Starting today, Amazon Elastic Compute Cloud (Amazon EC2) G7e instances accelerated by NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs are now available in the AWS Europe (Frankfurt, Stockholm) and Asia Pacific (Mumbai) Regions. G7e instances offer up to 2.3x inference performance compared to G6e.

Customers can use G7e instances to deploy large language models (LLMs), agentic AI models, multimodal generative AI models, and physical AI models. G7e instances offer the highest performance for spatial computing workloads as well as workloads that require both graphics and AI processing capabilities. G7e instances feature up to 8 NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs, with 96 GB of memory per GPU, and 5th Generation Intel Xeon processors. They support up to 192 virtual CPUs (vCPUs) and up to 1600 Gbps of networking bandwidth. G7e instances support NVIDIA GPUDirect Peer to Peer (P2P) that boosts performance for multi-GPU workloads. Multi-GPU G7e instances also support NVIDIA GPUDirect Remote Direct Memory Access (RDMA) with EFA in EC2 UltraClusters, reducing latency for small-scale multi-node workloads.

You can use G7e instances for Amazon EC2 in the following AWS Regions: US West (Oregon), US East (N. Virginia, Ohio), Europe (Spain, London, Frankfurt, Stockholm) and Asia Pacific (Tokyo, Seoul, Mumbai). You can purchase G7e instances as On-Demand Instances, Spot Instances, or as part of Savings Plans.

To get started, visit the AWS Management Console, AWS Command Line Interface (CLI), and AWS SDKs. To learn more, visit G7e instances.

 

​Starting today, Amazon Elastic Compute Cloud (Amazon EC2) G7e instances accelerated by NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs are now available in the AWS Europe (Frankfurt, Stockholm) and Asia Pacific (Mumbai) Regions. G7e instances offer up to 2.3x inference performance compared to G6e.
Customers can use G7e instances to deploy large language models (LLMs), agentic AI models, multimodal generative AI models, and physical AI models. G7e instances offer the highest performance for spatial computing workloads as well as workloads that require both graphics and AI processing capabilities. G7e instances feature up to 8 NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs, with 96 GB of memory per GPU, and 5th Generation Intel Xeon processors. They support up to 192 virtual CPUs (vCPUs) and up to 1600 Gbps of networking bandwidth. G7e instances support NVIDIA GPUDirect Peer to Peer (P2P) that boosts performance for multi-GPU workloads. Multi-GPU G7e instances also support NVIDIA GPUDirect Remote Direct Memory Access (RDMA) with EFA in EC2 UltraClusters, reducing latency for small-scale multi-node workloads.
You can use G7e instances for Amazon EC2 in the following AWS Regions: US West (Oregon), US East (N. Virginia, Ohio), Europe (Spain, London, Frankfurt, Stockholm) and Asia Pacific (Tokyo, Seoul, Mumbai). You can purchase G7e instances as On-Demand Instances, Spot Instances, or as part of Savings Plans.
To get started, visit the AWS Management Console, AWS Command Line Interface (CLI), and AWS SDKs. To learn more, visit G7e instances.  

Amazon CloudWatch Logs now supports intelligent storage tiering, which automatically classifies your log data across three storage tiers – Standard (existing), Infrequent Access, and Archive Instant Access based on access patterns. This allows you to store logs in Amazon CloudWatch for extended periods at lower-cost tiers without any operational overhead.

With today’s launch, customers can now retain high-volume verbose logs needed to be stored for longer periods at a lower cost in Amazon CloudWatch. Instead of filtering these logs or exporting them, you can now keep them natively in Amazon CloudWatch and benefit from the same query experience regardless of which tier your data resides in. Amazon CloudWatch monitors access patterns and automatically reclassifies data not accessed for 30 days to the Infrequent Access tier, and data not accessed for 90 days to the Archive Instant Access tier. When you access older data, it is automatically promoted back to the Standard tier for 30 days. By consolidating all your logs in CloudWatch, you get full visibility in one tool, thereby eliminating the operational overhead of managing multiple storage solutions and reducing your Mean Time to Resolution (MTTR) by analyzing, and alerting on all your logs in a single place.

Amazon CloudWatch Logs Intelligent-Tiering is available in all AWS commercial regions except Middle East (Bahrain) and Middle East (UAE). You can enable intelligent tiering at the account level in the AWS Management Console, AWS SDKs or through AWS CLI. Learn more about CloudWatch Logs intelligent tiering pricing and documentation.

