Starting today, Amazon EC2 customers can now force terminate instances that are stuck in the shutting-down state. EC2 Instances can get stuck in the shutting down state because of rare issues caused by frozen operating system or underlying hardware problems. When customers use force terminate, the instance will first attempt a graceful shutdown process. If unsuccessful within the timeout period, the instance proceeds with a forced shutdown. A forced shutdown may not flush the file system caches and metadata or run shutdown scripts before instance termination. Force terminate allows customers to recover resources associated with stuck instances such as vCPU Quotas or Elastic IP addresses without waiting for AWS intervention, providing greater flexibility in managing EC2 instances.

 

​Starting today, Amazon EC2 customers can now force terminate instances that are stuck in the shutting-down state. EC2 Instances can get stuck in the shutting down state because of rare issues caused by frozen operating system or underlying hardware problems. When customers use force terminate, the instance will first attempt a graceful shutdown process. If unsuccessful within the timeout period, the instance proceeds with a forced shutdown. A forced shutdown may not flush the file system caches and metadata or run shutdown scripts before instance termination. Force terminate allows customers to recover resources associated with stuck instances such as vCPU Quotas or Elastic IP addresses without waiting for AWS intervention, providing greater flexibility in managing EC2 instances.  

Amazon Simple Notification Service (Amazon SNS) now supports message group IDs in standard topics, enabling fair queue functionality for all subscribed Amazon SQS standard queues. This feature allows you to mitigate noisy neighbor impact in all multi-tenant standard queues subscribed to a SNS standard topic by ensuring that high-volume or slow-processing messages from one tenant don’t delay messages from other tenants.

When you include a message group ID in messages sent to your Amazon SNS standard topic, the topic automatically forwards these IDs to all subscribed Amazon SQS standard queues, activating fair queue behavior across those queues. This capability is particularly valuable for SaaS applications that use Amazon SNS to distribute messages to multiple processing queues, event-driven architectures serving multiple customers, and microservices that need to maintain quality of service across different request types.

This feature is now available in all AWS commercial and AWS GovCloud (US) Regions. To learn more about using message group IDs with Amazon SNS, see the Amazon SNS Developer Guide. For more information about Amazon SQS fair queues, read our blog post.

 

​Amazon Simple Notification Service (Amazon SNS) now supports message group IDs in standard topics, enabling fair queue functionality for all subscribed Amazon SQS standard queues. This feature allows you to mitigate noisy neighbor impact in all multi-tenant standard queues subscribed to a SNS standard topic by ensuring that high-volume or slow-processing messages from one tenant don’t delay messages from other tenants. When you include a message group ID in messages sent to your Amazon SNS standard topic, the topic automatically forwards these IDs to all subscribed Amazon SQS standard queues, activating fair queue behavior across those queues. This capability is particularly valuable for SaaS applications that use Amazon SNS to distribute messages to multiple processing queues, event-driven architectures serving multiple customers, and microservices that need to maintain quality of service across different request types. This feature is now available in all AWS commercial and AWS GovCloud (US) Regions. To learn more about using message group IDs with Amazon SNS, see the Amazon SNS Developer Guide. For more information about Amazon SQS fair queues, read our blog post.  

Today, Amazon Q Developer announced expanded multi-language support in AWS Management Console, AWS Console Mobile application and Q Developer in Microsoft Teams and Slack chat applications. Among the many supported languages are French, German, Italian, Japanese, Korean, Mandarin, Spanish, and Portuguese.

To get started, simply start a conversation with Q Developer using your preferred language. Q Developer will automatically detect the language and provide answers in the appropriate language, enabling global teams to learn, monitor, operate, and troubleshoot AWS resources faster and in a more accessible way.

This update is available in all AWS Regions where Amazon Q Developer is available. To get started visit Amazon Q Developer.

 

​Today, Amazon Q Developer announced expanded multi-language support in AWS Management Console, AWS Console Mobile application and Q Developer in Microsoft Teams and Slack chat applications. Among the many supported languages are French, German, Italian, Japanese, Korean, Mandarin, Spanish, and Portuguese. To get started, simply start a conversation with Q Developer using your preferred language. Q Developer will automatically detect the language and provide answers in the appropriate language, enabling global teams to learn, monitor, operate, and troubleshoot AWS resources faster and in a more accessible way. This update is available in all AWS Regions where Amazon Q Developer is available. To get started visit Amazon Q Developer.  

