8/14/2025, 12:00:00 AM ~ 8/15/2025, 12:00:00 AM (UTC)
Recent Announcements
SageMaker HyperPod now supports fine-grained quota allocation of compute resources
SageMaker HyperPod task governance now supports fine-grained compute quota allocation of GPU, Trainium accelerator, vCPU, and vCPU memory within an instance. Administrators can allocate fine-grained compute quota across teams, optimizing compute resource distribution and staying within budget.\n Data scientists often execute LLM tasks, like training or inference, that do not require entire HyperPod instances, leading to underutilization of accelerated compute resources. HyperPod task governance enables administrators to manage compute quota allocation across teams. With this capability, administrators can now strategically allocate compute resources, ensuring fair access, preventing resource monopolization, and maximizing cluster utilization. This capability enables fine-grained compute quota allocation in addition to instance-level allocation, aligning with organizational workload demands. SageMaker HyperPod task governance is available in all AWS Regions where HyperPod is available: US East (N. Virginia), US West (N. California), US West (Oregon), Asia Pacific (Mumbai), Asia Pacific (Singapore), Asia Pacific (Sydney), and Asia Pacific (Tokyo), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Stockholm), and South America (São Paulo). To learn more, visit SageMaker HyperPod webpage, and HyperPod task governance documentation.
Amazon U7i instances now available in the AWS US East (Ohio) Region
Starting today, Amazon EC2 High Memory U7i instances with 12TB of memory (u7i-12tb.224xlarge) are now available in the US East (Ohio) region. U7i-12tb instances are part of AWS 7th generation and are powered by custom fourth generation Intel Xeon Scalable Processors (Sapphire Rapids). U7i-12tb instances offer 12TiB of DDR5 memory enabling customers to scale transaction processing throughput in a fast-growing data environment.\n U7i-12tb instances offer 896 vCPUs, support up to 100Gbps Elastic Block Storage (EBS) for faster data loading and backups, deliver up to 100Gbps of network bandwidth, and support ENA Express. U7i instances are ideal for customers using 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 EC2 R8g instances now available in AWS Asia Pacific (Jakarta)
Starting today, Amazon Elastic Compute Cloud (Amazon EC2) R8g instances are available in AWS Asia Pacific (Jakarta)region. These instances are powered by AWS Graviton4 processors and deliver up to 30% better performance compared to AWS Graviton3-based instances. Amazon EC2 R8g instances are ideal for memory-intensive workloads such as databases, in-memory caches, and real-time big data analytics. These instances are built on the AWS Nitro System, which offloads CPU virtualization, storage, and networking functions to dedicated hardware and software to enhance the performance and security of your workloads.\n AWS Graviton4-based Amazon EC2 instances deliver the best performance and energy efficiency for a broad range of workloads running on Amazon EC2. AWS Graviton4-based R8g instances offer larger instance sizes with up to 3x more vCPU (up to 48xlarge) and memory (up to 1.5TB) than Graviton3-based R7g instances. These instances are up to 30% faster for web applications, 40% faster for databases, and 45% faster for large Java applications compared to AWS Graviton3-based R7g instances. R8g instances are available in 12 different instance sizes, including two bare metal sizes. They offer up to 50 Gbps enhanced networking bandwidth and up to 40 Gbps of bandwidth to the Amazon Elastic Block Store (Amazon EBS). To learn more, see Amazon EC2 R8g Instances. To explore how to migrate your workloads to Graviton-based instances, see AWS Graviton Fast Start program and Porting Advisor for Graviton. To get started, see the AWS Management Console.
