Cloud Computing Köln

Amazon RDS Enhances IAM Database Authentication with Connection Rate Scaling

Amazon Relational Database Service (Amazon RDS) now offers dynamic connection scaling for IAM database authentication, allowing connection rates to scale with instance resources. IAM database authentication performance now scales with available instance resources, enabling enterprise workloads to leverage IAM authentication for high-volume connection patterns. The number of new IAM authentication requests your instance can handle depends on available resources and workload characteristics. For optimal performance, we recommend reusing IAM user or IAM assumed role principals to generate authentication tokens, or reusing the authentication tokens themselves, when possible. This update is available in all AWS Regions, including the AWS GovCloud (US) Regions, where IAM database authentication is supported for Amazon Aurora and Amazon RDS database engines including PostgreSQL, MySQL, and MariaDB. To learn more, visit the IAM database authentication documentation.
Quelle: aws.amazon.com

AWS CloudFormation and CDK accelerate development feedback loops with pre-deployment validation on all stack operations

AWS CloudFormation customers can now get immediate feedback on deployment errors in seconds, eliminating the need to wait through a full provision-and-rollback cycle to discover preventable failures. CloudFormation now runs pre-deployment validation on Create Stack and Update Stack operations, catching common deployment errors before resource provisioning begins. This accelerates development velocity across all deployment workflows, from manual iteration to CI/CD pipelines to AI agents provisioning infrastructure. Previously, pre-deployment validation was available during change set creation, covering property syntax errors, resource name conflicts, and S3 bucket emptiness constraints. With this release, the same validations now run automatically on Create Stack and Update Stack operations. Additionally, three new validation checks are now available as warnings during change set creation. Service quota limits validation warns when creating resources would exceed your account’s service quotas. AWS Config Recorder conflict detection warns when your template adds Config rules to an account that does not have Config recording enabled, or defines a Config Recorder in an account where one is already active. ECR repository delete readiness validation warns when an ECR repository targeted for deletion still contains images. When validation detects an issue, you can view errors using the DescribeEvents API with the operation ID, or in the CloudFormation console by navigating to your stack’s Events tab and clicking the operation ID (or the link in the banner or status reason column) to open the Operation view page, which opens directly on the Deployment validations tab. Each error includes the logical resource ID and property path, so you can pinpoint and fix the problem before any resources are provisioned. In CDK, both cdk deploy and cdk validate surface validation results with construct-level tracing in a unified report, so AI agents and automation tools can parse structured responses and self-correct immediately. Pre-deployment validation is enabled by default on all stack operations with no configuration required. If you need to skip validation for a specific operation, use the new DisableValidation parameter on CreateStack, UpdateStack and CreateChangeSet API calls, or the –disable-validation flag in the CLI. Visit the Validate stack deployments User Guide to learn more. This feature is available in all AWS Regions where CloudFormation is supported, excluding China. Refer to the AWS Region table for service availability details.
Quelle: aws.amazon.com

AWS CloudFormation and CDK express mode speeds up infrastructure deployments by up to 4x

AWS CloudFormation and CDK express mode reduces deployment time by up to 4x for developers and AI agents building infrastructure, based on internal benchmarks. Express mode completes stack operations when CloudFormation confirms resource configuration is applied, rather than waiting for extended stabilization checks such as traffic readiness, region propagation, and resource cleanup. This enables faster iteration cycles for developers and AI agents building infrastructure. When iterating on infrastructure in development environments, developers and AI agents need faster iteration cycles to build infrastructure incrementally. Previously, every deployment waited for full resource stabilization regardless of whether the workflow required it. For example, creating a CloudFront distribution required waiting 5-10 minutes for propagation to all edge locations before the deployment completed, even when the developer only needed the distribution domain name to continue. With express mode, deployments complete in seconds once configuration is applied, and propagation continues in the background. CloudFormation still processes resources in dependency order and handles dependent resource failures within the same stack. Express mode disables rollback by default, enabling immediate fix-and-retry without waiting for rollback operations. To get started, set –deployment-config ‘{“mode”: “EXPRESS”}’ when creating, updating, and deleting stacks or creating a change set through the AWS CLI, AWS SDKs, or the AWS Management Console. For AWS CDK users, activate express mode with cdk deploy –express. No template changes are required. Express mode works with all existing CloudFormation templates, and nested stacks. Visit the CloudFormation Express mode documentation to learn more. This feature is available in all AWS Regions where CloudFormation is supported. Refer to the AWS Region table for service availability details.
Quelle: aws.amazon.com

Amazon CloudWatch Logs enriches log events with AWS resource tags

Amazon CloudWatch Logs now enriches log events with resource tags, making it easier to filter, search, and analyze logs by the metadata that matters most to your organization, such as  team ownership, environment, cost center, or application name, without requiring changes to your logging instrumentation.
With tag enrichment, Amazon CloudWatch Logs adds resource tags directly to your log events at ingestion time. You can immediately use tags in log queries, to scope your analysis without building custom pipelines or manually adding context to your application logs. For example, you can quickly filter all logs from production resources owned by a specific team, or filter by cost center during an incident investigation.
Tag enrichment for logs is available in all commercial AWS Regions except Middle East (UAE), Middle East (Bahrain), and Israel (Tel Aviv). To get started, enable resource tags on telemetry in the Amazon CloudWatch Settings, or through the AWS Command Line Interface (AWS CLI), and AWS SDKs to use your existing AWS resource tags to enrich your log events. Tag enrichment is available for no additional cost. Learn more on the Amazon CloudWatch documentation page.
Quelle: aws.amazon.com

Announcing general availability of Amazon WorkSpaces for AI agents

Amazon WorkSpaces for agents is now generally available, enabling AI agents to securely access and operate desktop applications through managed WorkSpaces environments. Enterprises run critical business processes on desktop applications (ERP systems, CRMs, mainframes, and proprietary tools) where years of customization, undocumented logic, and strict compliance requirements make them too critical to abandon and costly to modernize. WorkSpaces for agentsnow gives AI agents a managed cloud workspace where they can see the screen and operate these applications the way humans do, without requiring application modernization or custom integrations.
WorkSpaces uses the same infrastructure for agents as organizations have trusted for over a decade to deliver secure, managed desktops at scale. Agents inherit the same identity controls, network isolation, and compliance boundaries as human users, so organizations gain automation without giving up governance. Organizations can automate workflows such as claims processing, patient record updates, trade settlement, and back-office operations. The service works with any agent framework using Model Context Protocol (MCP), and pricing scales based on active session time.
Since launching in Preview, customer and partner feedback has shaped new capabilities. MCP tool forwarding allows agents to interact with applications and the desktop operating system through direct MCP calls rather than using computer use tools, improving accuracy, reducing latency, and lowering cost. Real-time session control gives operators live visibility into agent activity with the ability to revoke access mid-session. Domain-joined fleet support lets agents operate under existing Active Directory identities, extending the same access policies and audit attribution that apply to employees.
To learn more, visit Amazon WorkSpaces for AI agents. To get started building, see the documentation and sample code on GitHub.  
Quelle: aws.amazon.com