Amazon CloudWatch Application Signals adds GitHub Action and MCP server improvements
AWS announces the general availability of a new GitHub Action and improvements to CloudWatch Application Signals MCP server that bring application observability into developer tools, making troubleshooting issues faster and more convenient. Previously, developers had to leave GitHub to triage production issues, look up trace data, and ensure observability coverage, often switching between consoles, dashboards, and source code. Starting today, Application observability for AWS GitHub Action helps you catch breaching SLOs or critical service errors, in GitHub workflows. In addition, now you can use the CloudWatch Application Signals MCP server in AI coding agents such as Kiro to identify the exact file, function, and line of code responsible for latency, errors, or SLO violations. Furthermore, you can get instrumentation guidance that ensures comprehensive observability coverage.
With this new GitHub Action, developers can mention @awsapm in GitHub Issues with prompts like "Why is my checkout service experiencing high latency?" and receive intelligent, observability-based responses without switching between consoles, saving time and effort. In addition, with improvements in CloudWatch Application Signals MCP server, developers can now ask questions like "Which line of code caused the latency spike in my service?". Furthermore, when instrumentation is missing, the MCP server can modify infrastructure-as-code (e.g., CDK, Terraform) to help teams set up OTel-based application performance monitoring for ECS, EKS, Lambda, and EC2 without requiring coding effort.
Together, these features bring observability into development workflows, reduce context switching, and power intelligent, agent-assisted debugging from code to production. To get started, visit Application Observability for AWS GitHub Action documentation and the CloudWatch Application Signals MCP server documentation.