AWS Recent Announcements

Amazon OpenSearch Service now supports one-click migration from legacy OpenSearch Dashboards to OpenSearch UI, for both OpenSearch domains and serverless collections. OpenSearch UI is the new, zero-downtime, serverless interface for search and unified observability across multiple data sources. With this launch, the multiple tenants and thousands of saved objects you created in legacy OpenSearch Dashboards become reusable in your OpenSearch UI applications, reducing the operational complexity of moving between interfaces. With one-click migration, you can move your existing tenants and saved objects into OpenSearch UI workspaces without recreating them manually. The mechanism works for OpenSearch Dashboards created under Amazon OpenSearch Service domains and serverless collections. You can migrate everything into a new workspace or into an existing one. If you have created multiple tenants in your OpenSearch Dashboard, you have the option to either convert them into a single workspace or keep them separate for different teams.   This feature is available in all AWS Regions where OpenSearch UI is available. To get started, see Using OpenSearch UI in the Amazon OpenSearch Service Developer Guide. Visit the OpenSearch UI Help page for detailed feature tutorials. To learn more about the service, see the Amazon OpenSearch Service product page.

Amazon Managed Grafana is now a FedRAMP High authorized service in the AWS GovCloud (US-East) and AWS GovCloud (US-West) regions. Federal agencies, public sector organizations, and other enterprises with FedRAMP High compliance requirements can now use Amazon Managed Grafana to visualize, query, and alert on operational metrics across their AWS and hybrid environments while meeting their strict security and compliance requirements. Amazon Managed Grafana is a fully managed service based on open-source Grafana that makes it easier for you to visualize and analyze your operational data at scale. The Federal Risk and Authorization Management Program (FedRAMP) is a US government-wide program that delivers a standard approach to the security assessment, authorization, and continuous monitoring for cloud products and services.  For more details about Amazon Managed Grafana in AWS GovCloud (US), visit the Amazon Managed Grafana GovCloud documentation or contact your AWS account team for more information. To learn more, visit the Amazon Managed Grafana product page.

Today, AWS Billing and Cost Management (BCM) announces support for Cost Efficiency widget in BCM Dashboards. You can now view cost efficiency trends alongside Cost Explorer, Budgets, and reports for Savings Plans and Reserved Instance coverage and utilization reports. This provides a unified view of your spending, commitments, and optimization performance in a single, tailored dashboard. The Cost Efficiency widget displays your efficiency score over time, showing how your efficiency across your AWS environment changes over time. You can view efficiency by AWS account, region, or overall, and adjust granularity to analyze trends at the level that matters most to your team. By adding one or more Cost Efficiency widget to a BCM Dashboard, you can monitor your optimization performance from your existing cost management workflows. The widget links directly to the Cost Optimization Hub console so you can easily take actions when you have recommendations for savings opportunities. With the Cost Efficiency widget, you can create a unified view of your spending, commitments, budgets, and optimization performance. The widget is fully integrated with dashboard exports and can be included in scheduled email reports or downloaded as a CSV or PDF for offline analysis. They are also included with cross-account dashboard sharing. The Cost Efficiency widget for BCM Dashboards is available in all AWS commercial Regions at no additional charge. To learn more, visit our User Guide.

Amazon EC2 now surfaces the AWS Systems Manager (SSM) Parameter Store parameters associated with public AMIs directly in the AMI metadata. When you describe a public AMI, the response includes the associated public SSM parameter, making it easy to discover and reference in your configurations. Previously, finding the SSM parameter associated with a public AMI required searching through SSM parameter namespaces manually. Now, when you describe a public AMI, the response includes the public SSM parameter it is associated with. This allows you to discover the SSM parameter for a public AMI easily and use it as an alias that always resolves to the latest version, simplifying AMI updates across your infrastructure. This capability is available to all customers at no additional cost in all AWS regions including AWS China (Beijing) Region, operated by Sinnet, and AWS China (Ningxia) Region, operated by NWCD, and AWS GovCloud (US) Regions. To learn more, please visit the documentation.

