AWS Graviton4-based R8g database instances are now generally available for Amazon Aurora (MySQL and PostgreSQL compatibility) and Amazon RDS for PostgreSQL, MySQL, and MariaDB in Asia Pacific (Hyderabad, Melbourne, Malaysia), Europe (London, Paris, Zurich), AWS GovCloud (US-East), South America (Sao Paulo), and Mexico (Central) regions. Additionally, M8g instances are now supported for Amazon RDS for PostgreSQL, MySQL, and MariaDB in US West (N. California), Asia Pacific (Mumbai, Sydney, Hong Kong, Seoul, Malaysia, Singapore), Canada West (Calgary), Europe (Zurich, Milan, Paris), South America (Sao Paulo) and Africa (Cape Town) regions. 

AWS Graviton4-based instances provide up to 40% performance improvement and up to 29% price/performance improvement for on-demand pricing over Graviton3-based instances of equivalent sizes on Amazon Aurora and Amazon RDS databases, depending on database engine, version, and workload. Built on the AWS Nitro System, the new R8g database instances introduce 24xlarge and 48xlarge sizes, delivering up to 192 vCPUs, an 8:1 ratio of memory to vCPU with the latest DDR5 memory, up to 50Gbps enhanced networking bandwidth, and up to 40Gbps of bandwidth to Amazon Elastic Block Store (Amazon EBS).

You can easily launch R8g or M8g database instances through the Amazon RDS Management Console or by using the AWS Command Line Interface (CLI). For detailed information about specific engine versions that support these database instance types, please refer to the Aurora and RDS documentation. For complete information on pricing and regional availability, please refer to the Amazon RDS pricing page. 

 

​AWS Graviton4-based R8g database instances are now generally available for Amazon Aurora (MySQL and PostgreSQL compatibility) and Amazon RDS for PostgreSQL, MySQL, and MariaDB in Asia Pacific (Hyderabad, Melbourne, Malaysia), Europe (London, Paris, Zurich), AWS GovCloud (US-East), South America (Sao Paulo), and Mexico (Central) regions. Additionally, M8g instances are now supported for Amazon RDS for PostgreSQL, MySQL, and MariaDB in US West (N. California), Asia Pacific (Mumbai, Sydney, Hong Kong, Seoul, Malaysia, Singapore), Canada West (Calgary), Europe (Zurich, Milan, Paris), South America (Sao Paulo) and Africa (Cape Town) regions.  AWS Graviton4-based instances provide up to 40% performance improvement and up to 29% price/performance improvement for on-demand pricing over Graviton3-based instances of equivalent sizes on Amazon Aurora and Amazon RDS databases, depending on database engine, version, and workload. Built on the AWS Nitro System, the new R8g database instances introduce 24xlarge and 48xlarge sizes, delivering up to 192 vCPUs, an 8:1 ratio of memory to vCPU with the latest DDR5 memory, up to 50Gbps enhanced networking bandwidth, and up to 40Gbps of bandwidth to Amazon Elastic Block Store (Amazon EBS). You can easily launch R8g or M8g database instances through the Amazon RDS Management Console or by using the AWS Command Line Interface (CLI). For detailed information about specific engine versions that support these database instance types, please refer to the Aurora and RDS documentation. For complete information on pricing and regional availability, please refer to the Amazon RDS pricing page.   

Amazon Relational Database Service (Amazon RDS) for Db2 is now available in the Asia Pacific (Thailand), Asia Pacific (Malaysia), Asia Pacific (Taipei), Mexico (Central), and Canada West (Calgary) Regions. Amazon RDS for Db2 makes it easy to set up, operate, and scale Db2 databases in the cloud. Customers can deploy a Db2 database in minutes with automatically configured parameters for optimal performance. For databases setup with Multi-AZ configuration, Amazon RDS performs synchronous replication to a standby instance in a different Availability Zone to provide high availability.

