Amazon RDS Snapshot Export to S3 now available in AWS GovCloud (US) Regions

Amazon RDS Snapshot Export to S3 is now available in AWS GovCloud (US) regions, enabling you to export snapshot data in Apache Parquet format for analytics, data retention, and machine learning use cases. Snapshot export to S3 supports all DB snapshot types (manual, automated system, and AWS Backup snapshots) and runs directly on the snapshot without impacting database performance. The exported data in Apache Parquet format can be analyzed using other AWS services such as Amazon Athena, Amazon SageMaker, or Amazon Redshift Spectrum, or with big data processing frameworks such as Apache Spark. You can create a snapshot export with just a few clicks in the Amazon RDS Management Console or by using the AWS SDK or CLI. Snapshot Export to S3 is supported for Amazon Aurora PostgreSQL – Compatible Edition and Amazon Aurora MySQL, Amazon RDS for PostgreSQL, Amazon RDS for MySQL, and Amazon RDS for MariaDB snapshots. For more information, including instructions on getting started, read Aurora documentation or Amazon RDS documentation.
Quelle: aws.amazon.com

AWS Observability now available as a Kiro power

Today, AWS announces AWS Observability as a Kiro power, enabling developers and operators to investigate infrastructure and application health issues faster with AI agent-assisted workflows in Kiro. Kiro Powers is a repository of curated and pre-packaged Model Context Protocol (MCP) servers, steering files, and hooks validated by Kiro partners to accelerate specialized software development and deployment use cases. The AWS Observability power packages four specialized MCP servers with targeted observability guidance: the CloudWatch MCP server for observability data; the Application Signals MCP server for application performance monitoring; the CloudTrail MCP server for security analysis and compliance; and the AWS Documentation MCP server for contextual reference access. This unified platform gives Kiro agents instant context for comprehensive workflows including alarm response, anomaly detection, distributed tracing, SLO compliance monitoring, and security investigation. Additionally, the power includes automated gap analysis that helps you identify and fix missing instrumentation. With the AWS Observability power, developers can now accelerate troubleshooting their distributed applications and infrastructure in minutes, directly in their IDE. The power addresses two critical needs: reducing mean time to resolution (MTTR) for active incidents and proactively improving your observability stack. For faster incident response, when investigating an active alarm, the power dynamically loads relevant guidance and operational signals so AI agents receive only the context needed for the specific troubleshooting task at hand. For stack improvement, the automated gap analysis examines your code to identify missing instrumentation patterns—such as unlogged errors, missing correlation IDs, or absent distributed tracing—and provides actionable recommendations. The power includes eight comprehensive steering guides covering incident response, alerting, performance monitoring, security auditing, and gap analysis. The AWS Observability power is available for one-click installation within Kiro IDE and Kiro powers webpage in all AWS Regions, with each underlying MCP server functional based on regional support of the corresponding AWS service. To learn more about AWS observability MCP servers, visit our documentation. 
Quelle: aws.amazon.com

AWS Compute Optimizer now applies AWS-generated tags to EBS snapshots created during automation

AWS Compute Optimizer makes it easier to identify snapshots that are created when snapshotting and deleting unattached Amazon Elastic Block Store (EBS) volumes by automatically applying an AWS-generated tag during creation. This enhancement improves visibility and tracking of EBS snapshots created through Compute Optimizer Automation.
When Compute Optimizer creates a snapshot before deleting an unattached EBS volume—whether initiated through manual actions or automation rules—the snapshot now receives the tag aws:compute-optimizer:automation-event-id with a tag value that links the snapshot to the unique identifier of the automation event that created it. This allows you to easily identify, track, and manage snapshots created through the automated optimization process, helping you maintain better governance over your backup resources and understand the source of snapshots in your environment.
This is available in all AWS Regions where AWS Compute Optimizer Automation is available. To get started with automated optimization, go to the AWS Compute Optimizer console or visit the user guide documentation.
Quelle: aws.amazon.com

Amazon Bedrock now supports server-side tool execution with AgentCore Gateway

Amazon Bedrock now enables server-side tool execution through Amazon Bedrock AgentCore Gateway integration with the Responses API. Customers can connect their AgentCore Gateway tools to Amazon Bedrock models, enabling server-side tool execution without client-side orchestration.
With this launch, customers can specify an AgentCore Gateway ARN as a tool connector in Responses API requests. Amazon Bedrock automatically discovers available tools from the gateway, presents them to the model during inference, and executes tool calls server-side when the model selects them, all within a single API call. This eliminates the need for customers to build and maintain client-side tool orchestration loops, reducing application complexity and latency for agentic workflows. Customers retain full control over tool access through their existing AgentCore Gateway configurations and AWS IAM permissions.
Server-side tool execution with AgentCore Gateway supports all models available through the Amazon Bedrock Responses API. Customers define tools using the MCP server connector type with their gateway ARN, and Amazon Bedrock handles tool discovery, model-driven tool selection, execution, and result injection automatically. Multiple tool calls within a single conversation turn are supported, and tool results are streamed back to the client in real time.
This capability is generally available in all AWS Regions where both Amazon Bedrock’s Responses API and Amazon Bedrock AgentCore Gateway are available. To get started, visit the Amazon Bedrock documentation or the Amazon Bedrock console. For more information about Amazon Bedrock AgentCore Gateway, see the AgentCore documentation.
Quelle: aws.amazon.com