6/8/2026, 12:00:00 AM ~ 6/9/2026, 12:00:00 AM (UTC)

Recent Announcements

AWS Compute Optimizer now supports idle recommendations for six additional resource types

AWS Compute Optimizer now identifies idle resources for Amazon DynamoDB provisioned tables, Amazon ElastiCache (Redis and Valkey), Amazon MemoryDB, Amazon DocumentDB (provisioned and serverless), Amazon WorkSpaces, and Amazon SageMaker endpoints. This expansion enables you to detect unused resources across more of your AWS environment and identify potential cost savings.\n Compute Optimizer analyzes utilization metrics to determine whether a resource is idle. Customers can set this lookback period based on the nature of their workloads. For each resource type, Compute Optimizer evaluates service-specific signals such as consumed capacity, cache hits, active connections, and CPU utilization. When Compute Optimizer identifies potential idle resources, it surfaces these recommendations, along with detailed utilization metrics and estimated savings in the console, enabling you to evaluate recommendations before acting. You can also view idle resource recommendations across all AWS accounts in your organization through the Cost Optimization Hub, with de-duplicated estimated savings with other recommendations on the same resources.

For more information about the AWS Regions where Compute Optimizer is available, see the AWS Region table. For more information about AWS Compute Optimizer, visit our product page and documentation. You can start using AWS Compute Optimizer through the AWS Management Console, AWS CLI, and AWS SDK.

Amazon MSK Express Brokers now support automatic topic creation with Kafka Streams

Effective today, Amazon MSK Express Brokers support automatic topic creation with Kafka Streams. Customers can now deploy their Kafka Streams applications on Express Brokers without needing to manually pre-create or manage topics for stateful operations.\n 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. Kafka Streams uses topics to store state and repartition data for stateful operations. Previously, customers running Kafka Streams with Express Brokers had to manually name and pre-create these topics before deploying their application. With this launch, these topics are created automatically when the application starts, simplifying deployment and reducing operational setup for Kafka Streams applications on Express Brokers. This capability is available today in all AWS regions where MSK Express Brokers are available. No additional configuration or setup is required to get started. To learn more, see Amazon MSK Developer Guide.

Amazon DocumentDB now supports engine minor version starting with 5.0.1

Amazon DocumentDB (with MongoDB compatibility) now supports engine minor versions, starting with 5.0.1. This release delivers enhanced aggregation capabilities with new operators ($rand, $pow, $dateToParts, $dateFromParts), the active connections metric to monitor instances, and granular command-level performance metrics in CloudWatch (find, insert, findAndModify, update, etc.). For a full list of what’s included, see release notes. Minor versions provide new features and bug fixes within the same major version, giving you more control over when and how you upgrade your clusters. We recommend upgrading to the latest minor version to benefit from these performance enhancements, bug fixes, and new capabilities.\n You can specify minor version 5.0.1 when creating a new cluster, or manually upgrade an existing 5.0.0 cluster to 5.0.1 using the AWS Management Console or AWS CLI (via the modify-db-cluster command with –engine-version 5.0.1). Once you upgrade to a newer minor version, you cannot downgrade back to a previous minor version. Upgrading from 5.0.0 (LTS) to 5.0.1 gives you access to the latest features and fixes, but you will no longer be on the LTS track. If minimizing upgrades is your priority, you should remain on LTS. For more information, see Using a long-term support (LTS) release. Amazon DocumentDB engine minor version 5.0.1 is available in all AWS Regions where Amazon DocumentDB 5.0 is available. Learn more about minor version upgrades and version support dates in the Amazon DocumentDB Developer Guide. Create or update a fully managed Amazon DocumentDB cluster in the Amazon DocumentDB Management Console.

AWS Savings Plans Purchase Analyzer now supports target coverage analysis

Today, AWS announces target coverage analysis in Savings Plans Purchase Analyzer, a capability in AWS Billing and Cost Management that helps you plan your Savings Plans purchases based on your coverage target. Savings Plans Purchase Analyzer helps you evaluate different purchase scenarios by estimating the potential impact of Savings Plans purchases on cost, coverage, utilization, and savings.\n With target coverage analysis, you can set a specific percentage of On-Demand spend to be covered by Savings Plans. Savings Plans Purchase Analyzer uses your historical usage to recommend a new purchase amount to help you reach that target. You can further customize your analysis using parameters such as custom lookback period or excluding expiring Savings Plans, and compare cost, coverage, utilization, and savings across different coverage targets. You can view your recommendations through interactive charts or access your target coverage analysis via the Purchase Analyzer API. Target coverage analysis is available in all AWS Regions where Savings Plans Purchase Analyzer is available. To learn more, visit the AWS Savings Plans page and user guide.