Amazon RDS for PostgreSQL 19 Beta 2 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 2 in the Amazon RDS Database Preview Environment that has the benefits of a fully managed database. PostgreSQL 19 introduces parallel autovacuum with configurable worker limits, so routine maintenance no longer bottlenecks large databases. The new REPACK CONCURRENTLY command rebuilds tables and reclaims storage online, keeping production databases accessible without third-party extensions. Native SQL Property Graph Queries (SQL/PGQ) let you express relationship traversals directly in standard SQL, eliminating separate application logic. Logical replication now synchronizes sequence values automatically and can be enabled dynamically without a server restart, reducing planned downtime. Beta 2 adds bug fixes and stability improvements from the Beta 1 testing period, including refinements to parallel autovacuum worker coordination and REPACK CONCURRENTLY lock handling. 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.

Amazon S3 Event Notifications now include system-generated tags in events delivered to all destinations including Amazon EventBridge, Amazon SQS, Amazon SNS, and AWS Lambda. System-generated tags are metadata labels attached to your bucket by AWS services. You can use these tags to filter events from thousands of buckets with a single EventBridge rule, instead of listing each bucket name individually. To get started, enable S3 Event Notifications on your general purpose buckets through the AWS Management Console, AWS SDK, or AWS CLI. If AWS services like AWS CloudFormation have already applied system-generated tags to your buckets, S3 automatically includes them in new event notifications. System-generated tags in S3 Event Notifications are available at no additional cost in all AWS Regions and require no changes to existing configurations. To learn more, visit the S3 Event Notifications documentation.

Customers can now view annual water withdrawals data associated with their AWS workloads in AWS Sustainability, alongside existing carbon emissions data. This enhancement helps organizations gain comprehensive visibility into their environmental impact across carbon and water. Water withdrawals data is available by AWS Region, service, and AWS account on an annual basis through the AWS Sustainability console and API. The data represents the total volume of water withdrawn for data center operations, with efficiency improvements reflected as lower withdrawal volumes. AWS Sustainability water withdrawals data is available at no additional charge in all AWS Regions where the service is available. To get started visit the AWS Sustainability user guide. For more information, see the AWS Sustainability console page.

Amazon EC2 High Memory U7in-24TB instances (u7in-24tb.224xlarge) are now available in AWS Europe (Paris) region. U7i instances are part of the AWS 7th generation and are powered by custom fourth-generation Intel Xeon Scalable processors (Sapphire Rapids). U7in-24TB instances offer 24 TiB of DDR5 memory, enabling customers to scale transaction processing throughput in a fast-growing data environment. U7i instances offer up to 45% better price performance over existing U-1 instances. U7in-24TB instances deliver 896 vCPUs and support up to 100 Gbps of Amazon EBS bandwidth for faster data loading and backups, 200 Gbps of network bandwidth, and ENA Express. U7i instances are ideal for customers running mission-critical in-memory databases like SAP HANA, Oracle, and SQL Server. To learn more about U7i instances, visit the High Memory instances page.

Amazon Redshift announces the general availability of two new RG instance sizes – rg.large and rg.12xlarge. These new sizes deliver the same Graviton-powered performance benefits as existing RG instances, including up to 2.4x faster query performance than previous-generation RA3 instances at 30% lower price per vCPU, giving you more flexibility to right-size your provisioned clusters for any workload. rg.large and rg.12xlarge instance sizes are available on the current track (P202) only. Customers on the trailing track (P201) can continue to use rg.xlarge and rg.4xlarge. Existing RA3 clusters can migrate to RG instances using Snapshot and Restore, Elastic Resize, or Classic Resize. RG instances are available with flexible pricing options, including On-Demand, and 1-year and 3-year Reserved Instances with No Upfront payment. The new rg.large and rg.12xlarge instance sizes are now available in the following AWS Regions: US East (N. Virginia), US East (Ohio), US West (Oregon), US West (N. California), Canada (Central), Mexico (Central), South America (São Paulo), Europe (Ireland), Europe (Frankfurt), Europe (London), Europe (Paris), Europe (Stockholm), Europe (Spain), Africa (Cape Town), Asia Pacific (Tokyo), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Mumbai), Asia Pacific (Jakarta), Asia Pacific (Hong Kong), Asia Pacific (Osaka), Asia Pacific (Malaysia), Asia Pacific (Hyderabad), Asia Pacific (Taiwan), Asia Pacific (Thailand), and Asia Pacific (Melbourne). To get started, refer to the following resources: Amazon Redshift node types RA3 to RG upgrade guide Amazon Redshift cluster versions Amazon Redshift pricing

