Monat: Oktober 2026

Amazon EKS Auto Mode now supports Kubernetes Gateway API

Amazon EKS Auto Mode now supports the Kubernetes Gateway API, giving customers a standard, portable way to define how traffic reaches their applications. Customers can configure application load balancing using Gateway and HTTPRoute resources, and EKS Auto Mode provisions and manages the underlying AWS infrastructure automatically.
With this launch, EKS Auto Mode customers can adopt the next-generation Kubernetes traffic management standard without installing or configuring a separate controller. Capabilities include HTTP and gRPC routing, cross-namespace traffic routing for multi-team environments, weighted traffic splitting, header-based routing, and automatic TLS certificate discovery through AWS Certificate Manager. Existing workloads using Ingress resources continue to work alongside Gateway API resources.
To get started, see the Amazon EKS documentation. Gateway API support is included as part of EKS Auto Mode and is available in all AWS Regions where EKS Auto Mode is supported. Standard charges apply for the AWS load balancing resources provisioned.
Quelle: aws.amazon.com

AWS Lambda supports Seekable OCI (SOCI) lazy loading for Lambda Managed Instances

AWS Lambda now supports Seekable OCI (SOCI) for lazy loading Event Functions packaged as Open Container Initiative (OCI) images running on Lambda Managed Instances. With SOCI support, Lambda fetches only the files needed at each stage of the execution environment startup rather than downloading the entire image upfront, reducing container startup times by up to 70%.
Customers building compute-intensive applications such as data processing pipelines, high-throughput API backends, and batch computation workloads require substantial memory and CPU resources to process large datasets, serve low-latency responses at scale, and run complex computations efficiently. Container images for these workloads can reach several gigabytes, and downloading and preparing the full image can take several minutes when provisioning new execution environments. SOCI support on Lambda Managed Instances eliminates this bottleneck by streaming only the required files at each stage of the execution environment startup, so your functions start faster as you scale.
To get started, create a SOCI index (a table of contents for the files in your image layers) for your container image and push it to Amazon ECR. When creating or updating your function, set the image URI to the SOCI-indexed tag in Amazon ECR (for example, my-function:v1-soci) and publish a function version. Lambda automatically detects the SOCI index and enables lazy loading with no additional configuration. If you use a coding assistant such as Kiro, Claude Code, or Codex, install the Lambda Managed Instances skill from the Agent Toolkit for AWS to configure and deploy functions through your agent.
The feature is available in all AWS commercial Regions where Lambda Managed Instances is available. To learn more, visit the AWS Lambda Managed Instances developer guide. 
Quelle: aws.amazon.com

Amazon ElastiCache for Valkey now supports changing durability on existing clusters

Amazon ElastiCache for Valkey now lets you enable or disable durability on your existing node-based clusters without creating a new cluster. Previously, you couldn’t change the durability configuration of an existing cluster in place. This made it harder to move from caching to persistent data store use cases, or to adapt as your application requirements change. Now you can change durability at any point in your application’s lifecycle.
You can choose between two durability options: synchronous and asynchronous writes. Synchronous writes persist data across at least two AZs before responding to the client, designed for zero data loss at single-digit millisecond write latency. Asynchronous writes persist data after responding to the client, maintaining microsecond write latency at no additional cost. However, up to 10 seconds of uncommitted data could be lost in the rare event of a failure. Both options maintain microsecond read latency. You can now use ElastiCache for a broader set of use cases beyond caching where data loss is unacceptable such as AI agent long-term memory, AI agent workflow state, knowledge bases for RAG applications, payment tokenization, and real-time inventory management.
This feature is available in all AWS Regions where ElastiCache for Valkey 9.0 and later is available. To get started, use the AWS Management Console, AWS SDK, or AWS CLI. For pricing, see the  Amazon ElastiCache pricing page . To learn more, see  Durability  in the ElastiCache documentation.
Quelle: aws.amazon.com

Amazon Aurora serverless now supports up to 384 ACUs

Amazon Aurora serverless now supports database capacity of up to 384 Aurora Capacity Units (ACUs) for Aurora PostgreSQL-Compatible Edition, a 50% increase from the previous maximum of 256 ACUs. Each ACU provides approximately 2 gibibytes (GiB) of memory with corresponding CPU and networking, so a single Aurora serverless database can now scale up to 768 GiB of memory. When the workload completes, Aurora serverless automatically scales down to zero. This makes Aurora serverless especially well-suited for agentic AI applications, which typically have bursts of activity, long idle windows, and unpredictable traffic patterns. Aurora serverless handles all of it automatically, scaling capacity with your agents, so you only pay for what you use.
With 384 ACU support, customers can now use Aurora serverless for even more demanding workloads while continuing to scale down to zero when not in use, paying only for the capacity consumed. For new clusters, select a supported Aurora PostgreSQL engine version and set your maximum capacity up to 384 ACUs. For existing clusters on Platform Version 4, simply modify the cluster to update the maximum capacity setting (and the engine version if needed). There will be no downtime if your database is already on Platform Version 4. For existing clusters on older platform versions, upgrade to Platform Version 4 through a pending maintenance action. 384 ACU support is available for Aurora PostgreSQL versions 18.4, 17.10, 16.14, 15.18, and 14.23, running on Platform Version 4.
To learn more, see Aurora serverless capacity in the Amazon Aurora User Guide. For pricing details and Region availability, visit Amazon Aurora Pricing.  To get started, create or modify an Aurora serverless database in the AWS Management Console.
Quelle: aws.amazon.com

SageMaker MLflow Apps now support MLflow 3.16

Amazon SageMaker AI MLflow Apps now support MLflow 3.16, bringing a redesigned tracing experience and faster experiment tracking to your generative AI and machine learning workflows.
MLflow 3.16 improves debugging and analysis of generative AI applications and agents. The redesigned trace explorer is now the default, with adjustable row height, reorderable columns, custom columns from any trace tag or metadata field. This release also accelerates metric charts for experiments with large metric histories.
New MLflow Apps are created on MLflow 3.16 by default. Existing MLflow Apps will be upgraded to MLflow 3.16 during an upcoming maintenance window, with no action required.
MLflow 3.16 is available in all AWS Regions where MLflow Apps are available. To learn more, visit the SageMaker AI MLflow developer guide.
Quelle: aws.amazon.com