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OpenLLMetry Monitoring

⬢ SADARKAA 2Meeshaalee
+$15–25k
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OpenLLMetry is an observability framework for LLM applications using OpenTelemetry standards. Track costs, latency, errors, and quality metrics across LLM calls. Works with OpenAI, Anthropic, Cohere, and others. Used by AI product teams for production observability. Salary: mid 135-155k. Learn in 3-4 weeks. Complements LLM Fundamentals and AI Observability.

OpenLLMetry Monitoring maali?

OpenLLMetry is an open-source observability framework for LLM applications based on OpenTelemetry standards. It instruments LLM API calls (OpenAI, Anthropic, Cohere, etc.) and exports traces to any OpenTelemetry backend (DataDog, New Relic, Jaeger). Key features: cost tracking, latency measurement, error detection, and quality metrics for LLM-powered applications.

🔧 MEESHAALEE & SIRNA NAANNOO
OpenLLMetry SDKOpenTelemetry IntegrationCost CalculationTrace ExportDashboard IntegrationSampling StrategiesCustom MetricsVendor Integration

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💰 Miindaa naannoodhaan

NaannooJalqabaaGiddu-galeessaAngafa
USA$80k$135k$185k
UK£48k£87k£125k
EU€52k€92k€135k
CANADAC$75kC$125kC$170k

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Is OpenLLMetry free?
Yes, open-source and free. You pay for backend services (DataDog, New Relic, etc.) if used.
Does OpenLLMetry track costs?
Yes, it calculates costs based on token counts and model pricing. Supports most LLM providers.
Can I use OpenLLMetry without changing code?
Mostly; OpenLLMetry uses Python instrumentation. Some code changes required but minimal.
What backends does OpenLLMetry export to?
Any OpenTelemetry backend: DataDog, New Relic, Jaeger, Google Cloud Trace, etc.
How does OpenLLMetry compare to LangSmith?
OpenLLMetry is framework-agnostic and uses open standards; LangSmith is LangChain-native. Choose OpenLLMetry for flexibility.

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