Amazon Simple Notification Service (Amazon SNS) now supports three additional message filtering operators: wildcard matching, anything-but wildcard matching, and anything-but prefix matching.

Amazon SNS is a fully managed pub/sub service that provides one-to-many message delivery to various endpoints, including AWS Lambda, Amazon SQS, Amazon Data Firehose, SMS via AWS End User Messaging, push notifications, and email. With this launch, topic subscribers can use these additional operators to define more flexible message filtering policies, ensuring they receive only relevant messages. This reduces the need for additional filtering logic in subscriber applications.

Amazon SNS message filtering is available in all AWS commercial Regions and AWS GovCloud (US) Regions. To learn more, see Message Filtering in the Amazon SNS Developer Guide.

 

​Amazon Simple Notification Service (Amazon SNS) now supports three additional message filtering operators: wildcard matching, anything-but wildcard matching, and anything-but prefix matching. Amazon SNS is a fully managed pub/sub service that provides one-to-many message delivery to various endpoints, including AWS Lambda, Amazon SQS, Amazon Data Firehose, SMS via AWS End User Messaging, push notifications, and email. With this launch, topic subscribers can use these additional operators to define more flexible message filtering policies, ensuring they receive only relevant messages. This reduces the need for additional filtering logic in subscriber applications. Amazon SNS message filtering is available in all AWS commercial Regions and AWS GovCloud (US) Regions. To learn more, see Message Filtering in the Amazon SNS Developer Guide.  

Amazon ElastiCache now offers Extended Support for ElastiCache versions 4 and 5 for Redis OSS, allowing customers to maintain critical workloads on these versions for up to three years beyond the standard support end date. This new offering addresses the needs of customers who require additional time to plan and execute version upgrades due to application dependencies or large-scale deployment complexities.

Standard support for ElastiCache versions 4 and 5 for Redis OSS will end on January 31, 2026. After this date, clusters not upgraded to a supported version will be automatically enrolled in Extended Support. During the Extended Support period, Amazon ElastiCache will continue to provide critical security updates for Common Vulnerabilities and Exposures (CVEs) and critical defect fixes for these Redis OSS versions. Customers can upgrade using service update APIs or Modify APIs for their cache clusters and replication groups. We recommend upgrading to the latest ElastiCache for Valkey version, where customers can benefit from 20% lower price, improved performance. To get started and learn more about the benefits, see our blog.

Amazon ElastiCache Extended Support is available in all AWS Regions, including the AWS GovCloud (US) Regions and China Regions. The start date for Extended Support charges will not be earlier than February 1, 2026. Learn more about Extended Support, including supported engine versions, in the Amazon ElastiCache user guide. Learn more about pricing details and timelines for Amazon ElastiCache Extended Support at Amazon ElastiCache Pricing.

 

​Amazon ElastiCache now offers Extended Support for ElastiCache versions 4 and 5 for Redis OSS, allowing customers to maintain critical workloads on these versions for up to three years beyond the standard support end date. This new offering addresses the needs of customers who require additional time to plan and execute version upgrades due to application dependencies or large-scale deployment complexities. Standard support for ElastiCache versions 4 and 5 for Redis OSS will end on January 31, 2026. After this date, clusters not upgraded to a supported version will be automatically enrolled in Extended Support. During the Extended Support period, Amazon ElastiCache will continue to provide critical security updates for Common Vulnerabilities and Exposures (CVEs) and critical defect fixes for these Redis OSS versions. Customers can upgrade using service update APIs or Modify APIs for their cache clusters and replication groups. We recommend upgrading to the latest ElastiCache for Valkey version, where customers can benefit from 20% lower price, improved performance. To get started and learn more about the benefits, see our blog. Amazon ElastiCache Extended Support is available in all AWS Regions, including the AWS GovCloud (US) Regions and China Regions. The start date for Extended Support charges will not be earlier than February 1, 2026. Learn more about Extended Support, including supported engine versions, in the Amazon ElastiCache user guide. Learn more about pricing details and timelines for Amazon ElastiCache Extended Support at Amazon ElastiCache Pricing.  

As of today, AWS Batch now supports scheduling for SageMaker Training jobs. With AWS Batch for SageMaker Training jobs, data scientists are able to submit training jobs to configurable queues powered by AWS Batch. This integration enables jobs to be scheduled based on priority and resource availability, eliminating manual retries and coordination. Additionally, system administrators can set up fair-share scheduling policies to optimize resource utilization across teams. The system will automatically retry failed jobs and provide visibility into queue status.

