1/15/2026, 12:00:00 AM ~ 1/16/2026, 12:00:00 AM (UTC)

Recent Announcements

Amazon S3 on Outposts is now available on second-generation AWS Outposts racks

Amazon S3 on Outposts is now available on second-generation AWS Outposts racks for your data residency, low latency, and local data processing use cases on-premises. S3 on Outposts on second-generation Outposts racks offers three storage tiers: 196 TB, 490 TB, and 786 TB. Choose the storage tier that matches your workload, whether for production workloads, backups, or archival workloads.\n With S3 on Outposts, you can store, secure, retrieve, and control access to your data using familiar S3 APIs and features. AWS Outposts is a fully managed service that extends AWS infrastructure, services, and tools to virtually any data center, co-location space, or on-premises facility for a consistent hybrid experience. S3 on Outposts on second-generation Outposts racks is available in all AWS Regions and countries/territories where these racks are available. To learn more, visit the S3 on Outposts page or read our documentation.

AWS Clean Rooms now supports parameters in PySpark analysis templates

AWS Clean Rooms announces support for parameters in PySpark analysis templates, offering increased flexibility for organizations and their partners to scale their privacy-enhanced data collaboration use cases. With this launch, you can create a single PySpark analysis template that allows different values to be provided by the Clean Rooms collaborator running a job at submission time without modifying the template code. With parameters in PySpark analysis templates, the code author creates a PySpark template with parameters support, and if approved to run, the job runner submits parameter values directly to the PySpark job. For example, a measurement company running attribution analysis for advertising campaigns can input time windows and geographic regions dynamically to surface insights that drive campaign optimizations and media planning accelerating time-to-insights.\n

With AWS Clean Rooms, customers can create a secure data clean room in minutes and collaborate with any company on AWS or Snowflake to generate unique insights about advertising campaigns, investment decisions, and research and development. For more information about the AWS Regions where AWS Clean Rooms is available, see the AWS Regions table. To learn more about collaborating with AWS Clean Rooms, visit AWS Clean Rooms.

AWS Databases are now available on v0 by Vercel

Amazon Aurora PostgreSQL, Amazon Aurora DSQL, and Amazon DynamoDB serverless databases are now available on v0 by Vercel, an AI-powered tool that transforms your ideas into production-ready, full-stack web applications in minutes. With this launch, you can build your ideas as well as create and connect to AWS databases from v0 using natural language prompts.\n To get started, simply describe what you want to build in v0. The tool takes care of developing the frontend user interface and backend logic, storing your application data in the AWS database that best meets your application needs. v0 provides an end-to-end setup experience where you can choose and configure database resources under a new AWS account or link to an existing account, all without leaving v0 interface. New AWS accounts from Vercel include access to all three databases and $100 USD in credits that can be used with any of the database options for up to six months. You can also manage your plan, add payment information, and view usage details anytime by visiting the AWS settings portal from the Vercel dashboard. To learn more, visit v0 or the AWS landing page on the Vercel Marketplace. The serverless options for Amazon Aurora PostgreSQL, Amazon Aurora DSQL, and Amazon DynamoDB do not require infrastructure management and reduce costs by scaling down to zero automatically when not in use. You can create a database in the following AWS Regions: US East (N. Virginia), US East (Ohio), US West (Oregon), Europe (Ireland), Europe (Frankfurt), Asia Pacific (Tokyo), and Asia Pacific (Mumbai). AWS Databases deliver security, reliability, and price performance without the operational overhead, whether you’re prototyping your next big idea or running production AI and data driven applications. For more information, visit the AWS Databases webpage.

Announcing Amazon EC2 Memory optimized X8i instances

Amazon Web Services (AWS) is announcing the general availability of Amazon EC2 X8i instances, next-generation memory optimized instances powered by custom Intel Xeon 6 processors available only on AWS. X8i instances are SAP-certified and deliver the highest performance and fastest memory bandwidth among comparable Intel processors in the cloud. They deliver up to 43% higher performance, 1.5x more memory capacity (up to 6TB), and 3.4x more memory bandwidth compared to previous generation X2i instances.\n X8i instances are designed for memory-intensive workloads like SAP HANA, large databases, data analytics, and Electronic Design Automation (EDA). Compared to X2i instances, X8i instances offer up to 50% higher SAPS performance, up to 47% faster PostgreSQL performance, 88% faster Memcached performance, and 46% faster AI inference performance. X8i instances come in 14 sizes, from large to 96xlarge, including two bare metal options. X8i instances are available in the following AWS Regions: US East (N. Virginia), US East (Ohio), US West (Oregon), and Europe (Frankfurt). To get started, visit the AWS Management Console. X8i instances can be purchased via Savings Plans, On-Demand instances, and Spot instances. For more information visit X8i instances page.

Amazon Connect now provides agent scheduling metrics in data lake

Amazon Connect now provides agent scheduling metrics in data lake, making it easier for you to generate reports and insights from this data. For example, after publishing schedules for next month, you can access interval level (15 minutes or 30 minutes) metrics such as forecasted headcount, scheduled headcount, and projected service level in Connect analytics data lake. You can view aggregated metrics for an entire business unit (forecast group) or broken down by specific demand segments (demand groups). You can then visualize this data in Amazon Quick Sight or another BI tool of your choice for further analysis, such as identifying periods of over or under-staffing. This eliminates the need for manual reviews of agent schedules thus improving productivity for schedulers and supervisors.\n This feature is available in all AWS Regions where Amazon Connect agent scheduling is available. To learn more about Amazon Connect agent scheduling, click here.

