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OpenLLMetry Monitoring

⬢ 層級 2工具
+$15–25k
薪資影響
1 個月
學習時長
中等
難度
—
職業
一覽

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.

什麼是 OpenLLMetry Monitoring

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.

🔧 工具與生態
OpenLLMetry SDKOpenTelemetry IntegrationCost CalculationTrace ExportDashboard IntegrationSampling StrategiesCustom MetricsVendor Integration

💰 各地區薪資

地區初級中級高級
USA$80,000$135,000$185,000
UK£48,000£87,000£125,000
EU€52,000€92,000€135,000
CANADACA$75,000CA$125,000CA$170,000

❓ 常見問題

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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