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OpenObserve vs Cortex

OpenObserveCortex

Bottom line: OpenObserve for teams running agents in production; Cortex for aPI teams with maintained specifications.

OpenObserveOpenObserve

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

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CortexCortex

Turn API specifications into docs, typed SDKs, and an MCP server

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Votes00
PricingFreemiumFree
CategoryLlm ObservabilityMcp
Tags
opentelemetryllm tracingagent observabilitytoken costopen source
mcp serverapi documentationsdk generationopenapiopen source
Best for
  • Teams running agents in production
  • Platform teams already using OpenTelemetry
  • Organisations needing LLM cost attribution
  • API teams with maintained specifications
  • Teams exposing APIs to agents via MCP
  • Open-source projects needing docs and SDKs
Pros
  • 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
  • MIT licensed with a public repository
  • Generates docs, SDKs, and an MCP server from one spec
  • Supports OpenAPI, AsyncAPI, GraphQL, gRPC, and OpenRPC
  • Eleven SDK output languages
  • Fully self-hostable, deployable anywhere Node runs
Cons
  • 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
  • Output quality depends entirely on spec quality
  • No hosted service or commercial support
  • Requires a build step in your pipeline
  • No team collaboration features
  • Young project with a small ecosystem

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