You can also procure SageMaker Flexible Training Plans (FTP) to guarantee the capacity you need during the time you need it. With a Flexible Training Plan in place, Batch’s queuing capabilities allows you to maximize your utilization for the duration of your plan. Data scientists can submit experiments with confidence directly from the SageMaker Python SDK, knowing that infrastructure complexities are handled automatically.

You can start using AWS Batch for SageMaker Training jobs immediately through the AWS Management Console, AWS Command Line Interface (CLI), or AWS SDKs. There are no additional charges for AWS Batch itself – you only pay for the AWS resources used to run your applications. AWS Batch for SageMaker Training jobs is now generally available in all commercial AWS Regions where AWS Batch and SageMaker AI are available. To get started, see the AWS Batch for SageMaker Training jobs documentation and our blog post.

 

​As of today, AWS Batch now supports scheduling for SageMaker Training jobs. With AWS Batch for SageMaker Training jobs, data scientists are able to submit training jobs to configurable queues powered by AWS Batch. This integration enables jobs to be scheduled based on priority and resource availability, eliminating manual retries and coordination. Additionally, system administrators can set up fair-share scheduling policies to optimize resource utilization across teams. The system will automatically retry failed jobs and provide visibility into queue status. You can also procure SageMaker Flexible Training Plans (FTP) to guarantee the capacity you need during the time you need it. With a Flexible Training Plan in place, Batch’s queuing capabilities allows you to maximize your utilization for the duration of your plan. Data scientists can submit experiments with confidence directly from the SageMaker Python SDK, knowing that infrastructure complexities are handled automatically. You can start using AWS Batch for SageMaker Training jobs immediately through the AWS Management Console, AWS Command Line Interface (CLI), or AWS SDKs. There are no additional charges for AWS Batch itself – you only pay for the AWS resources used to run your applications. AWS Batch for SageMaker Training jobs is now generally available in all commercial AWS Regions where AWS Batch and SageMaker AI are available. To get started, see the AWS Batch for SageMaker Training jobs documentation and our blog post.  

Amazon Chime SDK now offers customers the option to use Internet Protocol version 6 (IPv6) addresses. Customers can use IPv6 to address new dual-stack API endpoints to invoke Amazon Chime SDK APIs.

The new dual-stack endpoints support both IPv4 and IPv6 clients, helping you transition from IPv4 to IPv6-based systems and applications at your own pace. This approach can help you work toward IPv6 compliance requirements while reducing the need for additional networking equipment to handle address translation between IPv4 and IPv6.

Dual-stack endpoints are available in all AWS Regions where Amazon Chime SDK is available, including AWS GovCloud (US). To learn more about Amazon Chime SDK, refer to the following resources:

• Amazon Chime SDK website
• Amazon Chime SDK endpoints
• Available regions in the Amazon Chime SDK Developer Guide

 

​Amazon Chime SDK now offers customers the option to use Internet Protocol version 6 (IPv6) addresses. Customers can use IPv6 to address new dual-stack API endpoints to invoke Amazon Chime SDK APIs. The new dual-stack endpoints support both IPv4 and IPv6 clients, helping you transition from IPv4 to IPv6-based systems and applications at your own pace. This approach can help you work toward IPv6 compliance requirements while reducing the need for additional networking equipment to handle address translation between IPv4 and IPv6. Dual-stack endpoints are available in all AWS Regions where Amazon Chime SDK is available, including AWS GovCloud (US). To learn more about Amazon Chime SDK, refer to the following resources:

Amazon Chime SDK website
Amazon Chime SDK endpoints
Available regions in the Amazon Chime SDK Developer Guide  

AWS Lambda response streaming now supports a default maximum response payload size of 200 MB, 10x higher than before. Lambda response streaming allows you to progressively stream response payloads back to clients, improving performance for latency sensitive workloads by reducing time to first byte (TTFB) performance.

Response streaming is ideal for use cases which are sensitive to end-user latency, including real-time AI chat or web or mobile applications where page load performance influences user experience. Previously, the default response payload limit for response streaming functions was 20 MB and if your response payload exceeded this limit, you needed to incur additional overhead by compressing the payload or using services like Amazon S3 as an intermediary step. The increased response payload limit allows you to process response payloads of up to 200 MB directly within Lambda, enabling use cases such as real-time processing of large datasets, image-heavy PDF files, or even music files.

