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Portkey vs OpenObserve

PortkeyOpenObserve

Bottom line: Portkey for teams routing production traffic across many LLMs; OpenObserve for teams running agents in production.

PortkeyPortkey

Open-source AI gateway and control plane for production Gen AI.

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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
ai-gatewayllmopsopen-sourceobservabilitygovernance
opentelemetryllm tracingagent observabilitytoken costopen source
Best for
  • Teams routing production traffic across many LLMs
  • Organizations needing governance and reliability tooling
  • Developers wanting an open-source, self-hostable gateway
  • Teams running agents in production
  • Platform teams already using OpenTelemetry
  • Organisations needing LLM cost attribution
Pros
  • Fully open-source, self-hostable gateway for data control and no lock-in
  • Access to more than 1,600 models through one API
  • Broad feature set spanning observability, guardrails, routing, prompts, and cost control
  • Transparent, relatively cheap entry with free and ~$49 tiers
  • Battle-tested at very large scale
  • 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
  • Adds a network hop and dependency in the critical request path
  • Log-volume-based pricing can get complex or expensive at scale
  • Free-tier logging caps and short retention are tight for real debugging
  • Self-hosting the open-source gateway shifts ops burden to you
  • It is a gateway and ops layer, not a full build-and-eval IDE
  • 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

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