You can now transition objects to S3 Standard-Infrequent Access (S3 Standard-IA) and S3 One Zone-Infrequent Access (S3 One Zone-IA) as soon as the day they are created, without the previous 30-day minimum retention in S3 Standard. These storage classes offer up to 40% lower storage costs than S3 Standard while still providing millisecond access when needed, making them ideal for backups, log analytics, and compliance workloads where data becomes cold within hours or days. To get started, create new S3 Lifecycle rules to transition objects to S3 Standard-IA and S3 One Zone-IA as soon as 0 days after creation. You can configure these rules using the S3 console, AWS CLI, or SDKs. This update is available in all AWS Regions where S3 Standard-IA and S3 One Zone-IA are available. For pricing details, visit the Amazon S3 pricing page. To learn more, visit the overview page and documentation.

AWS Backup restore testing is now available in seven additional AWS Regions: Asia Pacific (Taipei), Asia Pacific (Malaysia), Asia Pacific (New Zealand), Asia Pacific (Thailand), Israel (Tel Aviv), Mexico (Central), and Canada West (Calgary). Restore testing helps you automate and periodically run restore tests of supported AWS resources across storage, compute, and database services. You can create restore testing plans that automatically select recovery points, run restores on a schedule, and measure restore job completion time against your recovery time objectives (RTO). This helps you evaluate recovery readiness and meet regulatory and compliance requirements for disaster recovery and business continuity. To get started, visit the AWS Backup console, AWS Command Line Interface (CLI), or AWS SDKs. For a complete list of supported Regions and features, visit the AWS Backup documentation To learn more about restore testing, visit the feature documentation and pricing page.

AWS Backup logically air-gapped vaults are now available in six additional AWS Regions: Asia Pacific (Taipei), Asia Pacific (Malaysia), Asia Pacific (New Zealand), Asia Pacific (Thailand), Mexico (Central), and Canada West (Calgary). With logically air-gapped vaults now available in these Regions, you can store immutable, isolated backups that are locked by default and encrypted using AWS owned keys or customer-managed keys. You can back up directly to logically air-gapped vaults, copy backups across accounts and Regions, share vaults for recovery using AWS Resource Access Manager (RAM), and safeguard vault access during account compromise using Multi-party approval. To get started, visit the AWS Backup console, AWS Command Line Interface (CLI), or AWS SDKs. For a complete list of supported Regions and features, visit the AWS Backup documentation. To learn more about logically air-gapped vaults, visit the feature documentation and pricing page.

AWS Control Tower Account Factory for Terraform (AFT) can now automatically re-apply an account’s customizations when that account moves to a different Organizational Unit (OU). Previously, moving an enrolled account between OUs required manually triggering customization re-application, creating operational overhead and risk of configuration drift. With this capability, you can opt in to automatic re-application in your AFT deployment, so accounts stay consistent with their OU-specific configuration as soon as they’re moved. To enable this capability, set aft_customization_triggers = [“account_move”] in your AFT configuration. The re-application workflow skips the bootstrap and provisioning phases, running only global and account-level customizations for faster execution. Individual accounts can be excluded from this behavior by setting account_skip_customization_triggers = “true”, giving teams precise control over which accounts participate in automated re-application. This release also includes additional improvements: support for custom Terraform Cloud and Enterprise workspace naming variables, tighter access controls on the AFT logging bucket, and improved scaling for large-scale AWS Enterprise Support enrollment. Organizations enforcing compliance or security baselines tied to OU membership will benefit most from these combined enhancements. This capability is available today across all AWS regions where AWS Control Tower Account Factory for Terraform is offered. To learn more about enabling automatic customization re-application and upgrading to the latest AFT release, visit the AFT documentation and review the AFT release notes on GitHub.

