Amazon RDS for SQL Server and Amazon RDS for Oracle now support RDS storage autoscaling on additional storage volumes. RDS storage autoscaling automatically scales storage capacity in response to growing database workloads, with zero downtime.

Additional storage volumes allow you to add up to three additional volumes to increase your storage capacity up to 256 TiB. Previously, you had to manually provision storage capacity on the additional storage volumes based on anticipated application capacity demands while autoscaling could be enabled on the primary storage volume. Under-provisioning could result in application downtime, and over-provisioning could result in under-utilized resources and higher costs. With RDS storage autoscaling, you simply set your desired maximum storage limit for each additional storage volume, and autoscaling takes care of the rest.

RDS storage autoscaling continuously monitors actual storage consumption, and scales capacity up automatically when actual utilization approaches provisioned storage capacity. Autoscaling works with new and existing database instances. Autoscaling has no additional charges and you only pay for the provisioned storage resources. You can enable it by using the AWS Management Console, AWS CLI, or Amazon RDS API.

RDS storage autoscaling for additional storage volumes is available for Amazon RDS for SQL Server and Amazon RDS for Oracle in all commercial AWS Regions and the AWS GovCloud (US) Regions. To learn more, please visit the Amazon RDS storage autoscaling documentation. 

 

​Amazon RDS for SQL Server and Amazon RDS for Oracle now support RDS storage autoscaling on additional storage volumes. RDS storage autoscaling automatically scales storage capacity in response to growing database workloads, with zero downtime.
Additional storage volumes allow you to add up to three additional volumes to increase your storage capacity up to 256 TiB. Previously, you had to manually provision storage capacity on the additional storage volumes based on anticipated application capacity demands while autoscaling could be enabled on the primary storage volume. Under-provisioning could result in application downtime, and over-provisioning could result in under-utilized resources and higher costs. With RDS storage autoscaling, you simply set your desired maximum storage limit for each additional storage volume, and autoscaling takes care of the rest.
RDS storage autoscaling continuously monitors actual storage consumption, and scales capacity up automatically when actual utilization approaches provisioned storage capacity. Autoscaling works with new and existing database instances. Autoscaling has no additional charges and you only pay for the provisioned storage resources. You can enable it by using the AWS Management Console, AWS CLI, or Amazon RDS API.
RDS storage autoscaling for additional storage volumes is available for Amazon RDS for SQL Server and Amazon RDS for Oracle in all commercial AWS Regions and the AWS GovCloud (US) Regions. To learn more, please visit the Amazon RDS storage autoscaling documentation.   

You can now use your AWS Step Functions workflows as tools for AI agents through Amazon Bedrock AgentCore Gateway. Your agent decides when to run a workflow and what input to pass, and Step Functions runs each step exactly as you defined it. Agents can use your existing Standard and Express workflows as tools.

AWS Step Functions is a visual workflow service capable of orchestrating over 220 AWS services to help customers build distributed applications at scale. AgentCore Gateway connects AI agents to tools through the Model Context Protocol (MCP). With this launch, your agents can run multi-step business processes in the same order every time. For example, a customer support agent can start your refund workflow, and Step Functions runs the eligibility check, manager approval, and credit steps, so every refund follows your policy. Agents can also look up workflow runs, so an operations agent can tell your on-call engineer which order runs failed overnight and where, letting them go straight to fixing the step that broke.

This capability is available in all AWS Regions where Amazon Bedrock AgentCore Gateway is available. You pay standard rates for Step Functions and AgentCore Gateway.

To get started, follow the tutorial in the Step Functions Developer Guide. For all supported operations and setup options, see Step Functions connector targets in the AgentCore Gateway documentation. If you build with an AI coding assistant such as Kiro, the Agent Toolkit for AWS gives it skills and guidance for building on AWS.

