant accepting a tradeoff: either run two separate load balancers (one per IP version) and split clients with DNS, or send all traffic to one target group and lose the original client IP through protocol translation. Listener rules remove that tradeoff by enabling conditional routing at Layer 3, directing each connection to a same-family target group with no translation and no additional infrastructure. You can add listener rules to existing dual-stack NLBs without recreating them. Rules are supported on TCP, UDP, TCP_UDP, and TLS listeners and work alongside existing NLB features including connection draining, target group stickiness, cross-zone load balancing, weighted target groups, and client IP preservation. Listener rules for Network Load Balancer are available in all AWS commercial Regions and the AWS GovCloud (US) Regions at no additional charge. Standard NLB pricing for load balancer hours and LCUs applies. To get started, see this AWS blog, and the Network Load Balancer User Guide.  

AWS Lambda durable functions now supports encryption of durable execution data with an AWS Key Management Service (AWS KMS) customer managed key. Lambda durable functions lets you build long-running, reliable workflows directly in your Lambda function code with automatic state management. Lambda encrypts execution state at rest by default with an AWS owned key. Now with support for AWS KMS, you can choose and manage the encryption key yourself.

If you operate in regulated industries such as financial services or healthcare, your data governance policies may require customer-owned encryption keys. You can now configure a customer managed key for durable execution data, giving you control over key rotation and who can access execution history and state. The durable execution key operates independently of the function-level key that protects environment variables and SnapStart snapshots, so you can manage access to execution data separately from function configuration.

This feature is available in all AWS Regions where Lambda durable functions is available. Standard AWS KMS charges apply for customer managed keys. There are no additional Lambda charges for this feature.

To learn more, see Encrypting Lambda durable execution data in the AWS Lambda Developer Guide. 

 

​AWS Lambda durable functions now supports encryption of durable execution data with an AWS Key Management Service (AWS KMS) customer managed key. Lambda durable functions lets you build long-running, reliable workflows directly in your Lambda function code with automatic state management. Lambda encrypts execution state at rest by default with an AWS owned key. Now with support for AWS KMS, you can choose and manage the encryption key yourself.
If you operate in regulated industries such as financial services or healthcare, your data governance policies may require customer-owned encryption keys. You can now configure a customer managed key for durable execution data, giving you control over key rotation and who can access execution history and state. The durable execution key operates independently of the function-level key that protects environment variables and SnapStart snapshots, so you can manage access to execution data separately from function configuration.
This feature is available in all AWS Regions where Lambda durable functions is available. Standard AWS KMS charges apply for customer managed keys. There are no additional Lambda charges for this feature.
To learn more, see Encrypting Lambda durable execution data in the AWS Lambda Developer Guide.   

On July 22, 2026, Amazon announced quarterly security and critical updates for Amazon Corretto Long-Term Support (LTS) and Feature Release (FR) versions of OpenJDK. Corretto 26.0.2, 25.0.4, 21.0.12, 17.0.20, 11.0.32, and 8u502 are now available for download. Amazon Corretto is a no-cost, multi-platform, production-ready distribution of OpenJDK.

Starting with this release, the default Amazon Corretto Docker images are based on Amazon Linux 2023. Amazon Linux 2 images will continue to be provided as non-default options for customers who cannot yet migrate.

JavaFX binaries are no longer included with Corretto 8 starting from this release. You can learn more about the migration recommendations at Corretto 8 GitHub.

Visit Corretto home page to download Corretto 26, Corretto 25, Corretto 21, Corretto 17, Corretto 11, or Corretto 8. You can also get the updates on your Linux system by configuring a Corretto Apt, Yum, or Apk repo.

Feedback is welcomed!

 

​On July 22, 2026, Amazon announced quarterly security and critical updates for Amazon Corretto Long-Term Support (LTS) and Feature Release (FR) versions of OpenJDK. Corretto 26.0.2, 25.0.4, 21.0.12, 17.0.20, 11.0.32, and 8u502 are now available for download. Amazon Corretto is a no-cost, multi-platform, production-ready distribution of OpenJDK. Starting with this release, the default Amazon Corretto Docker images are based on Amazon Linux 2023. Amazon Linux 2 images will continue to be provided as non-default options for customers who cannot yet migrate. JavaFX binaries are no longer included with Corretto 8 starting from this release. You can learn more about the migration recommendations at Corretto 8 GitHub. Visit Corretto home page to download Corretto 26, Corretto 25, Corretto 21, Corretto 17, Corretto 11, or Corretto 8. You can also get the updates on your Linux system by configuring a Corretto Apt, Yum, or Apk repo. Feedback is welcomed!  

Today, AWS announced the expansion of 100 Gbps dedicated connections at the existing AWS Direct Connect location within the Cirion data center in Lima, Peru. You can now establish private, direct network access to all public AWS Regions (except those in China), AWS GovCloud Regions, and AWS Local Zones from this location. This is the first AWS Direct Connect location in Peru to provide 100 Gbps connections with MACsec encryption capabilities.

The Direct Connect service enables you to establish a private, physical network connection between AWS and your data center, office, or colocation environment. These private connections can provide a more consistent network experience than those made over the public internet.

For more information on the over 150 Direct Connect locations worldwide, visit the locations section of the Direct Connect product detail pages. Or, visit our getting started page to learn more about how to purchase and deploy Direct Connect.

 

​Today, AWS announced the expansion of 100 Gbps dedicated connections at the existing AWS Direct Connect location within the Cirion data center in Lima, Peru. You can now establish private, direct network access to all public AWS Regions (except those in China), AWS GovCloud Regions, and AWS Local Zones from this location. This is the first AWS Direct Connect location in Peru to provide 100 Gbps connections with MACsec encryption capabilities.
The Direct Connect service enables you to establish a private, physical network connection between AWS and your data center, office, or colocation environment. These private connections can provide a more consistent network experience than those made over the public internet.
For more information on the over 150 Direct Connect locations worldwide, visit the locations section of the Direct Connect product detail pages. Or, visit our getting started page to learn more about how to purchase and deploy Direct Connect.