What problem does it solve? Setting up and troubleshooting AWS observability requires deep knowledge of CloudWatch alarms, Log Insights queries, X-Ray tracing, ADOT collectors, and Application Signals onboarding, with many subtle defaults and constraints that cause misconfigurations. ## Core Features & Use Cases - Application Signals Onboarding: Enable auto-instrumentation for services on EC2, ECS, EKS, and Lambda in Python, Node.js, Java, and .NET using ADOT SDKs, including ServiceEvents metadata propagation through CI/CD pipelines. - CloudWatch Configuration: Build metric, composite, and anomaly detection alarms with recommended defaults, write Log Insights queries, publish custom metrics via EMF, and design dashboards with cross-account support. - Dynamic Instrumentation: Debug live running services with breakpoints and snapshot capture without redeploying code, using dedicated Python scripts for instrumentation CRUD operations. - Use Case: A team needs to onboard a Python service on EKS to Application Signals, add deployment metadata env vars to their GitHub Actions workflow, and create p99 latency alarms with a CDK dashboard template. ## Quick Start Ask the assistant to enable Application Signals auto-instrumentation for your service, or to write a CloudWatch alarm or Log Insights query for your workload.