Amazon OpenSearch UI is now available in seven new regions
Amazon OpenSearch Service expands its modernized operational analytics experience to seven new regions, including Asia Pacific (Hyderabad), Asia Pacific (Osaka), Asia Pacific (Seoul), Europe (Milan), Europe (Zurich), Europe (Spain), and US-West (N. California) enabling users to gain insights across data spanning managed domains and serverless collections from a single endpoint. The expansion includes Workspaces to enhance collaboration and productivity, allowing teams to create dedicated spaces. Discover is revamped to provide a unified log exploration experience supporting languages such as Piped-Processing-Language (PPL) and SQL, in addition to DQL and Lucene. Discover now features a data selector to support multiple sources, new visual design and query autocomplete for improved usability. This experience ensures users can access the latest UI enhancements, regardless of version of underlying managed cluster or collection.\n The expanded OpenSearch analytics helps users gain insights from their operational data by providing purpose-built features for observability, security analytics, and search use cases. With the enhanced Discover interface, users can now analyze data from multiple sources without switching tools, improving efficiency. Workspaces enable better collaboration by creating dedicated environments for teams to work on dashboards, saved queries, and other relevant content. Availability of the latest UI updates across all versions ensures uninterrupted access to the newest features and tools. OpenSearch UI can connect to OpenSearch domains (above version 1.3) and OpenSearch serverless collections. It is now available in 22 AWS commercial regions. To get started, create an OpenSearch application in AWS Management Console. Learn more at Amazon OpenSearch Service Developer Guide.
PostgreSQL 18 Beta 3 is now available in Amazon RDS Database Preview Environment
Amazon RDS for PostgreSQL 18 Beta 3 is now available in the Amazon RDS Database Preview Environment, allowing you to evaluate the pre-release of PostgreSQL 18 on Amazon RDS for PostgreSQL. You can deploy PostgreSQL 18 Beta 3 in the Amazon RDS Database Preview Environment that has the benefits of a fully managed database.\n PostgreSQL 18 includes “skip scan” support for multicolumn B-tree indexes and improves WHERE clause handling for OR and IN conditions. It introduces parallel GIN index builds and updates join operations. Observability improvements show buffer usage counts and index lookups during query execution, along with per-connection I/O utilization metric. Please refer the RDS PostgreSQL release documentation 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.
SageMaker HyperPod now supports Topology Aware Scheduling of LLM tasks
SageMaker HyperPod task governance now supports Topology Aware Scheduling (TAS), enabling data scientists to schedule their large language model (LLM) tasks on an optimal network topology that minimizes network communication and enhances training efficiency.\n LLM training and fine-tuning tasks that are distributed across multiple accelerated compute instances frequently exchange large volumes of data between them. Multiple network hops between instances can result in higher communication latency, impacting LLM task performance. SageMaker HyperPod task governance now enables data scientists to use network topology information when scheduling tasks with specific topology preferences. Using network topology in HyperPod, SageMaker HyperPod task governance automatically schedules tasks in optimal locations, reducing instance-to-instance communication and enhancing training efficiency.
SageMaker HyperPod task governance is available in all AWS Regions where HyperPod is available: US West (N. California), US West (Oregon), Asia Pacific (Singapore), Asia Pacific (Sydney), Europe (Frankfurt), Europe (Ireland), Europe (Stockholm). To learn more, visit SageMaker HyperPod webpage, and SageMaker HyperPod task governance documentation.
Amazon EC2 I7ie instances are now available in additional AWS regions
Amazon Web Services (AWS) announces the availability of Amazon EC2 I7ie instances in the AWS Europe (Stockholm), Asia Pacific (Jakarta), and US West (N. California) regions. Designed for large storage I/O intensive workloads, these new instances are powered by 5th generation Intel Xeon Scalable processors with an all-core turbo frequency of 3.2 GHz, offering up to 40% better compute performance and 20% better price performance over previous generation I3en instances.\n I7ie instances offer up to 120TB local NVMe storage density—the highest available in the cloud for storage optimized instances—and deliver up to twice as many vCPUs and memory compared to prior generation instances. Powered by 3rd generation AWS Nitro SSDs, these instances achieve up to 65% better real-time storage performance, up to 50% lower storage I/O latency, and 65% lower storage I/O latency variability compared to I3en instances. Additionally, torn write prevention feature support up to 16KB block sizes, enables customers to eliminate performance bottlenecks for database workloads. I7ie instances are high-density storage-optimized instances, for workloads that demand rapid local storage with high random read/write performance and consistently low latency for accessing large data sets. These instances are offered in eleven different sizes including 2 metal sizes, providing flexibility for customers computational needs. They deliver up to 100 Gbps of network performance bandwidth, and 60 Gbps of dedicated bandwidth for Amazon Elastic Block Store (EBS), ensuring fast and efficient data transfer for applications. To learn more, visit the I7ie instances page.
