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Expedia's STAR platform demonstrates a pragmatic approach to AI observability by leveraging deterministic workflows rather than autonomous agents. This strategy prioritizes consistency and human-in-the-loop validation when analyzing infrastructure telemetry for root cause analysis. The implementation highlights how structured prompt chaining can effectively accelerate incident response times in complex distributed systems without relying on experimental capabilities like RAG or function calling.
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Expedia Uses AI-Driven Service Telemetry Analyzer to Accelerate Incident Investigation

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Expedia Group has introduced STAR, an internal AI-assisted observability platform that helps engineers investigate production incidents using service telemetry and LLMs. Built with FastAPI, Datadog, Celery, Redis, and Langfuse, STAR follows structured workflows to analyze telemetry, generate root cause assessments, and support incident response while keeping engineers in the loop. By Leela Kumili

Expedia Group has introduced Service Telemetry Analyzer (STAR), an internal AI-assisted observability platform that helps engineers investigate production incidents by analyzing service telemetry and generating structured root cause assessments. The system combines operational metrics with large language models (LLMs) through predefined diagnostic workflows, aiming to reduce…

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