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Traceloop vs OpenObserve

TraceloopOpenObserve

Bottom line: Traceloop for engineering teams operating LLM apps in production; OpenObserve for teams running agents in production.

TraceloopTraceloop

Open-source LLM observability built on OpenTelemetry

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OpenObserveOpenObserve

OpenTelemetry-native observability for LLM calls, tools, and agent handoffs

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Votes00
PricingFreemiumFreemium
CategoryLlm ObservabilityLlm Observability
Tags
llm observabilitymonitoringopentelemetrydeveloper toolsopen source
opentelemetryllm tracingagent observabilitytoken costopen source
Best for
  • Engineering teams operating LLM apps in production
  • Developers wanting vendor-neutral observability
  • Teams already using OpenTelemetry
  • Teams running agents in production
  • Platform teams already using OpenTelemetry
  • Organisations needing LLM cost attribution
Pros
  • Built on open standard OpenTelemetry, avoiding lock-in
  • Open-source OpenLLMetry library is free (Apache-2.0)
  • Generous free tier on the managed platform
  • Broad support for providers and frameworks
  • Multiple language SDKs
  • Agent traces are standard OpenTelemetry spans, not a silo
  • Per-span token cost from your own model pricing
  • Unlimited users with no per-seat charge
  • AGPL-3.0 core with a self-hosted option
  • Self-hosted enterprise free up to 50 GB per day
Cons
  • Requires engineering effort to instrument and interpret
  • Smaller, seed-stage company
  • Advanced evaluation features still maturing
  • Aimed at developers, not non-technical users
  • Enterprise support and guarantees worth verifying
  • LLM observability is labelled preview
  • Online evaluations are an enterprise feature
  • Ingestion-based pricing needs volume forecasting
  • Self-hosting carries operational overhead
  • Payload capture raises data governance questions

Comparison generated from each tool's listing. Add or remove tools above to change it.