AWS Batch now supports AWS Graviton-based Spot compute with AWS Fargate
AWS Batch for ECS Fargate now supports AWS Graviton-based compute with AWS Fargate Spot. This capability helps you run fault-tolerant Arm-based applications with up to 70% discount compared to Fargate prices. AWS Graviton processors are custom-built by AWS to deliver the best price-performance for cloud workloads.\n AWS Batch for ECS Fargate enables customers to deploy and build workloads at scale in a serverless manner. Starting today, customers can further optimize for costs by running fault-tolerant Arm-based workloads on AWS Fargate Spot. To get started, create a new Fargate configured Compute Environment (CE), select ARM64 as the cpuArchitecture, and choose FARGATE_SPOT as the type. You can then connect it to existing job queues or create a new one for your workload. AWS Batch will leverage spare AWS Graviton-based compute capacity available in the AWS cloud for running your service or task. You can now get the simplicity of serverless compute with familiar cost optimization levers of Spot capacity with Graviton-based compute. This capability is now available for AWS Batch in all commercial and the AWS GovCloud (US) Regions. To learn more, see Batch’s updated RuntimePlatform API and AWS Batch for ECS Fargate documentation.
Amazon FSx for NetApp ONTAP now supports decreasing your SSD storage capacity
Amazon FSx for NetApp ONTAP, a fully managed shared storage service built on NetApp’s popular ONTAP file system, now allows you to decrease your file system’s solid-state drive (SSD) storage capacity, enabling you to more efficiently run project-based workloads with varying active working sets. You can provision SSD capacity upfront to meet peak usage needs—for periodic reporting, analytics, or large-scale data ingestion and processing—and then easily decrease SSD capacity to reduce storage costs.\n An FSx for ONTAP file system offers two storage tiers: a provisioned high-performance SSD tier for your workload’s active working set and a fully elastic capacity pool cost-optimized for infrequently accessed data. Until now, you could only increase your file system’s SSD capacity as your workload’s active working set grew. Starting today, you can decrease your file system’s SSD capacity in-place with just a few clicks in the Amazon FSx console, allowing you to deliver optimal performance during peak usage for workloads such as Electronic Design Automation and media processing, then scale down SSD capacity once data processing is complete. You can also accelerate data migrations by temporarily increasing SSD capacity to enable faster data ingestion, then right-sizing SSD capacity after data has been tiered to the capacity pool. You can decrease SSD storage capacity on all FSx for ONTAP second-generation file systems in all AWS Regions where FSx for ONTAP second-generation file systems are available. For more information, see the FSx for ONTAP user guide.