Amazon Aurora DSQL is now in scope for FedRAMP Moderate in the US East (Ohio), US East (N. Virginia), and US West (Oregon) Regions. You can now use Aurora DSQL to build applications and run workloads that are subject to FedRAMP Moderate compliance requirements. The Federal Risk and Authorization Management Program (FedRAMP) is a US government-wide program that delivers a standard approach to the security assessment, authorization, and continuous monitoring for cloud products and services. Amazon Aurora DSQL is the fastest serverless, distributed SQL database, with active-active high availability and multi-Region strong consistency. It enables you to build always-available applications with virtually unlimited scale, the highest availability, and zero infrastructure management. To learn more about FedRAMP, visit the AWS services in scope page. To learn more about Amazon Aurora DSQL, visit the Aurora DSQL webpage and documentation.

Amazon CloudWatch Logs Insights query language now supports 25 new commands and functions that expand your ability to query, transform, correlate, and analyze logs. Customers analyzing logs in CloudWatch Logs Insights often need to perform statistical aggregation, handle null values in time-series data, compare logs across time windows, detect outliers, and enrich events with lookup data. With this launch, CloudWatch Logs Insights adds type conversion and encoding functions (hexToAscii, hexToDec, decToHex), date and time functions (parseDate, formatDate, queryStartTime, queryEndTime, queryTimeRange), string functions (messageSize), JSON inspection functions (jsonArraySize, jsonArrayContains), and a conditional validation function (isNumeric). It also introduces statistical commands (variance, topk, countFrequent), row-sequencing and null-handling commands (autoregress, accum, filldown, fillmissing), sessionization and time-comparison commands (sessionize, logcompare), a data analysis command (outlier), query-composition and join commands (where, appendcols), and a lookup enrichment command (cidrlookup). These commands and functions are available today in all commercial AWS Regions. To learn more, see the Amazon CloudWatch Logs documentation.

Amazon CloudWatch Logs now supports intelligent storage tiering, which automatically classifies your log data across three storage tiers – Standard (existing), Infrequent Access, and Archive Instant Access based on access patterns. This allows you to store logs in Amazon CloudWatch for extended periods at lower-cost tiers without any operational overhead. With today’s launch, customers can now retain high-volume verbose logs needed to be stored for longer periods at a lower cost in Amazon CloudWatch. Instead of filtering these logs or exporting them, you can now keep them natively in Amazon CloudWatch and benefit from the same query experience regardless of which tier your data resides in. Amazon CloudWatch monitors access patterns and automatically reclassifies data not accessed for 30 days to the Infrequent Access tier, and data not accessed for 90 days to the Archive Instant Access tier. When you access older data, it is automatically promoted back to the Standard tier for 30 days. By consolidating all your logs in CloudWatch, you get full visibility in one tool, thereby eliminating the operational overhead of managing multiple storage solutions and reducing your Mean Time to Resolution (MTTR) by analyzing, and alerting on all your logs in a single place. Amazon CloudWatch Logs Intelligent-Tiering is available in all AWS commercial regions except Middle East (Bahrain) and Middle East (UAE). You can enable intelligent tiering at the account level in the AWS Management Console, AWS SDKs or through AWS CLI. Learn more about CloudWatch Logs intelligent tiering pricing and documentation.

Amazon MQ now allows you to configure the EBS Disk storage size for RabbitMQ brokers independently of instance type. When creating or updating a broker, you can define a custom storage size, allowing you to right-size storage independently of your instance size to match your specific messaging workload requirements. Configurable storage is available for RabbitMQ M7g brokers on version 4.2 or later using cluster deployments only. With configurable storage, you can choose a storage size from the default value on M7g to the maximum allowed value depending on your instance size in increments of 5 GB. You can specify the Storage Size using the using the AWS Console, AWS CloudFormation, AWS Command Line Interface (CLI), or the AWS Cloud Development Kit (CDK). Storage changes are applied during the next broker reboot.  Standard Amazon MQ storage pricing applies based on the disk size as per Amazon MQ pricing. Configurable storage is available in all commercial AWS Regions where Amazon MQ for RabbitMQ is offered. To learn more, see the Amazon MQ Developer Guide.

