Monat: Mai 2026

AWS IoT Core for Device Location adds Confidence Level Configuration and Measurement Type support

AWS IoT Core for Device Location now supports two enhancements that give developers greater control over location resolution and richer metadata for resolved device locations. Customers using the Cell ID, Wi-Fi, or Cell+Wi-Fi solvers can now specify a desired confidence level between 50% and 99% when resolving device locations. The confidence level represents the statistical probability that the actual device location falls within the reported accuracy radius. A higher confidence level (for example, 95%) increases certainty that the device falls within the reported radius but produces a larger accuracy radius. A lower confidence level (for example, 50%) yields a smaller radius with less certainty. Customers can now configure this value to balance accuracy and confidence based on their specific requirements. This feature is currently supported for HTTP-based location resolution. This update also introduces a measurement type field in resolved location metadata, giving developers greater visibility into how each device location was determined — whether through GNSS, Wi-Fi or BLE location resolvers. This make it easier to assess location data quality, debug positioning issues, and make more informed decisions based on how each location was determined. These updates are available in all AWS IoT Core for Device Location supported regions. For detailed guidance and implementation instructions, visit the AWS IoT Core Device Location and IoT Wireless Developer Guide .
Quelle: aws.amazon.com

Amazon WorkSpaces now lets AI agents operate desktop applications (Preview)

Amazon WorkSpaces, AWS’s fully managed cloud desktop service, now enables AI agents to securely access and operate desktop applications through managed WorkSpaces environments. Many enterprises run critical business processes on desktop applications—mainframes, ERP systems, and proprietary tools—that lack modern APIs, creating a “last-mile challenge” for AI agents. WorkSpaces now allows organizations to automate everyday workflows at scale while maintaining full enterprise-grade governance and compliance.
AI agents built on any framework and running anywhere—cloud-hosted, on-premises, or hybrid—can now connect to business applications with minimal code using industry-standard Model Context Protocol (MCP) integration. Builders gain fast time-to-value without standing up new infrastructure, while IT administrators maintain centralized permissions, logging, and auditing controls identical to human WorkSpaces environments. Enterprise observability features including screenshots and metrics provide full visibility into agent activities. Organizations can automate workflows spanning claims processing, trade settlement, candidate screening, and back-office operations across financial services, healthcare, and other regulated industries—all without requiring application modernization.
WorkSpaces delivers secure environments where agents can point, click, and navigate on desktop applications just like humans. With pay-as-you-go pricing and elastic scale built on AWS’s global infrastructure, enterprises reduce IT overhead while expanding what’s possible when people and AI work together. To learn more, visit the WorkSpaces documentation.  
Quelle: aws.amazon.com

Amazon ElastiCache adds thirteen new Amazon CloudWatch metrics for network capacity planning and engine diagnostics

Amazon ElastiCache customers can now detect network throttling, memory fragmentation, and connection exhaustion, using thirteen new Amazon CloudWatch metrics for node-based clusters. You can monitor these host-level and engine-level diagnostics directly from CloudWatch without running INFO commands on individual nodes or calculating baselines from raw byte counters.

Network capacity: NetworkBaselineUsageInPercentage, NetworkBaselineUsageOutPercentage, NetworkBaselineMaxUsageInPercentage, and NetworkBaselineMaxUsageOutPercentage report network utilization relative to instance baseline, enabling portable alarms that remain valid across instance type changes. Values above 100 percent signal that a host is consuming burst credits, a leading indicator that a sustained workload will eventually lead to credit exhaustion and throttling. The variants capturing max report per-second bursts that averaged metrics can hide.
Memory health: UsedMemoryDataset shows memory consumed by actual stored data excluding engine overhead. AllocatorFragmentationBytes and AllocatorFragmentationRatio isolate fragmentation that the activedefrag parameter can address. MajorPageFaults captures OS-level page faults that indicate memory pressure beyond what the engine can surface.
Connectivity health: BlockedConnections and RejectedConnections surface connections waiting on blocking commands and connections turned away when the maxclients limit is reached. When RejectedConnections is non-zero, raise maxclients or diagnose client-side connection pool leaks.
Pub/sub workloads: PubSubChannels and PubSubShardChannels expose active classic and sharded channels on each node. When classic channel counts are growing with utilization, consider switching to sharded pub/sub to scale horizontally.
Command throughput: ProcessedCommands provides total command throughput across all command types.

These metrics are available for node-based clusters in all commercial AWS Regions and the AWS China and AWS GovCloud (US) Regions where ElastiCache is supported, at no additional cost. To get started, view the new metrics in the ElastiCache console monitoring tab or in the AWS/ElastiCache namespace in the CloudWatch console. To learn more, see Host-Level Metrics and Metrics for Valkey and Redis OSS.
Quelle: aws.amazon.com

AWS SAM now supports WebSocket APIs for Amazon API Gateway

AWS Serverless Application Model (AWS SAM) now supports WebSocket APIs for Amazon API Gateway, enabling you to define complete WebSocket APIs with minimal configuration in your SAM template.
AWS SAM is a collection of open-source tools that make it easy for you to build and manage serverless applications. WebSocket APIs are critical for real-time applications such as chat, live dashboards, AI/LLM streaming, and IoT. However, SAM previously did not support WebSocket APIs, requiring you to manually configure all of the underlying resources in AWS CloudFormation. This made it difficult to debug common issues such as missing IAM permissions for Lambda functions. Now, SAM handles all of this automatically, generating the required resources and permissions from your template. The new resource provides feature parity with API Gateway WebSocket APIs, including IAM and Lambda authorization, custom domains, RouteSettings, Models, and StageVariables. Globals support lets you share common configuration across multiple WebSocket APIs.
To get started, add the AWS::Serverless::WebSocketApi resource type to your SAM template. Define your routes by specifying Lambda function handlers for $connect, $disconnect, and $default routes, along with any custom routes your application requires. SAM automatically wires up the integrations and permissions for each route. You can also configure authorization, stage settings, and custom domains directly within the resource definition.
To learn more, visit the SAM developer guide.
Quelle: aws.amazon.com

AWS SAM CLI adds BuildKit support for AWS Lambda functions packaged as container images

AWS Serverless Application Model Command Line Interface (SAM CLI) now supports BuildKit for building container images from Dockerfiles, enabling faster, more efficient container image builds for Lambda functions packaged as container images.
SAM CLI is a command-line tool for building, testing, debugging, and packaging serverless applications locally before deploying to AWS Cloud. Developers packaging Lambda functions as container images often need advanced build features provided by BuildKit to optimize their images for production. However, SAM CLI previously did not support BuildKit features. Now, with BuildKit support in SAM CLI, you can utilize multi-stage builds to create smaller final images without development dependencies, improved caching to reduce rebuild times, and better parallelization of build steps. BuildKit also enables cross-architecture builds, allowing you to build container images targeting both x86_64 and arm64 (AWS Graviton2) instruction set architectures from the same development machine. You can also use Docker secrets during builds, keeping sensitive data such as credentials and API keys out of your final image layers.
To get started, download or update SAM CLI to version 1.159.0 or later and use the –use-buildkit flag with sam build. This feature works regardless of whether you are using Docker or Finch with SAM CLI, unlocking the full set of BuildKit capabilities.
To learn more, visit the SAM CLI developer guide.
Quelle: aws.amazon.com