PostgreSQL 19 Beta 1 is now available in Amazon RDS Database Preview Environment

Amazon RDS for PostgreSQL 19 Beta 1 is now available in the Amazon RDS Database Preview Environment, allowing you to evaluate the pre-release of PostgreSQL 19 on Amazon RDS for PostgreSQL. You can deploy PostgreSQL 19 Beta 1 in the Amazon RDS Database Preview Environment that has the benefits of a fully managed database.\n PostgreSQL 19 adds native graph query support via SQL Property Graph Queries (SQL/PGQ), so you can express complex relationship traversals directly in standard SQL instead of building separate application logic or syncing data across two databases. It also introduces support for concurrent table repacking that rebuilds tables and reclaims unused storage, so production databases stay accessible during routine table maintenance. Logical replication now synchronizes sequence values to the replica automatically, eliminating manual sequence reconciliation after major version upgrade cutover. Logical replication can also be enabled dynamically without a server restart, reducing planned downtime. Please refer to PostgreSQL community announcement for more details. Amazon RDS Database Preview Environment database instances are retained for a maximum period of 60 days and are automatically deleted after the retention period. Amazon RDS database snapshots that are created in the preview environment can only be used to create or restore database instances within the preview environment. You can use the PostgreSQL dump and load functionality to import or export your databases from the preview environment. Amazon RDS Database Preview Environment database instances are priced as per the pricing in the US East (Ohio) Region.

AWS Application Migration Service is now AWS Transform MGN

AWS Application Migration Service (MGN) is now available as AWS Transform MGN. This name change reflects MGN’s role as the proven replication engine powering AWS Transform, the agentic migration service.\n You can choose between two rehosting experiences. Use the AWS Transform MGN console for direct control over replication and cutover. Or use the AWS Transform agentic workflow, where an agent handles discovery, wave planning, landing zone setup, network creation, and rehosting or containerization on your behalf, accelerating your path to AWS. AWS Transform MGN retains all of its existing compliance certifications, including FedRAMP High, HIPAA, PCI DSS, ISO, and SOC 1, 2, and 3, so you can migrate with confidence. It is available in all commercial regions and both GovCloud (US) Regions. Visit the AWS Transform MGN product page and AWS Transform MGN documentation for more information on how to rehost applications to AWS.

Amazon Aurora DSQL now supports the JSONB data type with compression

Amazon Aurora DSQL introduces support for the PostgreSQL JSONB data type with optional compression. You can now use code and tools that depend on PostgreSQL’s JSONB type with Aurora DSQL, making it easier to store semi-structured data alongside relational data.\n You can use the JSONB data type when creating or modifying tables to store semi-structured data such as system configuration metadata, API parameters, and event logs. With PostgreSQL compression enabled by default, larger JSONB payloads are stored more efficiently, helping reduce storage costs. Get started with Aurora DSQL for free with the AWS Free Tier. For information about Regional availability, see the AWS Region table. You can learn more about Aurora DSQL data types, including JSONB, here.

AWS Lambda Managed Instances expands to additional AWS Regions

AWS Lambda Managed Instances (LMI) is now available in all commercial AWS Regions, except Israel (Tel Aviv), Middle East (Bahrain), Middle East (UAE), and Asia Pacific (Auckland).  \n LMI lets you run Lambda functions on managed Amazon EC2 instances, giving you access to specialized compute configurations and EC2 pricing advantages while maintaining Lambda’s operational simplicity. LMI fully manages instance lifecycle, OS and runtime patching, routing, load balancing, and auto-scaling, so you can focus on writing code. You can process parallel requests within each execution environment, maximizing resource utilization and improving price-performance. You can further improve costs by leveraging EC2 pricing models including Compute Savings Plans and Reserved Instances. LMI is ideal for customers requiring specialized hardware configurations, as well as those with steady-state or predictable workloads seeking to optimize costs.

You can continue building functions with familiar development workflows, including the Console and your preferred IDEs. To get started, create a capacity provider that defines your compute preferences, including VPC configuration, optional instance requirements, and scaling policies. Then, attach your Lambda functions to the capacity provider via the AWS Lambda Console, APIs, or Infrastructure as Code tooling. LMI integrates seamlessly with all Lambda event sources and tools like Amazon CloudWatch, AWS X-Ray, and AWS Config. To learn more, visit AWS Lambda pricing, AWS Lambda Managed Instances documentation, and blog.

AWS now provides AI-powered cost investigations for cost anomalies

AWS Cost Anomaly Detection now includes AI-powered cost investigation, which uses Amazon Q to analyze the root cause of detected cost anomalies. Investigating a cost change typically requires correlating cost data with AWS CloudTrail events and resource activity, which can take hours. Cost investigation delivers a plain-language explanation in minutes, helping FinOps practitioners and engineering teams move from alert to action faster.\n When you investigate an anomaly, Amazon Q determines whether the cost change is usage-driven or rate-driven, identifies the contributing services, accounts, and regions, and for usage-driven changes, correlates with AWS CloudTrail to attribute the change to specific API calls and IAM principals. For organizations with a CloudTrail organization trail, the investigation works across all member accounts automatically. You can continue the conversation with follow-up questions to explore patterns or drill into specific resources. 