To use Amazon RDS for Db2, customers can purchase a Db2 license from the AWS Marketplace for hourly, pay-as-you-go pricing, or use Bring Your Own License (BYOL). Both hourly and BYOL licensing are available in Standard and Advanced Editions. You can also choose to use the latest Db2 Community Edition that provides all the features available in Standard and Advanced Editions, with no commercial software licensing charges for development and test applications. This allows you to easily start developing and testing Db2 applications with a managed database service without worrying about software licensing.

To learn more about Amazon RDS for Db2, refer to documentation and pricing pages.

 

 

​Amazon Relational Database Service (Amazon RDS) for Db2 is now available in the Asia Pacific (Thailand), Asia Pacific (Malaysia), Asia Pacific (Taipei), Mexico (Central), and Canada West (Calgary) Regions. Amazon RDS for Db2 makes it easy to set up, operate, and scale Db2 databases in the cloud. Customers can deploy a Db2 database in minutes with automatically configured parameters for optimal performance. For databases setup with Multi-AZ configuration, Amazon RDS performs synchronous replication to a standby instance in a different Availability Zone to provide high availability. To use Amazon RDS for Db2, customers can purchase a Db2 license from the AWS Marketplace for hourly, pay-as-you-go pricing, or use Bring Your Own License (BYOL). Both hourly and BYOL licensing are available in Standard and Advanced Editions. You can also choose to use the latest Db2 Community Edition that provides all the features available in Standard and Advanced Editions, with no commercial software licensing charges for development and test applications. This allows you to easily start developing and testing Db2 applications with a managed database service without worrying about software licensing. To learn more about Amazon RDS for Db2, refer to documentation and pricing pages.
   

Amazon RDS now allows up to four storage modifications per database instance within a rolling 24-hour window. These modifications let you increase the size, change the type, and adjust the performance of your RDS storage volumes. You can start a new modification right after storage optimization for the previous modification is complete without having to wait for the six-hour cool-off period to complete.

This enhancement improves operational agility for scaling storage capacity or adjusting performance during sudden data growth or unexpected workload spikes. With RDS storage modifications, you can modify your volumes without downtime, keeping applications running with minimal performance impact.

The feature is automatically enabled on all Amazon RDS for PostgreSQL, Amazon RDS for MariaDB, Amazon RDS for MySQL, Amazon RDS for Db2, Amazon RDS for Oracle, and Amazon RDS for Microsoft SQL Server instances in all commercial AWS Regions and the AWS GovCloud (US) Regions. To learn more, refer the Amazon RDS User Guide.

 

​Amazon RDS now allows up to four storage modifications per database instance within a rolling 24-hour window. These modifications let you increase the size, change the type, and adjust the performance of your RDS storage volumes. You can start a new modification right after storage optimization for the previous modification is complete without having to wait for the six-hour cool-off period to complete.
This enhancement improves operational agility for scaling storage capacity or adjusting performance during sudden data growth or unexpected workload spikes. With RDS storage modifications, you can modify your volumes without downtime, keeping applications running with minimal performance impact.
The feature is automatically enabled on all Amazon RDS for PostgreSQL, Amazon RDS for MariaDB, Amazon RDS for MySQL, Amazon RDS for Db2, Amazon RDS for Oracle, and Amazon RDS for Microsoft SQL Server instances in all commercial AWS Regions and the AWS GovCloud (US) Regions. To learn more, refer the Amazon RDS User Guide.  

Amazon OpenSearch Service now integrates with the Agent Toolkit for AWS, enabling you to build, manage, and query OpenSearch Service domains and OpenSearch Serverless collections directly from AI coding agents such as Claude Code, Kiro, and Cursor. The integration is powered by the AWS MCP (Model Context Protocol) server, which executes AWS API calls on your behalf, paired with the curated amazon-opensearch-service skill that automatically routes natural-language requests to the right capability.

With this skill, you can describe a goal in plain language and the agent handles the rest across five areas. Migration moves you from self-managed OpenSearch into OpenSearch Service or OpenSearch Serverless. Operations provisions and manages domains and collections. Search builds vector, semantic, hybrid, and RAG search. Log analytics analyzes logs with PPL and OpenSearch Ingestion. Trace analytics investigates distributed traces with OpenTelemetry. The integration works with both managed domains and collections across all versions, requires no changes to your existing infrastructure, and is available at no additional charge. To learn more about these capabilities, see our documentation.

