Cloud Computing Köln

AWS AppConfig adds enhanced targeting during feature flag rollout

AWS AppConfig enhances its deployment capabilities with new controls that allow customers to target feature flag and configuration data values to specific segments or individual users during the lifecycle of a gradual roll-out. One of AWS AppConfig’s key safety guardrails is the ability for customers to roll out feature flag or configuration data changes slowly, over the course of minutes or hours. This progressive delivery allows customers to move safer, and limit the impact of unexpected changes. AWS AppConfig uses customer-provided entity identifiers to make specific feature flag or dynamic configuration data “sticky” to individual target segments during the lifecycle of these gradual roll-outs. This targeting capability, using AppConfig Agent, ensures fine-grained control, including using an individual user ID or IDs, while updates are being deployed.
Quelle: aws.amazon.com

Aurora DSQL launches connector that simplifies building Ruby applications

Today we are announcing the release of the Aurora DSQL Connector for Ruby (pg gem) that makes it easy to build Ruby applications on Aurora DSQL. The Ruby Connector streamlines authentication and eliminates security risks associated with traditional user-generated passwords by automatically generating tokens for each connection, ensuring valid tokens are always used while maintaining full compatibility with existing pg gem features. The connector handles IAM token generation, SSL configuration, and connection pooling, enabling customers to scale from simple scripts to production workloads without changing their authentication approach. It also provides opt-in optimistic concurrency control (OCC) retry with exponential backoff, custom IAM credential providers, and AWS profile support, giving customers flexibility in how they manage their AWS credentials and handle transient failures. To get started, visit the Connectors for Aurora DSQL documentation page. For code examples, visit our Github page for the Ruby connector. Get started with Aurora DSQL for free with the AWS Free Tier. To learn more about Aurora DSQL, visit the webpage.
Quelle: aws.amazon.com

Amazon Bedrock AgentCore adds support for Chrome policies and custom root CA

Amazon Bedrock AgentCore now enables customers to configure Chrome Enterprise policies for AgentCore Browser and specify custom root Certificate Authority (CA) certificates for both AgentCore Browser and Code Interpreter. These enhancements help ensure enterprise requirements are met when allowing AI agents to operate within organizations that have strict security policies and internal infrastructure using custom certificates. With Chrome policies, you can leverage over 100+ configurable policies for managing browser behavior across security, URL filtering, content settings, and more to enforce organizational compliance requirements. For example, restrict agents to specific URLs for kiosk-mode operations, disable password managers and downloads for data-entry tasks, or implement URL blocklists for regulatory compliance. Custom root CA support enables agents to seamlessly connect to internal services like Artifactory, Jira, and finance portals that use SSL certificates signed by your organization’s internal Certificate Authority, and work with corporate proxies performing TLS interception. These features are available in all 14 AWS Regions where Amazon Bedrock AgentCore Browser and Code Interpreter are available: US East (N. Virginia), US East (Ohio), US West (Oregon), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Paris), Europe (Stockholm), Asia Pacific (Mumbai), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Asia Pacific (Seoul), and Canada (Central). To learn more, visit the AgentCore Browser documentation. 
Quelle: aws.amazon.com

Amazon SageMaker Unified Studio launches support for remote connection from Cursor IDE

Today, AWS announces remote connection from Cursor IDE to Amazon SageMaker Unified Studio via the AWS Toolkit extension. This new capability allows data scientists, ML engineers, and developers to leverage their Cursor setup – including its AI-powered code completion, natural language editing, and multi-file editing capabilities – while accessing the scalable compute resources of Amazon SageMaker. By connecting Cursor to SageMaker Unified Studio using the AWS Toolkit extension, you can eliminate context switching between your local IDE and cloud infrastructure, maintaining your existing AI-assisted development workflows within a single environment for all your AWS analytics and AI/ML services.
SageMaker Unified Studio, part of the next generation of Amazon SageMaker, offers a broad set of fully managed cloud interactive development environments (IDE), including JupyterLab and Code Editor based on Code-OSS (Open-Source Software). Starting today, you can also use your customized local Cursor setup – complete with custom rules, extensions, and AI model preferences – while accessing your compute resources and data on Amazon SageMaker. Since Cursor is built on Code-OSS, authentication is secure via IAM through the AWS Toolkit extension, giving you access to all your SageMaker Unified Studio domains and projects. This integration provides a convenient path from your local AI-powered development environment to scalable infrastructure for running workloads across data processing, SQL analytics services like Amazon EMR, AWS Glue, and Amazon Athena, and ML workflows – all with enterprise-grade security including customer-managed encryption keys and AWS IAM integration.
This feature is available in all AWS Regions where Amazon SageMaker Unified Studio is available. To learn more, visit the local IDE support documentation..
Quelle: aws.amazon.com

AWS Batch now provides AMI status and supports AWS Health Planned Lifecycle Events

AWS Batch now provides enhanced visibility into your compute environments with two new capabilities that help you maintain operational best practices. When you describe a compute environment, you can now see the status of your Batch-provided default Amazon Machine Images (AMIs), indicating when updates are available. Additionally, AWS Batch now publishes AWS Health Planned Lifecycle Events to help you prepare for and track changes affecting your batch computing resources. The AMI status indicator shows whether you’re using the latest AMI (LATEST) or if an update is available (UPDATE_AVAILABLE), helping you identify compute environments that may be running outdated AMIs. AWS Health Planned Lifecycle Events provide advance notification of upcoming changes, such as AMI deprecations, help you monitor migration status of your affected compute environments, and automate responses using Amazon EventBridge. AMI status indicator and AWS Health Planned Lifecycle Events are available today in all AWS Regions where AWS Batch is available. For more information, see Managing AMI versions and AWS Health Planned Lifecycle Events pages in the AWS Batch User Guide.
Quelle: aws.amazon.com