10/29/2026, 12:00:00 AM ~ 10/30/2026, 12:00:00 AM (UTC)

Recent Announcements

Amazon RDS for Oracle and SQL Server now support storage autoscaling on additional storage volumes

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.\n 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 Aurora now supports post-quantum TLS key exchange

Starting today, Amazon Aurora PostgreSQL-Compatible Edition introduces support for post-quantum TLS (PQ-TLS) key exchange, providing you with post-quantum cryptography options for encrypting your data in transit.\n Amazon Aurora PostgreSQL versions 18 and higher support modification of the ssl_groups parameter. You can select cryptographic groups from the Amazon Aurora PostgreSQL allow list to align with your organization’s security standards.

Amazon Aurora is designed for high performance and availability at global scale with full PostgreSQL compatibility. It provides scale-to-zero serverless compute, Aurora Global Database for multi-Region resilience, Aurora I/O-Optimized for improved price performance on I/O-intensive workloads, and built-in security and continuous backups. To get started, take a look at our getting started page.

Amazon MSK Connect now supports updating connector plugins and worker configurations

Amazon MSK Connect (Amazon Managed Streaming for Apache Kafka Connect) now lets you update the custom plugin and worker configuration of an existing connector. This is useful when you need to update the custom plugin to run a new version of your connector code, for example one with updated dependencies. You can also update the worker configuration to change worker-level settings, such as switching key and value converters or tuning producer and consumer properties for throughput and latency.\n Amazon MSK Connect is a fully managed service that allows you to deploy, monitor, and scale Apache Kafka Connect connectors with Amazon MSK (Managed Streaming for Apache Kafka). Previously, updating a connector’s plugin or worker configuration meant deleting the connector and recreating it - a disruptive operation that added risk and operational overhead. With this launch, you can update a connector’s plugin and worker configuration in place. The connector keeps its committed offsets, so its tasks continue processing from where they left off once the update completes.

This capability is available at no additional cost in all AWS Regions where Amazon MSK Connect is supported. To learn more, visit Amazon MSK Connect developer guide.

AWS DataSync Enhanced mode now supports Amazon FSx for Windows File Server, FSx for NetApp ONTAP, and Red Hat OpenShift Virtualization

AWS DataSync Enhanced mode now supports Amazon FSx for Windows File Server and Amazon FSx for NetApp ONTAP as source or destination locations. You can now run Windows to Windows transfers, such as from an on-premises file server to FSx for Windows File Server. Additionally, Enhanced mode agents can now run on Red Hat OpenShift Virtualization version 4.20 or later.\n With this launch, you can use the same location options in Enhanced mode as in Basic mode. Enhanced mode processes data in parallel for higher performance, removes file count limitations, and provides detailed data transfer metrics. OpenShift Virtualization expands your agent deployment options alongside VMware ESXi, KVM, Microsoft Hyper-V, and Amazon EC2.

You can get started by choosing Enhanced mode when you create a task in the AWS DataSync console. These capabilities are available in all AWS Regions where DataSync Enhanced mode is supported. To learn more, visit the AWS DataSync documentation.

AWS Step Functions workflows now available as AI agent tools

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.\nAWS 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 additional Regions

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.\n 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.

ACM now supports ACME for public certificates in AWS GovCloud (US)

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

Amazon Managed Grafana now supports in-place upgrade to Grafana version 13.2

Amazon Managed Grafana now supports in-place upgrade from Grafana version 12.4 to 13.2. Upgrading to version 13.2 brings features launched as part of open-source Grafana versions 13.0 to 13.2. These include Git Sync for dashboards, dynamic dashboards, and PromQL query support in the Amazon CloudWatch data source plugin.\nWith Git Sync, you can treat dashboards as code by linking a workspace to a Git repository. Dashboard modifications can be tracked, reviewed, and reverted through version control. Dynamic dashboards bring a more adaptable approach to layout and paneling. You can construct responsive views driven by conditions that respond to the data and variables in scope. With Amazon CloudWatch data source plugin support for Prometheus Query Language, you can use PromQL to query metrics that CloudWatch takes in via its OpenTelemetry (OTLP) endpoint, in addition to the existing Metric Search and Metrics Insights query types. In-place upgrade to Grafana 13.2 is supported in all AWS regions where Amazon Managed Grafana is generally available. You can upgrade with just a few clicks from the AWS Console, AWS SDK or AWS CLI. For a complete list of new features, refer to Differences between Grafana versions in the Amazon Managed Grafana User Guide. For upgrade instructions, see Update your workspace version. To learn more about Amazon Managed Grafana features and its pricing, visit the product page and pricing page.

Amazon SageMaker AI now supports SOCI-indexed images to start training jobs in seconds

Today, Amazon SageMaker AI announces support for Seekable OCI (SOCI)-indexed container images for training and processing jobs, so your jobs start running your code sooner. SOCI-indexed images start Amazon SageMaker AI training containers in seconds, cutting GPU idle time during image pulls by up to 90%, with no impact on training performance. Before a training or processing job can run, SageMaker AI downloads its container image to the instance. For deep learning images, which routinely exceed 10 GB, that download adds minutes to the start of every job, and you pay for that time. Now, when your image includes a SOCI index, SageMaker AI lazy-loads the image, fetching only the files needed to start the container and streaming the rest in the background as your code runs.\n To use this feature, reference a SOCI-indexed image from a private Amazon ECR repository in your training or processing job. You can use a pre-indexed AWS Deep Learning Container by changing the image tag to its -soci variant, or add a SOCI index to your own image in Amazon ECR with open-source tools, without rebuilding the image. No changes to your job definition, entry point, or data channels are needed. SageMaker AI checks for an index automatically and images without an index download as before. If an index can’t be used, the job falls back to a standard download and continues running.

SOCI-indexed images for SageMaker AI training and processing jobs are available today in all AWS Regions where SageMaker AI is available, through the SageMaker AI APIs, CLIs, SDKs, and Console. To learn more, see the documentation for training jobs and processing jobs, or read the launch blog.

AWS Backup now supports cross-account management and cross-account backup in the AWS European Sovereign Cloud

AWS Backup now supports cross-account management, cross-account backup, and delegated administrators in the AWS European Sovereign Cloud (Germany) Region. These capabilities help you centrally manage, monitor, and copy backups across the accounts in your organization using AWS Organizations.\n With cross-account management, you can deploy organization-wide backup policies from your AWS Organizations management account or a delegated administrator account. You can also monitor backup, copy, and restore jobs across all of your organization accounts from one place. With cross-account backup, you can copy recovery points to a backup vault in another account in your organization, which adds protection against accidental or malicious deletion in the source account. You can also register a member account as a delegated administrator, so your teams can manage backups across your organization without needing access to your management account.

There is no additional charge to use these capabilities; standard AWS Backup pricing applies. To learn more, see the AWS Backup documentation at https://docs.aws.amazon.com/aws-backup/. To get started, visit the AWS Backup console at https://console.aws.amazon.com/backup.

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