 

​You can now use your AWS Step Functions workflows as tools for AI agents through Amazon Bedrock AgentCore Gateway. Your agent decides when to run a workflow and what input to pass, and Step Functions runs each step exactly as you defined it. Agents can use your existing Standard and Express workflows as tools.
AWS Step Functions is a visual workflow service capable of orchestrating over 220 AWS services to help customers build distributed applications at scale. AgentCore Gateway connects AI agents to tools through the Model Context Protocol (MCP). With this launch, your agents can run multi-step business processes in the same order every time. For example, a customer support agent can start your refund workflow, and Step Functions runs the eligibility check, manager approval, and credit steps, so every refund follows your policy. Agents can also look up workflow runs, so an operations agent can tell your on-call engineer which order runs failed overnight and where, letting them go straight to fixing the step that broke.
This capability is available in all AWS Regions where Amazon Bedrock AgentCore Gateway is available. You pay standard rates for Step Functions and AgentCore Gateway.
To get started, follow the tutorial in the Step Functions Developer Guide. For all supported operations and setup options, see Step Functions connector targets in the AgentCore Gateway documentation. If you build with an AI coding assistant such as Kiro, the Agent Toolkit for AWS gives it skills and guidance for building on AWS.  

Amazon DynamoDB Accelerator (DAX) is now available in two additional AWS Regions: Canada (Central) and Africa (Cape Town). DAX is a fully managed, highly available, in-memory cache for Amazon DynamoDB that delivers up to ten times performance improvement, from single-digit milliseconds to microseconds, even at millions of requests per second.

With DAX, you can accelerate read-intensive and bursty workloads such as real-time bidding, gaming leaderboards, and retail product catalogs, while offloading read traffic from your DynamoDB tables. DAX is API-compatible with DynamoDB, so you can add microsecond-latency caching to your applications with minimal code changes. Customers can now keep cached data within the Region and meet low-latency requirements while benefiting from a fully managed service, including automated patching and failover.

To learn more, see the Amazon DynamoDB Accelerator page. For the full list of Regions where DAX is available, see the AWS Regional Services page.

 

​Amazon DynamoDB Accelerator (DAX) is now available in two additional AWS Regions: Canada (Central) and Africa (Cape Town). DAX is a fully managed, highly available, in-memory cache for Amazon DynamoDB that delivers up to ten times performance improvement, from single-digit milliseconds to microseconds, even at millions of requests per second.
With DAX, you can accelerate read-intensive and bursty workloads such as real-time bidding, gaming leaderboards, and retail product catalogs, while offloading read traffic from your DynamoDB tables. DAX is API-compatible with DynamoDB, so you can add microsecond-latency caching to your applications with minimal code changes. Customers can now keep cached data within the Region and meet low-latency requirements while benefiting from a fully managed service, including automated patching and failover.
To learn more, see the Amazon DynamoDB Accelerator page. For the full list of Regions where DAX is available, see the AWS Regional Services page.  

AWS Certificate Manager (ACM) ACME protocol support is now available in AWS GovCloud (US-East) and AWS GovCloud (US-West), providing a fully managed ACME server endpoint that issues public TLS certificates from Amazon Trust Services using any ACMEv2-compatible client, including Certbot, cert-manager for Kubernetes, and acme.sh. With the CA/Browser Forum mandating 47-day certificate lifetimes by 2029, manual management of public certificates becomes untenable. ACME support in ACM gives developers a standards-based path to fully automate certificate issuance and renewal.

To learn more, visit the AWS News blog post, the ACM ACME documentation, the ACM pricing page, and the AWS Regional Services page.

 

​AWS Certificate Manager (ACM) ACME protocol support is now available in AWS GovCloud (US-East) and AWS GovCloud (US-West), providing a fully managed ACME server endpoint that issues public TLS certificates from Amazon Trust Services using any ACMEv2-compatible client, including Certbot, cert-manager for Kubernetes, and acme.sh. With the CA/Browser Forum mandating 47-day certificate lifetimes by 2029, manual management of public certificates becomes untenable. ACME support in ACM gives developers a standards-based path to fully automate certificate issuance and renewal.
To learn more, visit the AWS News blog post, the ACM ACME documentation, the ACM pricing page, and the AWS Regional Services page.  