AWS Cloud Map adds support for cross-account service discovery
AWS Cloud Map now supports cross-account service discovery through integration with AWS Resource Access Manager (AWS RAM). This enhancement lets you seamlessly manage and discover cloud resources—such as Amazon ECS tasks, Amazon EC2 instances, and Amazon DynamoDB tables—across AWS accounts. By sharing your AWS Cloud Map namespace via AWS RAM, workloads in other accounts can discover and manage resources registered in that namespace. This enhancement simplifies resource sharing, reduces duplication, and promotes consistent service discovery across environments for organizations with multi-account architectures.\n You can now share your AWS Cloud Map namespaces using AWS RAM with individual AWS accounts, specific Organizational Units (OUs), or your entire AWS Organization. To get started, create a resource share in AWS RAM, add the namespaces you want to share, and specify the principals (accounts, OUs, or the organization) that should have access. This enables platform engineers to maintain a centralized service registry—or a small set of registries—and share them across multiple accounts, simplifying service discovery. Application developers can then build services that rely on a consistent, shared registry without worrying about availability or synchronization across accounts. AWS Cloud Map’s cross-account service discovery support improves operational efficiency and makes it easier to scale service discovery as your organization grows by reducing duplication and streamlining access to namespaces. This feature is available now in all commercial AWS Regions via the AWS Management Console, API, SDK, CLI, and CloudFormation. To learn more, please refer to the AWS Cloud Map documentation.
Amazon Braket introduces support for program sets
Amazon Braket now supports program sets, enabling quantum researchers to run complex workloads requiring hundreds of quantum circuit executions up to 24X faster. This new feature allows customers to submit up to 100 quantum programs or a single parametric circuit with up to 100 parameter values within a single quantum task. Program sets help minimize the time between subsequent circuit executions reducing quantum task processing overhead for complex algorithms.\n Program sets are particularly valuable for researchers working with variational quantum algorithms (VQA), quantum machine learning models, and error mitigation techniques. Customers can create program sets using two approaches: submitting multiple independent circuits together, or submitting a single parametric circuit with parameter sets. Amazon Braket handles compilation and execution orchestration, returning results that include the status and outcomes for each quantum program. If individual programs within a program set fail during execution, customers receive partial results for successfully completed programs and error information for failed executions. When submitting a program set, you pay a single per-task fee accompanied by a per-shot fee based on the total number of successful shots across your workload in a program set. Program sets are initially available on all superconducting quantum processing units (QPUs) from Rigetti in the US West (N. California) Region and IQM in the Europe (Stockholm) Region. Customers are able to submit program sets to Braket directly via the Amazon Braket SDK, from Qiskit via the Qiskit-Braket provider, or from PennyLane via the Amazon Braket PennyLane Plugin. To learn more about program sets, visit the Amazon Braket developer guide, explore our new example notebooks, and visit our updated Amazon Braket management console.
Amazon RDS for PostgreSQL supports minor versions 17.6, 16.10, 15.14, 14.19, and 13.22
Amazon Relational Database Service (RDS) for PostgreSQL now supports the latest minor versions 17.6, 16.10, 15.14, 14.19, and 13.22. We recommend that you upgrade to the latest minor versions to fix known security vulnerabilities in prior versions of PostgreSQL, and to benefit from the bug fixes added by the PostgreSQL community. This release also includes updates for PostgreSQL extensions such as pg_repack 1.5.2, oracle_fdw 2.8.0, and pgactive 2.1.5\n You can use automatic minor version upgrades to automatically upgrade your databases to more recent minor versions during scheduled maintenance windows. You can also use Amazon RDS Blue/Green deployments for RDS for PostgreSQL using physical replication for your minor version upgrades. Learn more about upgrading your database instances, including automatic minor version upgrades and Blue/Green Deployments in the Amazon RDS User Guide . Amazon RDS for PostgreSQL makes it simple to set up, operate, and scale PostgreSQL deployments in the cloud. See Amazon RDS for PostgreSQL Pricing for pricing details and regional availability. Create or update a fully managed Amazon RDS database in the Amazon RDS Management Console.
