8/3/2026, 12:00:00 AM ~ 8/4/2026, 12:00:00 AM (UTC)

Recent Announcements

Amazon GameLift Streams now supports sharing streams with stream URLs

Amazon GameLift Streams now offers stream URLs, which give end users temporary, unauthenticated access to a playable stream session in a supported web browser. Recipients need no AWS account, no credentials, and no software install.\n To share a playable stream, create a stream URL for a stream group and one of its applications, set how long the stream URL stays valid and how many sessions it can start, and send the link. Each person who opens the link starts an independent stream session, and Amazon GameLift Streams routes them to a nearby streaming location from the locations you selected. No client integration or backend service is required. You can create, monitor, and revoke stream URLs in the Amazon GameLift Streams console or with the new CreateStreamUrl, GetStreamUrl, ListStreamUrls, and RevokeStreamUrl APIs.

There is no additional charge for stream URLs. You are charged for the stream capacity that sessions started from a stream URL consume, as described on the Amazon GameLift Streams pricing page. For a full list of supported Regions, see the AWS Region table.

To get started, see Share stream sessions with stream URLs in the Amazon GameLift Streams Developer Guide and the CreateStreamUrl API Reference. To learn more about the service, see the Amazon GameLift Streams product page.

AWS HealthOmics now supports task-level timeout for WDL workflows

AWS HealthOmics now supports task-level timeout for Workflow Description Language (WDL) workflows, enabling you to set maximum execution duration for individual tasks. AWS HealthOmics is a HIPAA-eligible service that helps healthcare and life sciences customers accelerate scientific breakthroughs at scale with fully managed bioinformatics workflows. \n With task-level timeout, you can define time bounds on individual WDL tasks to control costs and enable automated error recovery. HealthOmics provides the omicsTimeout runtime attribute that you can add to any task’s runtime section to specify the maximum duration a task is allowed to run. When a task exceeds the specified duration, HealthOmics stops the task and sets the task and run statuses to failed. The omicsTimeout attribute accepts duration values with standard time units (such as 90s, 2h, 1d). This prevents tasks from consuming resources and helps you set cost guardrails during workflow development. 

Task-level timeout for WDL workflows is available in all supported AWS HealthOmics Regions: US East (N. Virginia, Ohio), US West (Oregon), Europe (Frankfurt, Ireland, London), Israel (Tel Aviv), and Asia Pacific (Seoul, Singapore, Tokyo). To learn more, visit the WDL workflow definition specifics documentation.

AWS Resilience Hub now provides recommended resilience tests

AWS Resilience Hub now offers recommended resilience tests that help platform engineering and site reliability teams validate how their services respond to and recover from known failure scenarios. \n Resilience Hub provides pre-configured tests based on your service’s architecture, configuration, and resilience policy. It uses AWS Fault Injection Service (FIS) to inject controlled faults and then evaluates whether your service recovers within your defined recovery objectives. With the AWS-recommended resilience tests, teams can validate readiness for scenarios such as Availability Zone impairment, Regional impairment, and dependency failure. Each test automatically targets resources in the service, injects the required faults, produces a pass or fail outcome based on alarm evaluation and recovery objectives, then generates a detailed test report.

The recommended testing on the next generation of the AWS Resilience Hub is available in the following AWS Regions: US East (N. Virginia), US East (Ohio), US West (Oregon), Canada (Central), Europe (Ireland), Europe (London), Europe (Frankfurt), Europe (Paris), Europe (Stockholm), Asia Pacific (Mumbai), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Asia Pacific (Seoul), and South America (São Paulo).

To get started, visit the AWS console. To learn more about recommended resilience testing see the product page for the next generation of AWS Resilience Hub.

Amazon EC2 I7i instances now available in Asia Pacific (Thailand) and Israel (Tel Aviv) Regions

Amazon Web Services (AWS) announces the availability of high performance Storage Optimized Amazon EC2 I7i instances in the Asia Pacific (Thailand) and Israel (Tel Aviv) Regions. Powered by 5th Gen Intel Xeon Processors with an all-core turbo frequency of 3.2 GHz, these new instances deliver up to 23% better compute performance and more than 10% better price performance over previous generation I4i instances. Powered by 3rd generation AWS Nitro SSDs, I7i instances offer up to 45TB of NVMe storage with up to 50% better real-time storage performance, up to 50% lower storage I/O latency, and up to 60% lower storage I/O latency variability compared to I4i instances.\n I7i instances offer compute and storage performance for x86-based storage optimized instances in Amazon EC2 ideal for I/O intensive and latency-sensitive workloads that demand very high random IOPS performance with real-time latency to access the small to medium size datasets. Additionally, torn write prevention feature support up to 16KB block sizes, enabling customers to eliminate database performance bottlenecks. I7i instances are available in eleven sizes - nine virtual sizes up to 48xlarge and two bare metal sizes - delivering up to 100Gbps of network bandwidth and 60Gbps of Amazon Elastic Block Store (EBS) bandwidth. To learn more, visit the I7i instances page.