AWS announces the general availability of Amazon Bedrock AgentCore CLI version 1.0 (@aws/agentcore 1.0.0), rebuilt with faster startup, a consistent command structure, and support for more AgentCore resources. The CLI helps developers create, develop, deploy, and operate AI agents and supporting resources from the terminal.

With version 1.0, developers can use the project workflow or work directly with harnesses, runtimes, memory, identity, gateways, and payments without first adding them to a project. Developers can invoke existing resources by ID or ARN, open an interactive shell, export a harness, and use searchable menus, resource pickers, and guided workflows. Consistent global flags provide region selection, JSON output, debugging, and version information across commands.

Existing projects can be migrated to AgentCore version 1 using the agentcore migrate command.

Install AgentCore CLI version 1.0 from npm or explore the source on GitHub. To learn more, visit the Amazon Bedrock AgentCore product page, AgentCore CLI reference, and Get started with Amazon Bedrock AgentCore.

 

​AWS announces the general availability of Amazon Bedrock AgentCore CLI version 1.0 (@aws/agentcore 1.0.0), rebuilt with faster startup, a consistent command structure, and support for more AgentCore resources. The CLI helps developers create, develop, deploy, and operate AI agents and supporting resources from the terminal.
With version 1.0, developers can use the project workflow or work directly with harnesses, runtimes, memory, identity, gateways, and payments without first adding them to a project. Developers can invoke existing resources by ID or ARN, open an interactive shell, export a harness, and use searchable menus, resource pickers, and guided workflows. Consistent global flags provide region selection, JSON output, debugging, and version information across commands.
Existing projects can be migrated to AgentCore version 1 using the agentcore migrate command.
Install AgentCore CLI version 1.0 from npm or explore the source on GitHub. To learn more, visit the Amazon Bedrock AgentCore product page, AgentCore CLI reference, and Get started with Amazon Bedrock AgentCore.  

Amazon Relational Database Service (Amazon RDS) for Oracle now supports the September 2026 Monthly Recommended Patch (MRP) for Oracle Database version 19c and 26ai. An MRP is a minor engine version that builds on a quarterly Release Update (RU), bundling Oracle’s Critical Security Patch Update (CSPU) with additional Oracle-recommended fixes. The September 2026 MRP is applied on top of the July 2026 RU and includes the Oracle September CSPU. We recommend upgrading to the September 2026 MRP as it includes the latest security updates for Oracle Database.

This release also includes the updated Oracle time zone file (DST version 46), which reflects the latest daylight saving time rule changes in several regions, including British Columbia and Alberta in Canada (effective November 1, 2026) and Morocco and Western Sahara (effective September 20, 2026), which are moving to permanent UTC offsets. If you store timestamps that include time zone information for these areas, the updated time zone file keeps that data aligned with the new rules.

You can apply the September 2026 MRP for new database instances, or upgrade existing instances to engine version 19.0.0.0.ru-2026-07.mrp-2026-09.r2 or 26.0.0.0.ru-2026-07.mrp-2026-09.r2 from the Amazon RDS Management Console, or by using the AWS SDK or CLI. To learn more about Oracle MRPs supported on Amazon RDS for each engine version, see the Amazon RDS for Oracle Release notes.

