Otel

소개

When AI agents write, modify, or debug code, validating their changes requires structured observability data, not just unstructured logs. Otel offers an MCP-native observability surface that empowers AI agents to query their own execution history through distributed traces. It also assists humans in querying and analyzing these traces for efficient debugging and performance optimization, making complex observability data more accessible and actionable for both AI and human developers. The tool integrates with Jaeger to provide service discovery, trace inspection, and performance analysis via a REST API.

주요 기능

• Performance Analysis to identify slow traces, latency percentiles, and error rates
• Trace Inspection to search, filter, and inspect traces with full span details
• REST API with FastAPI endpoints and OpenAPI documentation
• Service Discovery for Jaeger services and operations
• 1 GitHub stars
• Self-Telemetry with internal tracing to Jaeger for debugging

사용 사례

• Debugging distributed systems by inspecting traces, finding errors, and analyzing span details.
• Validating AI agent code changes by querying their execution history and structured observability data.
• Optimizing application performance by identifying slow traces and understanding latency characteristics.