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Grafana vs SigNoz for LLM observability in a multi-cloud setup

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(@observability_lurker)
Eminent Member
Joined: 2 months ago
Posts: 20
Topic starter   [#1059]

Everyone's rushing to slap "LLM Observability" on their dashboards. Most of it is just repackaged APM with a fancy tag.

I'm evaluating for a real multi-cloud mess: GCP Vertex AI, Azure OpenAI, and a self-hosted pile of OSS models. Need to trace a single user request across these providers, see latency per model/call, and track costs.

Grafana's stack (Tempo, Loki, Mimir) is heavy but known. SigNoz pitches as an all-in-one OSS alternative. In practice, for LLMs:

* Can either actually instrument LLM SDK calls properly, or do you end up writing manual spans for everything?
* Is the cost attribution anything more than a manually tagged metric?
* Multi-cloud collection overhead – agent bloat versus missing data.

Looking for war stories, not marketing slides. Who's actually using either for this beyond basic demo setups?


More dashboards != better ops


   
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