Support is available in all AWS Regions where Amazon OpenSearch Service and OpenSearch Serverless are offered. To get started, install the aws-data-analytics plugin in your agent — it bundles the AWS MCP Server configuration and the OpenSearch skill in a single step. For setup instructions, see MCP Server and Agent Skills. 

 

​Amazon OpenSearch Service now integrates with the Agent Toolkit for AWS, enabling you to build, manage, and query OpenSearch Service domains and OpenSearch Serverless collections directly from AI coding agents such as Claude Code, Kiro, and Cursor. The integration is powered by the AWS MCP (Model Context Protocol) server, which executes AWS API calls on your behalf, paired with the curated amazon-opensearch-service skill that automatically routes natural-language requests to the right capability. With this skill, you can describe a goal in plain language and the agent handles the rest across five areas. Migration moves you from self-managed OpenSearch into OpenSearch Service or OpenSearch Serverless. Operations provisions and manages domains and collections. Search builds vector, semantic, hybrid, and RAG search. Log analytics analyzes logs with PPL and OpenSearch Ingestion. Trace analytics investigates distributed traces with OpenTelemetry. The integration works with both managed domains and collections across all versions, requires no changes to your existing infrastructure, and is available at no additional charge. To learn more about these capabilities, see our documentation. Support is available in all AWS Regions where Amazon OpenSearch Service and OpenSearch Serverless are offered. To get started, install the aws-data-analytics plugin in your agent — it bundles the AWS MCP Server configuration and the OpenSearch skill in a single step. For setup instructions, see MCP Server and Agent Skills.   

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) M8in, M8idn network optimized, and M8ib, M8idb EBS optimized instances are available in the AWS US East (Ohio), Europe (Ireland), and Asia Pacific (Tokyo) regions. The new instances are powered by custom sixth generation Intel Xeon Scalable processors available only on AWS and deliver up to 43% higher performance compared to previous generation instances. These instances also feature the latest sixth generation AWS Nitro cards.

M8in, M8idn instances deliver 600 Gbps network bandwidth, the highest network bandwidth among enhanced networking EC2 instances, and are ideal for workloads such as real-time big data analytics, distributed web scale in-memory caches, caching fleets for AI/ML clusters, and Telco applications such as 5G User Plane Function (UPF). 
 
M8ib, M8idb instances deliver up to 300Gbps EBS bandwidth, the highest among non-accelerated compute EC2 instances, and are best suited for workloads that benefit from high block storage performance, such as high-performance file systems and NoSQL databases.

M8idn instances are ideal for network-intensive workloads that benefit from low-latency local storage, such as distributed compute, data analytics, and high-performance file systems. M8idb instances are ideal for storage-intensive workloads such as large commercial databases, data lakes, and NoSQL databases that benefit from both high EBS throughput and low-latency local NVMe storage. 

M8in, M8idn, M8ib, M8idb instances are available in US East (N. Virginia, Ohio), US West (Oregon), Europe (Ireland), Asia Pacific (Tokyo), and Europe (Spain) regions, via Savings Plans, On-Demand, and Spot instances. For more information, visit the Amazon EC2 M8i instance page.

 

