opik
Opik is an open-source observability and evaluation platform for LLM applications, RAG systems, and agentic workflows. It provides tracing, automated evaluations, LLM-as-a-judge metrics, and production dashboards to help developers build and optimize AI applications from prototype to production.
Key facts
Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.
| Field | Value |
|---|---|
| Repository | comet-ml/opik |
| Owner | comet-ml |
| Primary language | Python |
| License | Apache-2.0 — OSI-approved |
| Stars | 20.4k |
| Forks | 1.6k |
| Open issues | 149 |
| Latest release | 2.1.19 (2026-07-07) |
| Last updated | 2026-07-08 |
| Source | https://github.com/comet-ml/opik |
What opik is
Python-based platform offering comprehensive LLM tracing with integration into popular frameworks (LangChain, LLaMA Index, Autogen, Flowise AI), dataset and experiment management for evaluation, LLM-as-a-judge metrics (hallucination detection, moderation, RAG assessment), and scalable production monitoring designed for 40M+ traces/day with online evaluation rules and PyTest CI/CD integration.
Get the opik source
Clone the repository and explore it locally.
git clone https://github.com/comet-ml/opik.gitcd opik# follow the project's README for install & configurationNeed it deployed, integrated, or customized instead? DEV.co ships production installs.
Best use cases
Implementation considerations
- Opik provides both cloud-hosted (Comet.com) and self-hosted (Docker/Kubernetes) deployment paths; choose based on operational capacity and data residency needs.
- Native integrations exist for LangChain, LLaMA Index, Autogen, Flowise AI, and Google ADK; custom integrations may require SDK instrumentation for non-standard frameworks.
- LLM-as-a-judge metrics depend on external LLM APIs (OpenAI, etc.) for evaluation; token costs and latency should be factored into evaluation workflows.
- Production monitoring at 40M+ traces/day requires proper infrastructure sizing; self-hosted deployments need database and storage capacity planning.
- Feedback annotation and experiment management integrate Python SDK, UI, and API calls; teams must align on feedback workflows and metric definitions upfront.
When to avoid it — and what to weigh
- Minimal LLM Integration Needed — If your application has minimal or no LLM components, Opik's observability and evaluation focus adds unnecessary overhead.
- Strict Data Residency or Air-Gapped Environments — While self-hosting is available, the recommended Comet Cloud option involves sending data to external servers. Self-hosted Kubernetes deployments add operational complexity.
- Budget Constraints with Enterprise Scale — Self-hosting and operating Opik at 40M+ traces/day requires infrastructure and DevOps investment. Commercial support and scaling may require Comet engagement.
- Closed-Source or Proprietary Requirements — Opik is open-source under Apache-2.0. If closed-source derivative distributions are required, review licensing implications for your use case.
License & commercial use
Licensed under Apache License 2.0 (Apache-2.0), a permissive OSI-approved open-source license allowing commercial use, modification, and distribution with minimal restrictions (attribution and license copy required).
Apache-2.0 permits commercial use without explicit restrictions. However, the platform is built and hosted by Comet; self-hosted deployments are free, but cloud-hosted (Comet.com) deployments may incur costs. Review Comet's commercial terms for hosted services separately. No restrictions on using Opik to build proprietary LLM applications.
DEV.co evaluation signals
Editorial assessment — not user reviews. Directional, with an explicit confidence level.
| Signal | Assessment |
|---|---|
| Maintenance | Active |
| Documentation | Strong |
| License clarity | Clear |
| Deployment complexity | Moderate |
| DEV.co fit | Strong |
| Assessment confidence | High |
Cloud-hosted deployments transmit trace and evaluation data to Comet servers; assess data sensitivity and compliance requirements (PII in prompts/responses, HIPAA, SOC 2, etc.). Self-hosted deployments maintain data control but require secure infrastructure setup (DB encryption, network isolation, credential management for LLM APIs). Apache-2.0 license does not provide security audit or liability guarantees; conduct security review before production use. No explicit security policy, vulnerability disclosure process, or security audit results provided in data.
Alternatives to consider
Langfuse
Open-source LLM observability and evaluation platform with similar tracing, dataset management, and LLM-as-a-judge capabilities; lighter footprint, also supports self-hosting.
LlamaIndex Observability
Native observability and evaluation built into LlamaIndex framework; tighter integration if already using LlamaIndex-based RAG, but narrower scope than standalone platform.
DataDog / New Relic (LLM Monitoring)
Enterprise APM platforms with LLM tracing and observability add-ons; better fit for existing enterprise monitoring stacks, but higher cost and less specialized for LLM evaluation workflows.
Build on opik with DEV.co software developers
Start with Comet Cloud (free signup) or deploy Opik on your infrastructure. Explore integrations, evaluate with LLM-as-a-judge, and monitor production in minutes.
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opik FAQ
Can I use Opik without Comet Cloud?
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How much does it cost to evaluate with LLM-as-a-judge metrics?
Is Opik suitable for production use?
Custom software development services
DEV.co is a software development agency delivering custom software development services to companies building on open source. Our software developers and web developers design, integrate, and ship production systems — spanning web development, APIs, AI, data, and cloud. If opik is part of your ai frameworks roadmap, our team can implement, customize, migrate, and maintain it.
Ready to Observe and Evaluate Your LLM Apps?
Start with Comet Cloud (free signup) or deploy Opik on your infrastructure. Explore integrations, evaluate with LLM-as-a-judge, and monitor production in minutes.