Amazon RDS now supports the latest CU and GDR updates for Microsoft SQL Server

Amazon Relational Database Service (Amazon RDS) for SQL Server now supports the latest General Distribution Release (GDR) updates for Microsoft SQL Server. This release includes support for Microsoft SQL Server 2016 SP3+GDR KB5068401 (RDS version 13.00.6475.1.v1), SQL Server 2017 CU31+GDR KB5068402 (RDS version 14.00.3515.1.v1), SQL Server 2019 CU32+GDR KB5068404 (RDS version 15.00.4455.2.1.v1) and SQL Server 2022 CU22 KB5068450 (RDS version 16.00.4225.2.1.v1).\n The GDR updates address vulnerabilities described in CVE-2025-59499. For additional information on the improvements and fixes included in these updates, see Microsoft documentation for KB5068401, KB5068402, KB5068404, KB5068450. We recommend that you upgrade your Amazon RDS for SQL Server instances to apply these updates using Amazon RDS Management Console, or by using the AWS SDK or CLI. You can learn more about upgrading your database instance in the Amazon RDS SQL Server User Guide for upgrading your RDS Microsoft SQL Server DB engine.

AWS Lambda announces cross-account access for DynamoDB Streams

AWS Lambda now supports cross-account access for AWS DynamoDB Streams event-source mappings (ESMs),\n enabling you to trigger Lambda functions in one account from DynamoDB Streams in another account. Customers build event-driven applications using Lambda’s fully-managed DynamoDB Streams ESMs, which poll change events from DynamoDB tables and trigger your Lambda functions. Organizations implementing multi-account architectures—whether to centralize event processing or share events with partner teams—previously needed to build complex data replication solutions to share data across accounts, which added operational overhead . With this launch, you can now provide cross-account access to your DynamoDB Streams to trigger Lambda functions in another account. By setting a resource-based policy on your DynomoDB stream, you can enable a Lambda function in one account to access DynomoDB stream in another account. This capability allows you to simplify your streaming applications across accounts without the overhead of replication solutions in each account. This feature is generally available in all AWS Commercial and AWS GovCloud (US) Regions. You can enable cross-account Lambda triggers by creating resource-based policies for your DynamoDB Streams using the AWS Management Console, AWS CLI, AWS SDKs, AWS CloudFormation, or AWS APIs. To learn more, read Lambda ESM documentation.

Amazon RDS Custom now supports the latest GDR updates for Microsoft SQL Server

Amazon Relational Database Service (Amazon RDS) Custom for SQL Server now supports the latest General Distribution Release (GDR) updates for Microsoft SQL Server. This release includes support for SQL Server 2019 CU32+GDR KB5068404 (RDS version 15.00.4455.2.1.v1) and SQL Server 2022 CU21+GDR KB5068406 (RDS version 16.00.4222.2.1.v1).\n The GDR updates address vulnerabilities described in CVE-2025-59499. For additional information on the improvements and fixes included in these updates, see Microsoft documentation for KB5068404 and KB5068406. We recommend that you upgrade your Amazon RDS Custom for SQL Server instances to apply these updates using Amazon RDS Management Console, or by using the AWS SDK or CLI. You can learn more about upgrading your database instance in the Amazon RDS Custom User Guide.

Amazon Redshift Serverless adds queue-based query resource management

Amazon Redshift Serverless introduces queue-based query resource management. You can create dedicated query queues with customized monitoring rules for different workloads. This feature provides granular control over resource usage. Queues let you set metrics-based predicates and automated responses. For example, you can configure rules to automatically abort queries that exceed time limits or consume too many resources.\n Previously, Query Monitoring Rules (QMR) were applied only at the Redshift Serverless workgroup level, affecting all queries run in this workgroup uniformly. The new queue-based approach lets you create queues with distinct monitoring rules. You can assign these queues to specific user roles and query groups. Each queue operates independently, with rules affecting only the queries within that queue. The available monitoring metrics can be found in Query monitoring metrics for Amazon Redshift Serverless. This feature is available in all AWS regions that support Amazon Redshift Serverless. You can manage QMR with queues through the AWS Console and Redshift APIs. For implementation details, see the documentation in the Amazon Redshift management guide.

Amazon EBS now supports up to four Elastic Volumes modifications in 24 hours

Amazon Elastic Block Store (EBS) now supports up to four Elastic Volumes modifications per volume within a rolling 24-hour window. Elastic Volumes modifications allow you to increase the size, change the type, and adjust the performance of your EBS volumes. With this update, you can start a new modification immediately after the previous one completes, as long as you have initiated fewer than four modifications in the past 24 hours.\n This enhancement improves your operational agility to immediately scale storage capacity or adjust performance in response to sudden data growth or unanticipated workload spikes. With Elastic Volumes modifications, you can modify your volumes without detaching them or restarting your instances, allowing your application to continue running with minimal performance impact.

This feature is available in all commercial AWS Regions, the AWS GovCloud (US) Regions, and the China Regions. This capability is automatically enabled without requiring changes to your existing workflows. To learn more, see Modify an Amazon EBS volume using Elastic Volumes operations in the Amazon EBS User Guide.

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