​Starting today, Amazon Elastic Compute Cloud (Amazon EC2) M8in, M8idn network optimized, and M8ib, M8idb EBS optimized instances are available in the AWS US East (Ohio), Europe (Ireland), and Asia Pacific (Tokyo) regions. The new instances are powered by custom sixth generation Intel Xeon Scalable processors available only on AWS and deliver up to 43% higher performance compared to previous generation instances. These instances also feature the latest sixth generation AWS Nitro cards.
M8in, M8idn instances deliver 600 Gbps network bandwidth, the highest network bandwidth among enhanced networking EC2 instances, and are ideal for workloads such as real-time big data analytics, distributed web scale in-memory caches, caching fleets for AI/ML clusters, and Telco applications such as 5G User Plane Function (UPF).    M8ib, M8idb instances deliver up to 300Gbps EBS bandwidth, the highest among non-accelerated compute EC2 instances, and are best suited for workloads that benefit from high block storage performance, such as high-performance file systems and NoSQL databases.
M8idn instances are ideal for network-intensive workloads that benefit from low-latency local storage, such as distributed compute, data analytics, and high-performance file systems. M8idb instances are ideal for storage-intensive workloads such as large commercial databases, data lakes, and NoSQL databases that benefit from both high EBS throughput and low-latency local NVMe storage. 
M8in, M8idn, M8ib, M8idb instances are available in US East (N. Virginia, Ohio), US West (Oregon), Europe (Ireland), Asia Pacific (Tokyo), and Europe (Spain) regions, via Savings Plans, On-Demand, and Spot instances. For more information, visit the Amazon EC2 M8i instance page.  

AWS Lambda now supports self-managed Amazon S3 buckets for code storage, enabling you to reference source code directly from your own S3 buckets without Lambda creating intermediate copies. This eliminates code storage limits and reduces function activation time after function creates and updates by removing the copy step.

AWS Lambda is a serverless compute service that runs your code without requiring you to manage servers. Customers who deploy many functions and additional code as Lambda layers often need more than 75GB of code storage per Region, requiring support tickets to increase this quota. Previously, Lambda always copied your deployment package to Lambda-managed storage during function and layer creation, counting against this limit. Now, with self-managed code storage, Lambda references your code directly in your Amazon S3 bucket without creating a copy, so you can store as much function and layer code as your bucket allows. You maintain a single source of truth for your deployment packages in your own account. No additional Lambda charges apply for self-managed storage; you only pay for standard Amazon S3 storage and, where applicable, cross-Region data transfer rates. In addition, Lambda has increased the default limit for Lambda-managed code storage from 75GB to 300GB per Region per account.

Self-managed Amazon S3 code storage is available in all commercial AWS Regions.

To get started, set the `S3ObjectStorageMode` parameter to `REFERENCE` when creating or updating functions and layers through the AWS CLI, AWS CloudFormation, AWS SAM, or AWS SDKs. You must grant the Lambda service principal `s3:GetObject` and `s3:GetObjectVersion` permissions on your S3 bucket. You can also update a function to use self-managed code storage via the Lambda Console. To learn more, visit the AWS Lambda Developer Guide.

 

​AWS Lambda now supports self-managed Amazon S3 buckets for code storage, enabling you to reference source code directly from your own S3 buckets without Lambda creating intermediate copies. This eliminates code storage limits and reduces function activation time after function creates and updates by removing the copy step.
AWS Lambda is a serverless compute service that runs your code without requiring you to manage servers. Customers who deploy many functions and additional code as Lambda layers often need more than 75GB of code storage per Region, requiring support tickets to increase this quota. Previously, Lambda always copied your deployment package to Lambda-managed storage during function and layer creation, counting against this limit. Now, with self-managed code storage, Lambda references your code directly in your Amazon S3 bucket without creating a copy, so you can store as much function and layer code as your bucket allows. You maintain a single source of truth for your deployment packages in your own account. No additional Lambda charges apply for self-managed storage; you only pay for standard Amazon S3 storage and, where applicable, cross-Region data transfer rates. In addition, Lambda has increased the default limit for Lambda-managed code storage from 75GB to 300GB per Region per account.
Self-managed Amazon S3 code storage is available in all commercial AWS Regions.
To get started, set the `S3ObjectStorageMode` parameter to `REFERENCE` when creating or updating functions and layers through the AWS CLI, AWS CloudFormation, AWS SAM, or AWS SDKs. You must grant the Lambda service principal `s3:GetObject` and `s3:GetObjectVersion` permissions on your S3 bucket. You can also update a function to use self-managed code storage via the Lambda Console. To learn more, visit the AWS Lambda Developer Guide.  

Amazon Managed Service for Apache Flink now offers AI Agent Skills that give AI coding assistants expert, up-to-date guidance for building and operating Flink applications. The skills provide expert guidance for common tasks such as creating applications, troubleshooting, scaling, monitoring, networking configuration, and cost optimization.