 

​Amazon Relational Database Service (Amazon RDS) for Oracle now supports the September 2026 Monthly Recommended Patch (MRP) for Oracle Database version 19c and 26ai. An MRP is a minor engine version that builds on a quarterly Release Update (RU), bundling Oracle’s Critical Security Patch Update (CSPU) with additional Oracle-recommended fixes. The September 2026 MRP is applied on top of the July 2026 RU and includes the Oracle September CSPU. We recommend upgrading to the September 2026 MRP as it includes the latest security updates for Oracle Database.
This release also includes the updated Oracle time zone file (DST version 46), which reflects the latest daylight saving time rule changes in several regions, including British Columbia and Alberta in Canada (effective November 1, 2026) and Morocco and Western Sahara (effective September 20, 2026), which are moving to permanent UTC offsets. If you store timestamps that include time zone information for these areas, the updated time zone file keeps that data aligned with the new rules.
You can apply the September 2026 MRP for new database instances, or upgrade existing instances to engine version 19.0.0.0.ru-2026-07.mrp-2026-09.r2 or 26.0.0.0.ru-2026-07.mrp-2026-09.r2 from the Amazon RDS Management Console, or by using the AWS SDK or CLI. To learn more about Oracle MRPs supported on Amazon RDS for each engine version, see the Amazon RDS for Oracle Release notes.  

Today, we’re announcing support for time series collections on the next generation of Amazon OpenSearch Serverless. With time series collections, you can ingest, store, and analyze logs, metrics, traces, and event data without provisioning or managing clusters. They absorb ingest spikes automatically, keep recent data fast to query, and make months or years of history searchable at low cost, all in the same collection.

Time series collections add a new, lower-cost warm storage tier in addition to the existing hot storage tier, so customers can retain their infrequently accessed data without paying hot storage prices. Customers can choose how long data stays hot before transitiong to warm storage.  With up to 100 TB of hot storage per collection, time series collections can handle high-volume observability workloads such as application monitoring, security analytics, and IoT telemetry. Alerting and anomaly detection are also now available, so customers can get notified about issues and spot unusual patterns in their log and event data without separate tooling.

Time series collections are available today in all AWS Regions where OpenSearch Serverless is available. To learn more about the pricing for the new warm storage,  see OpenSearch Serverless pricing. To learn more about time series collections on Amazon OpenSearch Serverless, see the OpenSearch Serverless feature page, the launch blog, and the AWS documentation.

 

​Today, we’re announcing support for time series collections on the next generation of Amazon OpenSearch Serverless. With time series collections, you can ingest, store, and analyze logs, metrics, traces, and event data without provisioning or managing clusters. They absorb ingest spikes automatically, keep recent data fast to query, and make months or years of history searchable at low cost, all in the same collection.
Time series collections add a new, lower-cost warm storage tier in addition to the existing hot storage tier, so customers can retain their infrequently accessed data without paying hot storage prices. Customers can choose how long data stays hot before transitiong to warm storage.  With up to 100 TB of hot storage per collection, time series collections can handle high-volume observability workloads such as application monitoring, security analytics, and IoT telemetry. Alerting and anomaly detection are also now available, so customers can get notified about issues and spot unusual patterns in their log and event data without separate tooling.
Time series collections are available today in all AWS Regions where OpenSearch Serverless is available. To learn more about the pricing for the new warm storage,  see OpenSearch Serverless pricing. To learn more about time series collections on Amazon OpenSearch Serverless, see the OpenSearch Serverless feature page, the launch blog, and the AWS documentation.  

Amazon Quick now supports smart approvals, a review layer that reduces unnecessary approval prompts while preserving human oversight of the actions that matter most. As agents take more actions on a user’s behalf, such as sending email, updating records, and creating tickets, asking a person to approve every step leads to approval fatigue and weaker oversight over time. With smart approvals, a separate review model called the classifier evaluates each eligible action against the user’s request. It approves routine actions automatically and refers consequential actions to the user for review.

Your existing policies always come first. Smart approvals only reviews actions where the user’s setting is «ask» each time. Denied actions stay denied, and smart approvals never grants new access. The classifier sends higher-impact actions to the user for review. These include sending content outside the organization, changing permissions, deleting content, making payments, and actions that go beyond what the user asked for. Each automatic approval covers only the exact action that was reviewed. If a review fails or times out, the action goes to the user.