AI-powered cost investigation is available today in all commercial AWS Regions at no additional charge. Cross-account investigations that use an organization-wide CloudTrail trail delivered to Amazon CloudWatch Logs might incur standard CloudWatch Logs Insights charges based on data scanned.

To get started, navigate to AWS Cost Anomaly Detection in the AWS Billing and Cost Management console and choose Investigate with Amazon Q on any detected anomaly. To learn more, see Investigating anomaly root causes with Amazon Q in the AWS Billing and Cost Management User Guide.

Amazon Connect Customer now offers AI agent trace details for self-service voice interactions

Amazon Connect Customer now provides AI agent traces for self-service voice interactions, enabling you to understand how AI agents reason, act, and respond during each customer conversation. With this launch, you have full visibility into how the AI agent handled an interaction, so you can confirm what worked, diagnose issues, validate behavior, and deploy agentic experiences with confidence.\n For example, if your AI agent fails to resolve a customer request, you can access the step-by-step trace directly in the Connect web UI alongside the full transcript, and see whether it reasoned incorrectly, called a tool with bad parameters, or timed out waiting for a response.

This feature is available in all AWS Regions where Amazon Connect Customer AI Agents are supported. For more information, see the Amazon Connect Customer Administrator Guide. To learn more about Amazon Connect Customer, an agentic AI solution that helps enterprises deliver exceptional customer experiences, visit the Amazon Connect Customer website.

Amazon Redshift reduces manual snapshot cost for Serverless and RG instances

Amazon Redshift announces a new billing model for manual snapshots on Amazon Redshift Serverless and Amazon Redshift RG instances. With this enhancement, Amazon Redshift now meters manual snapshot storage based on the unique data blocks stored across your snapshots rather than the total size of each individual snapshot. This results in lower manual snapshot costs for customers who maintain multiple snapshots.\n Customers who maintain multiple manual snapshots for disaster recovery, testing, or long-term retention will see reduced storage costs. With this new billing model, you can take more frequent manual snapshots to achieve a better recovery point objective (RPO) without proportional cost increases, enabling more robust disaster recovery strategies. The new billing model automatically applies to both existing and new manual snapshots. The new manual snapshot billing model is available in all AWS commercial and AWS GovCloud (US) Regions where Amazon Redshift Serverless and Amazon Redshift RG instances are available. To learn more about Amazon Redshift snapshots, please visit our documentation or the blog.

Amazon RDS for SQL Server migration cost assessment capabilities now available in AWS Transform

Amazon RDS for SQL Server now offers TCO assessment in AWS Transform, so you can estimate costs when migrating on-premises SQL Server databases to RDS for SQL Server. Using AI-powered agents, AWS Transform analyzes your on-premises SQL Server environment and provides optimal database instance recommendations that meet your workload requirements and reduce cost. With AI-powered what-if analysis, you can evaluate different options, compare costs, and choose the best option for your migration.\n RDS for SQL Server assessment within AWS Transform supports both Bring Your Own Media (BYOM), which allows you to use your existing SQL Server licenses, and License Included (LI) options. The assessments include cost optimization using Database Savings Plans, which offer up to 20% savings compared to On-Demand pricing, and eligibility for the AWS Migration Acceleration Program (MAP), which provides credits and support to offset migration costs. You can start your assessment with any data format you have, including RVTools exports, Configuration management database exports (CMDB) data, exports from the AWS Transform discovery tool, and other third-party discovery tools. Create what-if scenarios to compare multiple cost models with customized assumptions including region, resource utilization, and pricing terms. RDS for SQL Server joins the existing migration assessment capabilities in AWS Transform, so you can combine it with cost modeling of Amazon EC2, Amazon FSx, Amazon S3, SQL Server on EC2, and virtual desktops in what-if scenarios. You can also enhance your assessment with additional pillars of the Cloud Value Proposition such as staff productivity, operational resilience, business agility, and sustainability. To get started, sign in to the AWS Transform console and select Migration Assessment. AWS Transform migration assessments are available in all AWS Regions where AWS Transform is offered.

AWS Blogs

AWS Japan Blog (Japanese)

AWS Japan Startup Blog (Japanese)

AWS News Blog

AWS Big Data Blog

AWS Compute Blog

AWS Database Blog

AWS HPC Blog

Artificial Intelligence

AWS Security Blog

AWS Storage Blog

Open Source Project

AWS CLI

Amplify UI