Customers can leverage these skills to keep Flink applications healthy and performant, accelerate development of new streaming applications, and easily upgrade to latest versions of Apache Flink like Flink 2.2. The skills turn tasks that once required specialized Apache Flink knowledge into a guided experience developers can complete on their own.

You can use the Managed Service for Apache Flink skills with your existing AI coding agent, including Kiro, Claude Code, or Cursor. To get started, configure the Agent Toolkit for AWS using the AWS CLI, then ask your coding agent a question, such as «How do I create a new Flink application on MSF?» or «My Flink application is unhealthy — what’s wrong?»

 

​Amazon Managed Service for Apache Flink now offers AI Agent Skills that give AI coding assistants expert, up-to-date guidance for building and operating Flink applications. The skills provide expert guidance for common tasks such as creating applications, troubleshooting, scaling, monitoring, networking configuration, and cost optimization.
Customers can leverage these skills to keep Flink applications healthy and performant, accelerate development of new streaming applications, and easily upgrade to latest versions of Apache Flink like Flink 2.2. The skills turn tasks that once required specialized Apache Flink knowledge into a guided experience developers can complete on their own.
You can use the Managed Service for Apache Flink skills with your existing AI coding agent, including Kiro, Claude Code, or Cursor. To get started, configure the Agent Toolkit for AWS using the AWS CLI, then ask your coding agent a question, such as «How do I create a new Flink application on MSF?» or «My Flink application is unhealthy — what’s wrong?»  

AWS Elastic Disaster Recovery (AWS DRS) now supports the Amazon EBS volume initialization rate, helping recovered volumes reach full performance faster during drills and recoveries. When DRS restores EBS volumes from snapshots, the data loads from Amazon S3 in the background, and I/O to blocks that haven’t loaded yet can be slower until initialization finishes. With this launch, you can set a volume initialization rate on your DRS-managed EC2 launch template, and DRS applies it automatically when it creates volumes during recovery — bringing your applications to full storage performance on a predictable timeline.

This is especially valuable for I/O-intensive workloads such as databases, where fast, consistent storage performance is critical to meeting your recovery time objectives. You set the rate once on the launch template, and DRS preserves it across the updates it makes for rightsizing or disk changes. If the rate cannot be applied for a given recovery, DRS completes recovery without it, so your recovery is never blocked.

AWS DRS support for the EBS volume initialization rate is available in all AWS Regions and environments where the EBS volume initialization rate is offered. You are charged per GB based on the full snapshot size and the rate you specify; for details, see Amazon EBS pricing. To learn more, see the AWS Elastic Disaster Recovery User Guide.

 

​AWS Elastic Disaster Recovery (AWS DRS) now supports the Amazon EBS volume initialization rate, helping recovered volumes reach full performance faster during drills and recoveries. When DRS restores EBS volumes from snapshots, the data loads from Amazon S3 in the background, and I/O to blocks that haven’t loaded yet can be slower until initialization finishes. With this launch, you can set a volume initialization rate on your DRS-managed EC2 launch template, and DRS applies it automatically when it creates volumes during recovery — bringing your applications to full storage performance on a predictable timeline.
This is especially valuable for I/O-intensive workloads such as databases, where fast, consistent storage performance is critical to meeting your recovery time objectives. You set the rate once on the launch template, and DRS preserves it across the updates it makes for rightsizing or disk changes. If the rate cannot be applied for a given recovery, DRS completes recovery without it, so your recovery is never blocked.
AWS DRS support for the EBS volume initialization rate is available in all AWS Regions and environments where the EBS volume initialization rate is offered. You are charged per GB based on the full snapshot size and the rate you specify; for details, see Amazon EBS pricing. To learn more, see the AWS Elastic Disaster Recovery User Guide.  

AWS Elastic Disaster Recovery (AWS DRS) now recovers your AWS-based workloads faster. For source servers running on Amazon EC2, DRS can now skip preparation steps that these workloads no longer need, reducing recovery time by up to 65% for Windows and up to 40% for Linux.