Smart approvals is on for all users by default. Administrators control who can use it with custom permissions, and users can turn it off for their conversations and scheduled runs in chat options. AWS CloudTrail records each action review made through smart approvals and each change to a user’s smart approvals setting.

Smart approvals is available in Amazon Quick in all AWS Regions where Amazon Quick agentic capabilities are supported. For more information, see the AWS Region table.

To learn more about smart approvals, see smart approvals in the Amazon Quick User Guide. For more information about Amazon Quick, see the Amazon Quick product page.

 

​Amazon Quick now supports smart approvals, a review layer that reduces unnecessary approval prompts while preserving human oversight of the actions that matter most. As agents take more actions on a user’s behalf, such as sending email, updating records, and creating tickets, asking a person to approve every step leads to approval fatigue and weaker oversight over time. With smart approvals, a separate review model called the classifier evaluates each eligible action against the user’s request. It approves routine actions automatically and refers consequential actions to the user for review.
Your existing policies always come first. Smart approvals only reviews actions where the user’s setting is «ask» each time. Denied actions stay denied, and smart approvals never grants new access. The classifier sends higher-impact actions to the user for review. These include sending content outside the organization, changing permissions, deleting content, making payments, and actions that go beyond what the user asked for. Each automatic approval covers only the exact action that was reviewed. If a review fails or times out, the action goes to the user.
Smart approvals is on for all users by default. Administrators control who can use it with custom permissions, and users can turn it off for their conversations and scheduled runs in chat options. AWS CloudTrail records each action review made through smart approvals and each change to a user’s smart approvals setting.
Smart approvals is available in Amazon Quick in all AWS Regions where Amazon Quick agentic capabilities are supported. For more information, see the AWS Region table.
To learn more about smart approvals, see smart approvals in the Amazon Quick User Guide. For more information about Amazon Quick, see the Amazon Quick product page.  

Today, Amazon Elastic Kubernetes Service (Amazon EKS) announces certificate authority (CA) rotation visibility in the Amazon EKS Dashboard, giving you a consolidated view of CA rotation across your clusters. The Amazon EKS Dashboard already provides centralized visibility into your clusters across AWS Regions and accounts, and it now includes CA rotation, so you can see where action is needed without checking each cluster individually.

Each Amazon EKS cluster has its own CA, and clusters created since 2018 have CAs with a 10-year validity period that are now approaching the point where rotation activities should begin. In the EKS Dashboard, you can now see your clusters and their CA rotation status, which clusters have CAs approaching expiration, and upcoming automated rotation events, so platform teams who operate many clusters can prioritize action across their fleet from one place.

The Amazon EKS Dashboard aggregates data across your accounts and Regions through AWS Organizations, so you enable trusted access for the dashboard in your organization’s management account to use this capability. You view the dashboard from the US East region (us-east-1), and it is available at no additional cost. CA rotation support extends to all commercial AWS Regions, and the dashboard brings that rotation status together in one fleet-wide view. To learn more, see the Amazon EKS documentation.

 

​Today, Amazon Elastic Kubernetes Service (Amazon EKS) announces certificate authority (CA) rotation visibility in the Amazon EKS Dashboard, giving you a consolidated view of CA rotation across your clusters. The Amazon EKS Dashboard already provides centralized visibility into your clusters across AWS Regions and accounts, and it now includes CA rotation, so you can see where action is needed without checking each cluster individually.
Each Amazon EKS cluster has its own CA, and clusters created since 2018 have CAs with a 10-year validity period that are now approaching the point where rotation activities should begin. In the EKS Dashboard, you can now see your clusters and their CA rotation status, which clusters have CAs approaching expiration, and upcoming automated rotation events, so platform teams who operate many clusters can prioritize action across their fleet from one place.
The Amazon EKS Dashboard aggregates data across your accounts and Regions through AWS Organizations, so you enable trusted access for the dashboard in your organization’s management account to use this capability. You view the dashboard from the US East region (us-east-1), and it is available at no additional cost. CA rotation support extends to all commercial AWS Regions, and the dashboard brings that rotation status together in one fleet-wide view. To learn more, see the Amazon EKS documentation.  