Amazon SageMaker AI serverless model customization now supports full fine-tuning

Amazon SageMaker AI serverless model customization now supports full fine-tuning for over 25 open-source models. These include popular models from gpt-oss, Gemma, Llama, Nemotron, and Qwen model families. In addition to parameter-efficient methods such as LoRA, which update a small subset of model weights, you can now update all parameters in the model for deeper adaptation when your use case requires it.\n Full fine-tuning allows the model to more thoroughly learn your domain-specific patterns, terminology, and task structure. This is particularly valuable when you need the model to acquire capabilities beyond surface-level style adjustments, such as learning specialized reasoning patterns, adopting complex output formats, or internalizing domain knowledge from large proprietary datasets. With serverless model customization, SageMaker manages all infrastructure provisioning and training orchestration, so you can run full fine-tuning jobs without provisioning or managing any infrastructure and you pay only for what you use. Serverless full fine-tuning on SageMaker is available in US East (N. Virginia), US West (Oregon), Asia Pacific (Tokyo), and Europe (Ireland). To get started, navigate to the JumpStart and Models page in Amazon SageMaker Studio to launch a customization job, or use the SageMaker Python SDK. To learn more, and see the supported list of models, see the Amazon SageMaker AI model customization documentation.

AWS Transform for full-stack Windows modernization now supports offline schema transformation to Aurora PostgreSQL

Today, AWS Transform for full-stack Windows modernization announced general availability of offline source transformation, enabling customers to modernize Microsoft SQL Server databases to Amazon Aurora PostgreSQL without requiring a live database connection. AWS Transform now converts SQL Server storage objects, powered by AWS DMS, and code objects (stored procedures) using an agentic, interactive experience. Enterprises modernizing legacy .NET applications and their dependent SQL Server databases can now start their modernization by directly uploading the Data Design Language (DDL) source files from their databases.\n With offline source transformation, customers upload SQL Server data design language (DDL) files, assess database and stored procedure complexity, and generate a customizable transformation plan. AWS Transform converts tables, schemas and converts code objects such as stored procedures and functions, validates functional equivalence, and deploys the converted schema to Aurora PostgreSQL. The same workflow transforms database dependent .NET applications to be PostgreSQL compatible .NET applications with updated connection strings, ADO.NET and Entity Framework data-access calls. To address remaining conversion issues, customers can iterate directly in the web console or hand off to their preferred IDE using the AWS Transform MCP server. A separate synthetic data workflow populates Aurora PostgreSQL with test data for end-to-end application validation.

AWS Transform for full-stack Windows modernization and offline source transformation is available in US East (N. Virginia). To get started, you can go to AWS Transform product page or see AWS Transform for full-stack Windows documentation.

AWS WAF now supports Miggo Security managed rule groups for emerging threats and AI/ML application protection

AWS WAF now supports two new partner managed rule groups from Miggo Security, available through AWS Marketplace: Miggo Rules for AWS WAF – High Emerging Application Threats, and Miggo Rules for AWS WAF – AI/ML Application Protection. These rule groups give AWS WAF customers continuously updated protection against vulnerabilities that are being actively exploited, have public proof-of-concept code, or appear in the CISA Known Exploited Vulnerabilities (KEV) catalog, without writing or maintaining custom rules.\n The High Emerging Application Threats rule group focuses on vulnerabilities under active exploitation, and the AI/ML Application Protection rule group focuses on generative-AI application stacks such as AI agent frameworks, LLM gateways, and model-serving infrastructure. You can subscribe to either rule group and add it to a web ACL directly in the AWS WAF console through AWS Marketplace, with no additional configuration. Both rule groups support versioning, and pricing is set by Miggo through AWS Marketplace. To get started, visit the AWS WAF console or find the Miggo rule groups in AWS Marketplace. For more information, see the AWS WAF Developer Guide. For a full list of supported Regions, visit the AWS Regional Services page.

AWS Config now supports 15 new resource types

AWS Config now supports 15 additional AWS resource types across key services including Amazon Bedrock,  Amazon OpenSearch Serverless, and Amazon SageMaker. 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 resources are available: Resource Types:

AWS::AppSync::DomainName AWS::OpenSearchServerless::AccessPolicy

AWS::Bedrock::AutomatedReasoningPolicy AWS::OpenSearchServerless::LifecyclePolicy

AWS::Bedrock::AutomatedReasoningPolicyVersion AWS::SageMaker::ImageVersion

AWS::Bedrock::Blueprint AWS::SageMaker::InferenceComponent

AWS::Bedrock::DataAutomationProject AWS::SageMaker::PartnerApp

AWS::BedrockAgentCore::ApiKeyCredentialProvider AWS::SageMaker::Project

AWS::Connect::UserHierarchyGroup AWS::SageMaker::Space

AWS::Glue::Trigger

Amazon ECR now supports image layers up to 200 GB

Amazon Elastic Container Registry (Amazon ECR) has increased the maximum image layer size limit to 200 GB, for images pushed via Docker push.\n Previously, packaging assets required splitting data across multiple layers or offloading to external storage systems. With this update, customers can store up to 200 GB in a single image layer, eliminating extra complexity for use cases like embedding large language models, bundling genomics datasets, or packaging large binary dependencies directly into your container images. Images pushed using the AWS SDK or CLI; (UploadLayerPartAPI) remain limited to 50 GB.

This feature is available in all AWS Regions and partitions where Amazon ECR is available except the Middle East (Bahrain) and Middle East (UAE) Regions. To learn more, visit the Amazon ECR product page and refer to the Amazon ECR User Guide. For pricing information, see the Amazon ECR pricing page.

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