AWS Releases
Amazon Web Services releases and Terraform AWS provider. New features, breaking changes, security advisories and deprecations - each summarised in plain English and updated continuously.
Tracking 680 AWS releases · Updated
- AWS What's New aiawsengineeraws-ec2aws-sagemaker ·
SageMaker Notebook Instances Add P5.4xl Instance Support
Amazon SageMaker notebook instances now support EC2 P5.4xl instances, featuring NVIDIA H100 GPUs for accelerated deep learning and HPC workloads. This enhancement can improve training times by up to 4x and reduce costs by up to 40%, benefiting engineers and data scientists working with large language models and generative AI applications. P5 instances are available in select AWS regions, with setup instructions provided in developer guides.
feature - AWS What's New aiawsengineeraws-ec2aws-sagemaker ·
SageMaker Notebook Instances add P5en.48xl instance types
Amazon SageMaker notebook instances now support the new EC2 P5en.48xl instance types, featuring H200 GPUs with enhanced memory and bandwidth. This upgrade significantly boosts AI training and inference performance, particularly for distributed workloads like deep learning and generative AI. These instances are now available in select AWS regions and are designed for users running demanding AI and HPC applications.
feature - AWS What's New aiawsengineer ·
Amazon Connect uses generative AI for automated self-service interaction evaluation
Amazon Connect now integrates generative AI to automatically evaluate self-service customer interactions, providing managers with aggregated insights for improving customer experience. Users can define custom evaluation criteria in natural language, and the AI will assess interaction quality, offering detailed reasoning. This feature is available in select AWS regions and aims to help identify opportunities for enhancing AI agent performance.
feature - AWS What's New aiawsengineeraws-sagemaker ·
SageMaker HyperPod adds MinCount for Slurm clusters
Amazon SageMaker HyperPod now allows users to specify minimum capacity requirements (MinCount) for Slurm-orchestrated clusters using continuous provisioning. This enhancement ensures distributed AI/ML training jobs start with a guaranteed number of nodes, preventing issues with partial cluster capacity. This feature is available in all AWS Regions where SageMaker HyperPod is supported and is particularly beneficial for large-scale distributed training.
feature - AWS What's New aiawsengineeraws-rds ·
Amazon Aurora MySQL integrates with Kiro Powers for AI-assisted development
Amazon Aurora MySQL now integrates with Kiro Powers, a repository of AI agent tools, to help developers build applications faster. This integration offers conversational control over database operations and configuration, reducing the need for complex syntax. It provides task-specific guidance for scaling, migration, and replication, and is available via one-click installation in all AWS Regions where Aurora MySQL is supported.
feature announcement - AWS What's New aiawsengineeraws-sagemakeraws-iam ·
SageMaker Unified Studio expands domain management for Identity Center domains
Amazon SageMaker Unified Studio now offers domain management for Identity Center-based domains outside the AWS console, enabling administrators to manage projects, workforce identity, and networking. This expands capabilities previously limited to IAM-based domains, improving unified administration. These features are available in all regions where SageMaker Unified Studio is supported.
feature - AWS What's New aiawsengineermediaaws-sagemaker ·
SageMaker Inference Supports OpenAI-Compatible APIs
Amazon SageMaker Inference now supports OpenAI-compatible APIs, allowing direct integration with tools like OpenAI SDK and LangChain by simply changing the endpoint URL. This feature simplifies connecting to SageMaker endpoints, enabling users to leverage existing code and authentication with custom models and VPCs. It offers flexibility in instance choice, data privacy, model execution, and autoscaling, with authentication managed via AWS credentials. The capability is available today in multiple AWS regions.
feature announcement - AWS What's New aiawsgaengineeraws-bedrockaws-iam ·
Amazon Bedrock adds request-level usage attribution
Amazon Bedrock now supports request-level usage attribution for InvokeModel and InvokeModelWithResponseStream APIs, allowing granular tracking of inference usage across teams and applications. This enhancement provides deeper visibility into consumption patterns, aids cost optimization, and simplifies internal reporting without requiring new resources. The feature is available in all Amazon Bedrock commercial regions and builds upon existing attribution capabilities.
feature - AWS What's New aiawsengineeraws-s3aws-eksaws-sagemaker ·
SageMaker HyperPod adds data capture for inference workloads
Amazon SageMaker HyperPod now supports data capture for inference workloads, recording request and response payloads to Amazon S3. This feature provides crucial visibility for generative AI deployments, enabling drift detection, troubleshooting, and model improvement without custom logging pipelines. It is available for SageMaker HyperPod clusters using the EKS orchestrator in all supported AWS Regions.
feature - AWS What's New aiawsengineeraws-sagemaker ·
SageMaker Studio IDEs support GPU capacity reservation
Amazon SageMaker Studio IDEs now support GPU capacity reservations via SageMaker Flexible Training Plans (FTP). This provides predictable access to high-performance GPU resources with potential cost savings of up to 65% compared to On-Demand instances. The feature is available for users running ML workflows in JupyterLab or Code Editor within Studio, offering a self-serve procurement experience.
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About AWS release tracking on ReleaseBytes
AWS ships hundreds of service updates a month across EC2, Lambda, RDS, S3, EKS and the rest of the catalogue — far more than anyone can follow by reading the official What's New feed. ReleaseBytes ingests announcements from AWS's official release channels and the Terraform AWS provider changelog, summarises each one in plain English, and tags anything that is a breaking change, security advisory or deprecation so you can see at a glance whether it affects your workloads.
Frequently asked questions
How often are AWS release notes updated on ReleaseBytes? ›
Continuously. ReleaseBytes monitors the official AWS release channels around the clock and publishes a plain-English summary of each announcement shortly after it lands.
What kinds of AWS changes does ReleaseBytes track? ›
New features, enhancements, bug fixes, security advisories, breaking changes, deprecations and end-of-life announcements. Every item is tagged by type so you can filter to just the changes that need action.
How can I get alerts for new AWS releases? ›
Set up a free email or Slack alert filtered to AWS, subscribe to the weekly digest, or follow the RSS feed. Teams can also install the ReleaseBytes GitHub App or connect via MCP.
Where does the AWS release data come from? ›
From the official sources: Amazon Web Services releases and Terraform AWS provider. Every item links back to the original vendor announcement.