Today, Amazon Elastic Container Service (Amazon ECS) Managed Instances introduces two infrastructure optimization updates: cross-instance and Spot consolidation. Cross-instance consolidation evaluates tasks running across multiple underutilized instances together, packing them onto fewer instances to raise utilization and lower costs. Spot consolidation extends this capability to Spot capacity, consolidating underutilized Spot Instances after first verifying replacement capacity is available.

Amazon ECS Managed Instances provisions, configures, and operates right-sized Amazon EC2 instances for your workloads, balancing availability and cost. Its infrastructure optimization continuously monitors your fleet, reclaiming idle capacity and consolidating underutilized instances with graceful start-before-stop task replacement. Until now, optimization evaluated each instance in isolation for replacement, which worked well when a capacity provider was configured with diverse instance types. However, when a capacity provider was configured with a narrow range of instance types, there were fewer opportunities to consolidate multiple underutilized instances, because no single replacement could yield savings. With cross-instance consolidation, ECS now evaluates and repacks tasks across multiple instances simultaneously. For example, in our testing with a capacity provider configured for c9g instances with a minimum size of 4xlarge, running 261 tasks (each 1 vCPU, 1.94 GiB), cross-instance consolidation reduced the fleet from 19 instances (seven 4xlarge, seven 8xlarge, four 12xlarge, and one 24xlarge) to 13 instances (eight 4xlarge and five 8xlarge), while raising CPU utilization from 42% to 91% and memory utilization from 41% to 88%. Spot consolidation applies the same approach to Spot capacity, first verifying replacement capacity is available. With these enhancements, ECS Managed Instances delivers deeper cost optimization for both your On-Demand and Spot workloads.

Cross-instance and Spot consolidation are now available at no additional cost in all AWS Regions, and apply automatically to all existing and new ECS Managed Instances capacity providers. To learn more, see our documentation.

 

​Today, Amazon Elastic Container Service (Amazon ECS) Managed Instances introduces two infrastructure optimization updates: cross-instance and Spot consolidation. Cross-instance consolidation evaluates tasks running across multiple underutilized instances together, packing them onto fewer instances to raise utilization and lower costs. Spot consolidation extends this capability to Spot capacity, consolidating underutilized Spot Instances after first verifying replacement capacity is available.
Amazon ECS Managed Instances provisions, configures, and operates right-sized Amazon EC2 instances for your workloads, balancing availability and cost. Its infrastructure optimization continuously monitors your fleet, reclaiming idle capacity and consolidating underutilized instances with graceful start-before-stop task replacement. Until now, optimization evaluated each instance in isolation for replacement, which worked well when a capacity provider was configured with diverse instance types. However, when a capacity provider was configured with a narrow range of instance types, there were fewer opportunities to consolidate multiple underutilized instances, because no single replacement could yield savings. With cross-instance consolidation, ECS now evaluates and repacks tasks across multiple instances simultaneously. For example, in our testing with a capacity provider configured for c9g instances with a minimum size of 4xlarge, running 261 tasks (each 1 vCPU, 1.94 GiB), cross-instance consolidation reduced the fleet from 19 instances (seven 4xlarge, seven 8xlarge, four 12xlarge, and one 24xlarge) to 13 instances (eight 4xlarge and five 8xlarge), while raising CPU utilization from 42% to 91% and memory utilization from 41% to 88%. Spot consolidation applies the same approach to Spot capacity, first verifying replacement capacity is available. With these enhancements, ECS Managed Instances delivers deeper cost optimization for both your On-Demand and Spot workloads.
Cross-instance and Spot consolidation are now available at no additional cost in all AWS Regions, and apply automatically to all existing and new ECS Managed Instances capacity providers. To learn more, see our documentation.