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) G7e instances accelerated by NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs are now available in the AWS Europe (Frankfurt, Stockholm) and Asia Pacific (Mumbai) Regions. G7e instances offer up to 2.3x inference performance compared to G6e. Customers can use G7e instances to deploy large language models (LLMs), agentic AI models, multimodal generative AI models, and physical AI models. G7e instances offer the highest performance for spatial computing workloads as well as workloads that require both graphics and AI processing capabilities. G7e instances feature up to 8 NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs, with 96 GB of memory per GPU, and 5th Generation Intel Xeon processors. They support up to 192 virtual CPUs (vCPUs) and up to 1600 Gbps of networking bandwidth. G7e instances support NVIDIA GPUDirect Peer to Peer (P2P) that boosts performance for multi-GPU workloads. Multi-GPU G7e instances also support NVIDIA GPUDirect Remote Direct Memory Access (RDMA) with EFA in EC2 UltraClusters, reducing latency for small-scale multi-node workloads. You can use G7e instances for Amazon EC2 in the following AWS Regions: US West (Oregon), US East (N. Virginia, Ohio), Europe (Spain, London, Frankfurt, Stockholm) and Asia Pacific (Tokyo, Seoul, Mumbai). You can purchase G7e instances as On-Demand Instances, Spot Instances, or as part of Savings Plans. To get started, visit the AWS Management Console, AWS Command Line Interface (CLI), and AWS SDKs. To learn more, visit G7e instances.

Amazon Managed Streaming for Apache Kafka (Amazon MSK) Express Brokers now supports Apache Kafka version 4.2. This release includes Eligible Leader Replicas (ELR) enhancements that strengthen availability with improved leader election correctness. It also introduces a new consumer rebalance protocol that helps ensure smoother and faster group rebalances, and a new Streams Rebalance Protocol that extends broker coordination capabilities to Kafka Streams for optimized task assignments. For a complete list of improvements and bug fixes, please refer to the Apache Kafka release notes for version 4.2. 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. This launch brings the latest open-source reliability and performance improvements to MSK Express. To get started, simply select version 4.2.x when creating a new cluster with Express Brokers via the AWS Management Console, AWS CLI, or AWS SDKs. You can also upgrade existing MSK Express Brokers with an in-place rolling update. Amazon MSK orchestrates broker restarts to maintain availability and protect your data during the upgrade. Kafka version 4.2 support is available today across all AWS regions where Amazon MSK Express Brokers is offered. To learn how to get started, see the Amazon MSK Developer Guide.

AWS Graviton4-based R8g database instances are now generally available for Amazon Aurora (MySQL and PostgreSQL compatibility) and Amazon RDS for PostgreSQL, MySQL, and MariaDB in Asia Pacific (Hyderabad, Melbourne, Malaysia), Europe (London, Paris, Zurich), AWS GovCloud (US-East), South America (Sao Paulo), and Mexico (Central) regions. Additionally, M8g instances are now supported for Amazon RDS for PostgreSQL, MySQL, and MariaDB in US West (N. California), Asia Pacific (Mumbai, Sydney, Hong Kong, Seoul, Malaysia, Singapore), Canada West (Calgary), Europe (Zurich, Milan, Paris), South America (Sao Paulo) and Africa (Cape Town) regions.  AWS Graviton4-based instances provide up to 40% performance improvement and up to 29% price/performance improvement for on-demand pricing over Graviton3-based instances of equivalent sizes on Amazon Aurora and Amazon RDS databases, depending on database engine, version, and workload. Built on the AWS Nitro System, the new R8g database instances introduce 24xlarge and 48xlarge sizes, delivering up to 192 vCPUs, an 8:1 ratio of memory to vCPU with the latest DDR5 memory, up to 50Gbps enhanced networking bandwidth, and up to 40Gbps of bandwidth to Amazon Elastic Block Store (Amazon EBS). You can easily launch R8g or M8g database instances through the Amazon RDS Management Console or by using the AWS Command Line Interface (CLI). For detailed information about specific engine versions that support these database instance types, please refer to the Aurora and RDS documentation. For complete information on pricing and regional availability, please refer to the Amazon RDS pricing page. 