 

​Amazon CloudWatch Logs now supports intelligent storage tiering, which automatically classifies your log data across three storage tiers – Standard (existing), Infrequent Access, and Archive Instant Access based on access patterns. This allows you to store logs in Amazon CloudWatch for extended periods at lower-cost tiers without any operational overhead.
With today’s launch, customers can now retain high-volume verbose logs needed to be stored for longer periods at a lower cost in Amazon CloudWatch. Instead of filtering these logs or exporting them, you can now keep them natively in Amazon CloudWatch and benefit from the same query experience regardless of which tier your data resides in. Amazon CloudWatch monitors access patterns and automatically reclassifies data not accessed for 30 days to the Infrequent Access tier, and data not accessed for 90 days to the Archive Instant Access tier. When you access older data, it is automatically promoted back to the Standard tier for 30 days. By consolidating all your logs in CloudWatch, you get full visibility in one tool, thereby eliminating the operational overhead of managing multiple storage solutions and reducing your Mean Time to Resolution (MTTR) by analyzing, and alerting on all your logs in a single place.
Amazon CloudWatch Logs Intelligent-Tiering is available in all AWS commercial regions except Middle East (Bahrain) and Middle East (UAE). You can enable intelligent tiering at the account level in the AWS Management Console, AWS SDKs or through AWS CLI. Learn more about CloudWatch Logs intelligent tiering pricing and documentation.  

Amazon Cognito now supports importing users with password hashes in CSV user imports. Previously, users imported from a CSV file had to reset their passwords on first sign-in. Now, you can include password hashes in your CSV file so that imported users can sign in immediately with their existing credentials.

When creating a CSV import, you specify the password hashing algorithm used by your source system. Amazon Cognito imports these users and verifies their password against the imported hash on first sign-in. Supported algorithms include bcrypt, scrypt, Argon2id, and PBKDF2 with SHA-256. All imported hashes receive an additional layer of cryptographic protection before storage.

Password hash import is available in all AWS Regions where Amazon Cognito is available. To get started, create a user import using the AWS Management Console, AWS Command Line Interface (CLI), or AWS Software Development Kits (SDKs). See the developer guide for instructions.

 

​Amazon Cognito now supports importing users with password hashes in CSV user imports. Previously, users imported from a CSV file had to reset their passwords on first sign-in. Now, you can include password hashes in your CSV file so that imported users can sign in immediately with their existing credentials. When creating a CSV import, you specify the password hashing algorithm used by your source system. Amazon Cognito imports these users and verifies their password against the imported hash on first sign-in. Supported algorithms include bcrypt, scrypt, Argon2id, and PBKDF2 with SHA-256. All imported hashes receive an additional layer of cryptographic protection before storage. Password hash import is available in all AWS Regions where Amazon Cognito is available. To get started, create a user import using the AWS Management Console, AWS Command Line Interface (CLI), or AWS Software Development Kits (SDKs). See the developer guide for instructions.  

Amazon MQ now allows you to configure the EBS Disk storage size for RabbitMQ brokers independently of instance type. When creating or updating a broker, you can define a custom storage size, allowing you to right-size storage independently of your instance size to match your specific messaging workload requirements. Configurable storage is available for RabbitMQ M7g brokers on version 4.2 or later using cluster deployments only.

With configurable storage, you can choose a storage size from the default value on M7g to the maximum allowed value depending on your instance size in increments of 5 GB. You can specify the Storage Size using the using the AWS Console, AWS CloudFormation, AWS Command Line Interface (CLI), or the AWS Cloud Development Kit (CDK). Storage changes are applied during the next broker reboot. 

Standard Amazon MQ storage pricing applies based on the disk size as per Amazon MQ pricing. Configurable storage is available in all commercial AWS Regions where Amazon MQ for RabbitMQ is offered. To learn more, see the Amazon MQ Developer Guide.

 

​Amazon MQ now allows you to configure the EBS Disk storage size for RabbitMQ brokers independently of instance type. When creating or updating a broker, you can define a custom storage size, allowing you to right-size storage independently of your instance size to match your specific messaging workload requirements. Configurable storage is available for RabbitMQ M7g brokers on version 4.2 or later using cluster deployments only.
With configurable storage, you can choose a storage size from the default value on M7g to the maximum allowed value depending on your instance size in increments of 5 GB. You can specify the Storage Size using the using the AWS Console, AWS CloudFormation, AWS Command Line Interface (CLI), or the AWS Cloud Development Kit (CDK). Storage changes are applied during the next broker reboot. 
Standard Amazon MQ storage pricing applies based on the disk size as per Amazon MQ pricing. Configurable storage is available in all commercial AWS Regions where Amazon MQ for RabbitMQ is offered. To learn more, see the Amazon MQ Developer Guide.  

Amazon Managed Streaming for Apache Kafka (Amazon MSK) Express Brokers now supports Apache Kafka version 4.2. This release includes Eligible Leader Replicas (ELR) enhancements that strengthen availability with improved leader election correctness. It also introduces a new consumer rebalance protocol that helps ensure smoother and faster group rebalances, and a new Streams Rebalance Protocol that extends broker coordination capabilities to Kafka Streams for optimized task assignments. For a complete list of improvements and bug fixes, please refer to the Apache Kafka release notes for version 4.2.

MSK Express Brokers are designed to deliver up to three times more throughput per broker, scale up to 20 times faster, and reduce recovery time by 90 percent. This launch brings the latest open-source reliability and performance improvements to MSK Express.

