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This post explains how to set up zero-code observability for LLM and agent workloads on Kubernetes using the OpenLIT Operator and Grafana Cloud.
•OpenLIT Operator automatically injects OpenTelemetry instrumentation into Kubernetes pods without any code changes or image rebuilds
•It supports major LLM providers (OpenAI, Anthropic, Google, AWS Bedrock, Mistral) and frameworks (LangChain, LlamaIndex, CrewAI, Haystack, DSPy)
•Telemetry is forwarded via OTLP to Grafana Cloud, where pre-built dashboards visualize token usage, latency, cost, and agent step sequences
•Setup requires deploying the operator via Helm, creating an AutoInstrumentation CRD with label selectors, and enabling the AI Observability integration in Grafana Cloud
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The approach is vendor-neutral and OpenTelemetry-native, allowing telemetry routing to any OTLP-compatible backend without redeploying applications
This summary was automatically generated by AI based on the original article and may not be fully accurate.
Grafana
Google Cloud
AWS