Amazon Cognito now supports importing users with password hashes in CSV user imports. Previously, users imported from a CSV file had to reset their passwords on first sign-in. Now, you can include password hashes in your CSV file so that imported users can sign in immediately with their existing credentials. When creating a CSV import, you specify the password hashing algorithm used by your source system. Amazon Cognito imports these users and verifies their password against the imported hash on first sign-in. Supported algorithms include bcrypt, scrypt, Argon2id, and PBKDF2 with SHA-256. All imported hashes receive an additional layer of cryptographic protection before storage. Password hash import is available in all AWS Regions where Amazon Cognito is available. To get started, create a user import using the AWS Management Console, AWS Command Line Interface (CLI), or AWS Software Development Kits (SDKs). See the developer guide for instructions.

Amazon Relational Database Service (RDS) now supports R8gd database instances in 12 additional regions and and M8gd database instances in 6 additional Regions with Optimized Reads for Amazon Aurora PostgreSQL, RDS for PostgreSQL, RDS for MySQL, and RDS for MariaDB. R8gd and M8gd instances deliver up to 165% better throughput and up to 120% better price-performance over R6g instances for Aurora PostgreSQL. Optimized Reads uses local NVMe-based SSD block storage to store ephemeral data such as temporary tables, reducing network storage access and improving query latency. The result is improved query performance for complex queries and faster index rebuild operations. Aurora PostgreSQL Optimized Reads instances using the I/O-Optimized configuration also use the local storage to extend their caching capacity. Database pages that are evicted from the in-memory buffer cache are cached in local storage to speed subsequent retrieval of that data. Customers can get started with Optimized Reads through the AWS Management Console, CLI, and SDK by modifying their existing Aurora and RDS databases or creating a new database using R8gd or M8gd instances. R8gd instances are available in the following additional regions: Europe (Ireland), Asia Pacific (Seoul), Asia Pacific (Malaysia), Europe (London), US West (N. California), Asia Pacific (Sydney), Canada (Central), Asia Pacific (Jakarta), Africa (Cape Town), Canada West (Calgary), South America (Sao Paulo) and Asia Pacific (Hong Kong). M8gd instances are available in the following additional regions: Europe (Ireland), Asia Pacific (Malaysia), Europe (London), Asia Pacific (Sydney), South America (Sao Paulo) and Canada (Central). For complete information on pricing and regional availability, please refer to the pricing page. For information on specific engine versions that support these DB instance types, please see the Aurora and RDS documentation.

Amazon RDS now allows up to four storage modifications per database instance within a rolling 24-hour window. These modifications let you increase the size, change the type, and adjust the performance of your RDS storage volumes. You can start a new modification right after storage optimization for the previous modification is complete without having to wait for the six-hour cool-off period to complete. This enhancement improves operational agility for scaling storage capacity or adjusting performance during sudden data growth or unexpected workload spikes. With RDS storage modifications, you can modify your volumes without downtime, keeping applications running with minimal performance impact. The feature is automatically enabled on all Amazon RDS for PostgreSQL, Amazon RDS for MariaDB, Amazon RDS for MySQL, Amazon RDS for Db2, Amazon RDS for Oracle, and Amazon RDS for Microsoft SQL Server instances in all commercial AWS Regions and the AWS GovCloud (US) Regions. To learn more, refer the Amazon RDS User Guide.

