OpenLLMetry Monitoring

⬢ درجه 2وسایل

+$15–25k

د معاش اغېز

1 میاشتې

د زده کړې وخت

منځنی

سختوالی

—

مسلکونه

په یوه نظر

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 څه شی دی

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.

🔧 وسیلې او ایکوسیستم

OpenLLMetry SDKOpenTelemetry IntegrationCost CalculationTrace ExportDashboard IntegrationSampling StrategiesCustom MetricsVendor Integration

📋 مخکې له دې چې تاسو پیل کړئ

Monitoring Observability Python

💰 د سیمې له مخې معاش

سیمه	جونیر	منځنی	سېنیر
USA	$80k	$135k	$185k
UK	£48k	£87k	£125k
EU	€52k	€92k	€135k
CANADA	C$75k	C$125k	C$170k

🎓 تصدیقونه

OpenLLMetry Documentation OpenLLMetry GitHub

⚖ سره پرتله کړئ

Langsmith Observability Helicone Llm Proxy Langfuse Observability

❓ ډېرې پوښتل شوې پوښتنې

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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