Lambda response streaming supports Node.js managed runtimes as well as custom runtimes. The 200 MB response streaming payload limit is default in all AWS Regions where Lambda response streaming is supported.

To learn more about Lambda response streaming, please refer to Lambda documentation. 

 

​AWS Lambda response streaming now supports a default maximum response payload size of 200 MB, 10x higher than before. Lambda response streaming allows you to progressively stream response payloads back to clients, improving performance for latency sensitive workloads by reducing time to first byte (TTFB) performance. Response streaming is ideal for use cases which are sensitive to end-user latency, including real-time AI chat or web or mobile applications where page load performance influences user experience. Previously, the default response payload limit for response streaming functions was 20 MB and if your response payload exceeded this limit, you needed to incur additional overhead by compressing the payload or using services like Amazon S3 as an intermediary step. The increased response payload limit allows you to process response payloads of up to 200 MB directly within Lambda, enabling use cases such as real-time processing of large datasets, image-heavy PDF files, or even music files. Lambda response streaming supports Node.js managed runtimes as well as custom runtimes. The 200 MB response streaming payload limit is default in all AWS Regions where Lambda response streaming is supported. To learn more about Lambda response streaming, please refer to Lambda documentation.   

Amazon CloudWatch Database Insights expands the availability of its on-demand analysis experience to the RDS for Oracle database engine. This feature leverages machine learning models to help identify performance bottlenecks during the selected time period, and gives advice on what to do next.

This launch allows you to analyze database performance monitoring data for a time period of your choice. You can learn how the selected time period differs from normal, what went wrong, and get advice on corrective actions. Through simple-to-understand graphs and explanations, you can identify the chief contributors to performance issues. You will also get guidance on the next steps to act on these issues. This can reduce the mean-time-to-diagnosis for database performance issues from hours to minutes.

You can get started with this feature by enabling the Advanced mode of Database Insights on your RDS for Oracle databases using the RDS service console, AWS APIs, the AWS SDK, or AWS CloudFormation. Please refer to RDS documentation and Aurora documentation for information regarding the availability of this feature across different regions, engines and instance classes.

CloudWatch Database Insights delivers database health monitoring aggregated at the fleet level, as well as instance-level dashboards for detailed database and SQL query analysis. It is available in all AWS regions and offers vCPU-based pricing – see the pricing page for details. For further information, visit the Database Insights User Guide.

 

​Amazon CloudWatch Database Insights expands the availability of its on-demand analysis experience to the RDS for Oracle database engine. This feature leverages machine learning models to help identify performance bottlenecks during the selected time period, and gives advice on what to do next. This launch allows you to analyze database performance monitoring data for a time period of your choice. You can learn how the selected time period differs from normal, what went wrong, and get advice on corrective actions. Through simple-to-understand graphs and explanations, you can identify the chief contributors to performance issues. You will also get guidance on the next steps to act on these issues. This can reduce the mean-time-to-diagnosis for database performance issues from hours to minutes. You can get started with this feature by enabling the Advanced mode of Database Insights on your RDS for Oracle databases using the RDS service console, AWS APIs, the AWS SDK, or AWS CloudFormation. Please refer to RDS documentation and Aurora documentation for information regarding the availability of this feature across different regions, engines and instance classes. CloudWatch Database Insights delivers database health monitoring aggregated at the fleet level, as well as instance-level dashboards for detailed database and SQL query analysis. It is available in all AWS regions and offers vCPU-based pricing – see the pricing page for details. For further information, visit the Database Insights User Guide.  

Amazon Connect Cases now displays email content, including message body, images, and attachment details directly within the case activity feed, enabling case workers to understand email conversations more efficiently and resolve cases faster.

Amazon Connect Cases is available in the following AWS regions: US East (N. Virginia), US West (Oregon), Canada (Central), Europe (Frankfurt), Europe (London), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), and Africa (Cape Town) AWS regions. To learn more and get started, visit the Amazon Connect Cases webpage and documentation.

 

​Amazon Connect Cases now displays email content, including message body, images, and attachment details directly within the case activity feed, enabling case workers to understand email conversations more efficiently and resolve cases faster. Amazon Connect Cases is available in the following AWS regions: US East (N. Virginia), US West (Oregon), Canada (Central), Europe (Frankfurt), Europe (London), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), and Africa (Cape Town) AWS regions. To learn more and get started, visit the Amazon Connect Cases webpage and documentation.