AWS Glue SAP OData connector and zero-ETL integrations are now available in AWS GovCloud (US-West) and AWS GovCloud (US-East) Regions, with support for Amazon DynamoDB, Salesforce, and SAP OData as sources. Customers operating in regulated environments can now replicate data from these sources into Amazon Redshift, Amazon S3, or other supported destinations without building or maintaining custom data pipelines. The SAP OData connector allows you to extract data from SAP systems exposing OData services, eliminating the need for custom extraction logic or third-party middleware. The zero-ETL integrations are fully managed by AWS and minimize the need to build ETL data pipelines. With this new zero-ETL integration, you can efficiently extract and load valuable data from your Amazon DynamoDB databases or Salesforce and SAP applications into your data lake and data warehouse for analysis. Zero-ETL integration reduces your operational burden and saves the weeks of engineering effort needed to design, build, and test data pipelines. By selecting a few settings in the no-code interface, you can quickly set up your zero-ETL integration to automatically ingest and continually maintain an up-to-date replica of your data in the data lake and data warehouse. Zero-ETL integrations help you focus on deriving insights from your application data, breaking down data silos in your organization and improving operational efficiency. To get started, navigate to the AWS Glue console and create a new zero-ETL integration. For more information, visit the AWS Glue zero-ETL integrations documentation.

Amazon OpenSearch Service now integrates with the Agent Toolkit for AWS, enabling you to build, manage, and query OpenSearch Service domains and OpenSearch Serverless collections directly from AI coding agents such as Claude Code, Kiro, and Cursor. The integration is powered by the AWS MCP (Model Context Protocol) server, which executes AWS API calls on your behalf, paired with the curated amazon-opensearch-service skill that automatically routes natural-language requests to the right capability. With this skill, you can describe a goal in plain language and the agent handles the rest across five areas. Migration moves you from self-managed OpenSearch into OpenSearch Service or OpenSearch Serverless. Operations provisions and manages domains and collections. Search builds vector, semantic, hybrid, and RAG search. Log analytics analyzes logs with PPL and OpenSearch Ingestion. Trace analytics investigates distributed traces with OpenTelemetry. The integration works with both managed domains and collections across all versions, requires no changes to your existing infrastructure, and is available at no additional charge. To learn more about these capabilities, see our documentation. Support is available in all AWS Regions where Amazon OpenSearch Service and OpenSearch Serverless are offered. To get started, install the aws-data-analytics plugin in your agent — it bundles the AWS MCP Server configuration and the OpenSearch skill in a single step. For setup instructions, see MCP Server and Agent Skills. 

Amazon Relational Database Service (Amazon RDS) for Db2 is now available in the Asia Pacific (Thailand), Asia Pacific (Malaysia), Asia Pacific (Taipei), Mexico (Central), and Canada West (Calgary) Regions. Amazon RDS for Db2 makes it easy to set up, operate, and scale Db2 databases in the cloud. Customers can deploy a Db2 database in minutes with automatically configured parameters for optimal performance. For databases setup with Multi-AZ configuration, Amazon RDS performs synchronous replication to a standby instance in a different Availability Zone to provide high availability. To use Amazon RDS for Db2, customers can purchase a Db2 license from the AWS Marketplace for hourly, pay-as-you-go pricing, or use Bring Your Own License (BYOL). Both hourly and BYOL licensing are available in Standard and Advanced Editions. You can also choose to use the latest Db2 Community Edition that provides all the features available in Standard and Advanced Editions, with no commercial software licensing charges for development and test applications. This allows you to easily start developing and testing Db2 applications with a managed database service without worrying about software licensing. To learn more about Amazon RDS for Db2, refer to documentation and pricing pages.  