During a disaster or a drill, every minute matters. Because workloads already running on AWS come with AWS-compatible drivers and configuration, DRS can launch them with fewer steps — helping you bring applications back online sooner and with greater confidence. Networking, drivers, and licensing are still applied automatically, so recovery stays simple and hands-off. You remain in control: turn on faster recovery across your whole account or for individual servers and change the setting whenever your needs change.

This capability is available in all AWS Regions where AWS DRS is offered, at no additional cost. To learn more, visit the AWS Elastic Disaster Recovery User Guide.

 

​AWS Elastic Disaster Recovery (AWS DRS) now recovers your AWS-based workloads faster. For source servers running on Amazon EC2, DRS can now skip preparation steps that these workloads no longer need, reducing recovery time by up to 65% for Windows and up to 40% for Linux.
During a disaster or a drill, every minute matters. Because workloads already running on AWS come with AWS-compatible drivers and configuration, DRS can launch them with fewer steps — helping you bring applications back online sooner and with greater confidence. Networking, drivers, and licensing are still applied automatically, so recovery stays simple and hands-off. You remain in control: turn on faster recovery across your whole account or for individual servers and change the setting whenever your needs change.
This capability is available in all AWS Regions where AWS DRS is offered, at no additional cost. To learn more, visit the AWS Elastic Disaster Recovery User Guide.  

AWS Lambda console now provides a one-click setup prompt for coding agents that configures your agent with AWS Serverless skills and the Serverless Model Context Protocol (MCP) server, embedding serverless best practices from the start. This setup is available on the Lambda console wherever the developers start their Lambda journey: whether they are getting started with Lambda, exploring its capabilities, or have created their first function.

Developers use coding agents to build, test, and deploy Lambda functions, but setting up an agent for serverless development previously required navigating across multiple documentation pages to find the right configuration. The one-click setup prompt eliminates this friction as it provides a prompt that instructs the agent to install AWS Serverless skills (hosted in Agent Toolkit for AWS) and the Serverless MCP server directly in the developer’s preferred coding agent. The prompt references the Lambda agent setup guide, which includes installation commands for Claude Code, Kiro, Cursor, GitHub Copilot, Codex, Devin Desktop, and OpenCode, for the AWS Serverless skills, three specialized Lambda skills (MicroVM, Managed Instances, durable functions), and Serverless MCP server configuration. If a developer does not have local AWS authentication configured, the prompt guides them to connect using the signing-in-to-aws skill.

This capability is available in all commercial AWS Regions (except Middle East (Bahrain) and Middle East (UAE)) and AWS GovCloud (US) Regions where Lambda is available. Get started by visiting the AWS Lambda console or learn more in the Lambda agent setup guide.

 

 

​AWS Lambda console now provides a one-click setup prompt for coding agents that configures your agent with AWS Serverless skills and the Serverless Model Context Protocol (MCP) server, embedding serverless best practices from the start. This setup is available on the Lambda console wherever the developers start their Lambda journey: whether they are getting started with Lambda, exploring its capabilities, or have created their first function.
Developers use coding agents to build, test, and deploy Lambda functions, but setting up an agent for serverless development previously required navigating across multiple documentation pages to find the right configuration. The one-click setup prompt eliminates this friction as it provides a prompt that instructs the agent to install AWS Serverless skills (hosted in Agent Toolkit for AWS) and the Serverless MCP server directly in the developer’s preferred coding agent. The prompt references the Lambda agent setup guide, which includes installation commands for Claude Code, Kiro, Cursor, GitHub Copilot, Codex, Devin Desktop, and OpenCode, for the AWS Serverless skills, three specialized Lambda skills (MicroVM, Managed Instances, durable functions), and Serverless MCP server configuration. If a developer does not have local AWS authentication configured, the prompt guides them to connect using the signing-in-to-aws skill.
This capability is available in all commercial AWS Regions (except Middle East (Bahrain) and Middle East (UAE)) and AWS GovCloud (US) Regions where Lambda is available. Get started by visiting the AWS Lambda console or learn more in the Lambda agent setup guide.