Amazon Q Business launches Agentic RAG to enhance accuracy and explainability
Amazon Q Business, the generative AI-powered assistant for finding information, gaining insight, and taking action at work, today introduced Agentic Retrieval-Augmented Generation (RAG) for Q Business applications. The new feature significantly enhances the ability of Q Business to provide more accurate and explainable responses to complex, multi-step RAG queries.\n Using Agentic RAG, Q Business uses AI agents to dynamically plan the retrieval and response generation for user’s queries that target enterprise data. Agentic RAG breaks down complex queries into simpler ones, executes them in parallel to retrieve data, intelligently invokes data retrieval tools, and combines the data to generate comprehensive responses. The built-in AI agents critique and validate the responses, and retry retrievals if necessary, resulting in higher accuracy. Through Agentic RAG, Q Business delivers a more intuitive dialogue experience, proactively resolving data conflicts through targeted clarifying questions and maintaining momentum with contextually relevant follow-ups – all while keeping users informed of the actions that Q Business takes. Agentic RAG is available in all AWS Regions where Amazon Q Business is offered. For any of their queries targeting their company knowledge, users can leverage this feature by toggling the “Advanced Search” option in the built-in web application. For more details, refer to the documentation. For more information about Amazon Q Business and its features, please visit the Amazon Q product page.
AWS Config now supports 10 new resource types
AWS Config now supports 10 additional AWS resource types. This expansion provides greater coverage over your AWS environment, enabling you to more effectively discover, assess, audit, and remediate an even broader range of resources.\n With this launch, if you have enabled recording for all resource types, then AWS Config will automatically track these new additions. The newly supported resource types are also available in Config rules and Config aggregators. You can now use AWS Config to monitor the following newly supported resource types in all AWS Regions where the supported resources are available:
Resource Types:
AWS::Backup::RestoreTestingPlan
AWS::CloudFront::RealtimeLogConfig
AWS::EC2::SecurityGroupVpcAssociation
AWS::EC2::VerifiedAccessInstance
AWS::KafkaConnect::CustomPlugin
AWS::OpenSearchServerless::SecurityConfig
AWS::Redshift::Integration
AWS::Route53Profiles::ProfileAssociation
AWS::SSMIncidents::ResponsePlan
AWS::Transfer::Server
AWS Systems Manager Automation enhances runbook execution control and updates free tier
AWS Systems Manager Automation now offers three new features that enhance runbook execution control and success rates. Additionally, we are announcing updates to our free tier structure, as part of our ongoing commitment to providing simple, standardized, and cost-effective services to customers.\n There are three key features added. First, customers can now easily re-execute runbooks directly from the Automation console with pre-populated parameters, streamlining repeated operations. Second, customers will be able to automatically retry throttled API calls during high-concurrency scenarios to improve execution reliability. Lastly, customers will be able to specify nested organizational units (OUs) in their target selection for more fine-grained control over their resources across accounts. Additionally, the existing free tier for Automation (100,000 steps and 5,000 seconds of script duration per month) will no longer be available for new customers and will end on December 31, 2025 for existing customers. Customers can try Automation capabilities for free by starting a new AWS account under a free plan, where they can use up to $200 in Free Tier credits on eligible AWS Services. Automation pricing remains the same at $0.002 per step executed and $0.00003 per second of scripts executed. Systems Manager Automation is available in all AWS Commercial and AWS GovCloud (US) Regions. To learn more about Automation, review the documentation and Systems Manager pricing page. For more details on available plans on new customer benefits, visit the AWS Free Tier page.
Accelerate Amazon WorkSpaces deployment with streamlined Bring Your Own License (BYOL) process
WorkSpaces has improved the BYOL process, offering customers a more efficient and faster way to import their Windows images to use with WorkSpaces. With this streamlined approach, customers can enable the BYOL feature in their AWS account without contacting AWS Support.\n The new process supports importing either customized virtual machine (VM) images or Windows ISO files directly into WorkSpaces. Leveraging an integrated Amazon EC2 Image Builder pipeline, the system automatically constructs a WorkSpaces-compatible image from the imported source. During this process, most compatibility issues are identified and resolved automatically, reducing the manual troubleshooting efforts previously required. In cases where compatibility issues cannot be fixed automatically, customers now have the ability to access an EC2 instance to address these issues directly. This eliminates the need to upload a new image, further streamlining the import process. These improvements collectively reduce the overall time needed to get started with BYOL images on WorkSpaces, while minimizing the associated troubleshooting efforts. The improved BYOL process is available in all regions where WorkSpaces BYOL is currently available. To learn more, see the Amazon WorkSpaces BYOL documentation.