AWS Lambda now supports self-managed Amazon S3 buckets for code storage, enabling you to reference source code directly from your own S3 buckets without Lambda creating intermediate copies. This eliminates code storage limits and reduces function activation time after function creates and updates by removing the copy step. AWS Lambda is a serverless compute service that runs your code without requiring you to manage servers. Customers who deploy many functions and additional code as Lambda layers often need more than 75GB of code storage per Region, requiring support tickets to increase this quota. Previously, Lambda always copied your deployment package to Lambda-managed storage during function and layer creation, counting against this limit. Now, with self-managed code storage, Lambda references your code directly in your Amazon S3 bucket without creating a copy, so you can store as much function and layer code as your bucket allows. You maintain a single source of truth for your deployment packages in your own account. No additional Lambda charges apply for self-managed storage; you only pay for standard Amazon S3 storage and, where applicable, cross-Region data transfer rates. In addition, Lambda has increased the default limit for Lambda-managed code storage from 75GB to 300GB per Region per account. Self-managed Amazon S3 code storage is available in all commercial AWS Regions. To get started, set the `S3ObjectStorageMode` parameter to `REFERENCE` when creating or updating functions and layers through the AWS CLI, AWS CloudFormation, AWS SAM, or AWS SDKs. You must grant the Lambda service principal `s3:GetObject` and `s3:GetObjectVersion` permissions on your S3 bucket. You can also update a function to use self-managed code storage via the Lambda Console. To learn more, visit the AWS Lambda Developer Guide.

AWS Elastic Disaster Recovery (AWS DRS) now recovers your AWS-based workloads faster. For source servers running on Amazon EC2, DRS can now skip preparation steps that these workloads no longer need, reducing recovery time by up to 65% for Windows and up to 40% for Linux. During a disaster or a drill, every minute matters. Because workloads already running on AWS come with AWS-compatible drivers and configuration, DRS can launch them with fewer steps — helping you bring applications back online sooner and with greater confidence. Networking, drivers, and licensing are still applied automatically, so recovery stays simple and hands-off. You remain in control: turn on faster recovery across your whole account or for individual servers and change the setting whenever your needs change. This capability is available in all AWS Regions where AWS DRS is offered, at no additional cost. To learn more, visit the AWS Elastic Disaster Recovery User Guide.

AWS Elastic Disaster Recovery (AWS DRS) now supports the Amazon EBS volume initialization rate, helping recovered volumes reach full performance faster during drills and recoveries. When DRS restores EBS volumes from snapshots, the data loads from Amazon S3 in the background, and I/O to blocks that haven’t loaded yet can be slower until initialization finishes. With this launch, you can set a volume initialization rate on your DRS-managed EC2 launch template, and DRS applies it automatically when it creates volumes during recovery — bringing your applications to full storage performance on a predictable timeline. This is especially valuable for I/O-intensive workloads such as databases, where fast, consistent storage performance is critical to meeting your recovery time objectives. You set the rate once on the launch template, and DRS preserves it across the updates it makes for rightsizing or disk changes. If the rate cannot be applied for a given recovery, DRS completes recovery without it, so your recovery is never blocked. AWS DRS support for the EBS volume initialization rate is available in all AWS Regions and environments where the EBS volume initialization rate is offered. You are charged per GB based on the full snapshot size and the rate you specify; for details, see Amazon EBS pricing. To learn more, see the AWS Elastic Disaster Recovery User Guide.

Amazon CloudWatch now supports lookup processor, enabling you to enrich log events with additional context by matching fields in your logs against a lookup table directly within your CloudWatch Pipeline. With the lookup processor, you can upload CSV files containing reference data and configure your pipeline to match incoming log fields against this data to add enriched metadata. For example, you can upload a CSV mapping IP addresses to application teams and automatically tag VPC Flow Logs with team ownership information as logs are ingested. The lookup processor matches fields in your log events against fields in a lookup table and adds specified fields from matching rows to your log events. This enables data enrichment scenarios such as mapping user IDs to user details, product codes to product information, or error codes to human-readable error descriptions, thereby eliminating the need to build and maintain custom enrichment logic outside of CloudWatch. By enriching logs at ingestion time, your queries, dashboards, and alarms immediately benefit from the added context without any post-processing. The lookup table processor is available in all AWS commercial regions that support Amazon CloudWatch pipelines. You can add a lookup processor to your pipeline using the AWS Management Console, AWS CLI, or AWS SDKs. To get started, see the Amazon CloudWatch Logs documentation.