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AI Student Builds Observable LLM Assistant Using SigNoz and OpenTelemetry From Scratch

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A second-year AI and Data Science student built an observable AI assistant using SigNoz, OpenTelemetry, and Docker as part of the Agents of SigNoz hackathon, starting with no prior experience in any of these tools. The project involved instrumenting a Groq API-based assistant with distributed tracing, allowing each API call to be broken down into detailed spans capturing duration, token count, and model name. The student also implemented real-time cost tracking by calculating per-request expenses using Groq's token pricing and attaching the result as a custom span attribute. When a silent 401 authentication error occurred with no terminal output, the SigNoz Traces Explorer immediately surfaced the failing API call, pinpointing the issue within milliseconds. The experience highlighted how observability tools can expose hidden failures and costs in LLM applications that would otherwise go unnoticed.

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AI Student Builds Observable LLM Assistant Using SigNoz and OpenTelemetry From Scratch · ShortSingh