Amazon EC2 M8g instances now available in AWS Asia Pacific (Seoul)
Starting today, Amazon Elastic Compute Cloud (Amazon EC2) M8g instances are available in AWS Asia Pacific (Seoul) region. These instances are powered by AWS Graviton4 processors and deliver up to 30% better performance compared to AWS Graviton3-based instances. Amazon EC2 M8g instances are built for general-purpose workloads, such as application servers, microservices, gaming servers, midsize data stores, and caching fleets. These instances are built on the AWS Nitro System, which offloads CPU virtualization, storage, and networking functions to dedicated hardware and software to enhance the performance and security of your workloads.\n AWS Graviton4-based Amazon EC2 instances deliver the best performance and energy efficiency for a broad range of workloads running on Amazon EC2. These instances offer larger instance sizes with up to 3x more vCPUs and memory compared to Graviton3-based Amazon M7g instances. AWS Graviton4 processors are up to 40% faster for databases, 30% faster for web applications, and 45% faster for large Java applications than AWS Graviton3 processors. M8g instances are available in 12 different instance sizes, including two bare metal sizes. They offer up to 50 Gbps enhanced networking bandwidth and up to 40 Gbps of bandwidth to the Amazon Elastic Block Store (Amazon EBS). To learn more, see Amazon EC2 M8g Instances. To explore how to migrate your workloads to Graviton-based instances, see AWS Graviton Fast Start program and Porting Advisor for Graviton. To get started, see the AWS Management Console.
AWS Security Incident Response now allows you to choose membership coverage for specific AWS organizational units (OUs) within an AWS Organization. While memberships previously covered all accounts in the selected AWS Organization, you now have the flexibility to choose which OUs to cover making it easier to try out the service and support your existing IR processes. \n AWS Security Incident Response combines the power of automated monitoring and investigation, accelerated communication and coordination, and direct 24/7 access to the AWS Customer Incident Response Team (CIRT) to quickly prepare for, respond to, and recover from security events. This new feature allows you to enable Security Incident Response for specific types of workloads, such as production workloads, or for specific business subsidiaries that are grouped as OUs in their AWS Organization. You can also start with a pilot OU to evaluate the service’s effectiveness and refine processes before expanding coverage to your entire AWS Organization. All accounts within the selected OUs, including accounts under child OUs, are covered by the membership. Accounts added or removed from selected OUs will automatically update the coverage, making it easy for you to manage your AWS Security Incident Response membership.
Get started today by visiting AWS Security Incident Response via the AWS Management Console, AWS Command Line Interface (CLI), or AWS Software Development Kit (SDK). To learn more, see the AWS Security Incident Response documentation. For additional information on managing OUs with AWS Organizations, visit the AWS Organizations page.
AWS Blogs
AWS Japan Blog (Japanese)
AWS Architecture Blog
- How Karrot built a feature platform on AWS, Part 1: Motivation and feature serving
- How Karrot built a feature platform on AWS, Part 2: Feature ingestion
- Deploy LLMs on Amazon EKS using vLLM Deep Learning Containers
AWS Big Data Blog
- Cluster manager communication simplified with Remote Publication
- Enhance Amazon EMR observability with automated incident mitigation using Amazon Bedrock and Amazon Managed Grafana
AWS Compute Blog
AWS Contact Center
Artificial Intelligence
- Scalable intelligent document processing using Amazon Bedrock Data Automation
- Whiteboard to cloud in minutes using Amazon Q, Amazon Bedrock Data Automation, and Model Context Protocol
- Bringing agentic Retrieval Augmented Generation to Amazon Q Business
- Empowering students with disabilities: University Startups’ generative AI solution for personalized student pathways
- Citations with Amazon Nova understanding models