To get started, simply select version 4.2.x when creating a new cluster with Express Brokers via the AWS Management Console, AWS CLI, or AWS SDKs. You can also upgrade existing MSK Express Brokers with an in-place rolling update. Amazon MSK orchestrates broker restarts to maintain availability and protect your data during the upgrade. Kafka version 4.2 support is available today across all AWS regions where Amazon MSK Express Brokers is offered. To learn how to get started, see the Amazon MSK Developer Guide.

 

​Amazon Managed Streaming for Apache Kafka (Amazon MSK) Express Brokers now supports Apache Kafka version 4.2. This release includes Eligible Leader Replicas (ELR) enhancements that strengthen availability with improved leader election correctness. It also introduces a new consumer rebalance protocol that helps ensure smoother and faster group rebalances, and a new Streams Rebalance Protocol that extends broker coordination capabilities to Kafka Streams for optimized task assignments. For a complete list of improvements and bug fixes, please refer to the Apache Kafka release notes for version 4.2. MSK Express Brokers are designed to deliver up to three times more throughput per broker, scale up to 20 times faster, and reduce recovery time by 90 percent. This launch brings the latest open-source reliability and performance improvements to MSK Express. To get started, simply select version 4.2.x when creating a new cluster with Express Brokers via the AWS Management Console, AWS CLI, or AWS SDKs. You can also upgrade existing MSK Express Brokers with an in-place rolling update. Amazon MSK orchestrates broker restarts to maintain availability and protect your data during the upgrade. Kafka version 4.2 support is available today across all AWS regions where Amazon MSK Express Brokers is offered. To learn how to get started, see the Amazon MSK Developer Guide.  

Amazon Relational Database Service (RDS) now supports R8gd database instances in 12 additional regions and and M8gd database instances in 6 additional Regions with Optimized Reads for Amazon Aurora PostgreSQL, RDS for PostgreSQL, RDS for MySQL, and RDS for MariaDB.

R8gd and M8gd instances deliver up to 165% better throughput and up to 120% better price-performance over R6g instances for Aurora PostgreSQL. Optimized Reads uses local NVMe-based SSD block storage to store ephemeral data such as temporary tables, reducing network storage access and improving query latency. The result is improved query performance for complex queries and faster index rebuild operations. Aurora PostgreSQL Optimized Reads instances using the I/O-Optimized configuration also use the local storage to extend their caching capacity. Database pages that are evicted from the in-memory buffer cache are cached in local storage to speed subsequent retrieval of that data.

Customers can get started with Optimized Reads through the AWS Management Console, CLI, and SDK by modifying their existing Aurora and RDS databases or creating a new database using R8gd or M8gd instances. R8gd instances are available in the following additional regions: Europe (Ireland), Asia Pacific (Seoul), Asia Pacific (Malaysia), Europe (London), US West (N. California), Asia Pacific (Sydney), Canada (Central), Asia Pacific (Jakarta), Africa (Cape Town), Canada West (Calgary), South America (Sao Paulo) and Asia Pacific (Hong Kong). M8gd instances are available in the following additional regions: Europe (Ireland), Asia Pacific (Malaysia), Europe (London), Asia Pacific (Sydney), South America (Sao Paulo) and Canada (Central). For complete information on pricing and regional availability, please refer to the pricing page. For information on specific engine versions that support these DB instance types, please see the Aurora and RDS documentation.

 

​Amazon Relational Database Service (RDS) now supports R8gd database instances in 12 additional regions and and M8gd database instances in 6 additional Regions with Optimized Reads for Amazon Aurora PostgreSQL, RDS for PostgreSQL, RDS for MySQL, and RDS for MariaDB. R8gd and M8gd instances deliver up to 165% better throughput and up to 120% better price-performance over R6g instances for Aurora PostgreSQL. Optimized Reads uses local NVMe-based SSD block storage to store ephemeral data such as temporary tables, reducing network storage access and improving query latency. The result is improved query performance for complex queries and faster index rebuild operations. Aurora PostgreSQL Optimized Reads instances using the I/O-Optimized configuration also use the local storage to extend their caching capacity. Database pages that are evicted from the in-memory buffer cache are cached in local storage to speed subsequent retrieval of that data. Customers can get started with Optimized Reads through the AWS Management Console, CLI, and SDK by modifying their existing Aurora and RDS databases or creating a new database using R8gd or M8gd instances. R8gd instances are available in the following additional regions: Europe (Ireland), Asia Pacific (Seoul), Asia Pacific (Malaysia), Europe (London), US West (N. California), Asia Pacific (Sydney), Canada (Central), Asia Pacific (Jakarta), Africa (Cape Town), Canada West (Calgary), South America (Sao Paulo) and Asia Pacific (Hong Kong). M8gd instances are available in the following additional regions: Europe (Ireland), Asia Pacific (Malaysia), Europe (London), Asia Pacific (Sydney), South America (Sao Paulo) and Canada (Central). For complete information on pricing and regional availability, please refer to the pricing page. For information on specific engine versions that support these DB instance types, please see the Aurora and RDS documentation.  

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.