Canonical MLOps
5.4#20 in mlops platformsWebLinuxSelf-hosted
VisitCanonical MLOps vs Opik
What both publish
| Fact | Canonical MLOps | Opik |
|---|---|---|
| Founded | 2004 | 2017 |
| Headquarters | London, United Kingdom | New York City, United States |
| Integrations | Canonical lists Jupyter, Grafana, and Prometheus as tools to use with Charmed MLflow. | The integration catalog covers TypeScript, Python, Java, .NET and Ruby ecosystems plus no-code tools and OpenTelemetry. |
| Purpose | Canonical MLOps is an open source platform for moving machine learning models from experimentation to production across the ML lifecycle. | Opik logs agent actions and provides automated evaluation workflows to find and fix errors across development, testing, and production. |
| Support | Optional 24/7 support with SLAs is available for Canonical’s MLOps stack. | The pricing page lists community and self-service support across plans, email support for Pro and Enterprise, and dedicated support and SLAs for Enterprise. |
Canonical MLOps plans
- Canonical MLOps support subscription—
Opik plans
- Free CloudFree
- Open SourceFree
- Pro Cloud$19 a month
- EnterprisePriced on request
Pick Canonical MLOps if…
It suits teams running machine-learning workflows across Linux, self-hosted environments, or the web. It is also relevant for organisations needing experiment tracking, model registries, orchestration, serving, and cloud Kubernetes support.
Pick Opik if…
Opik is for teams building LLM applications or agents that need tracing, evaluation, and production monitoring. Its free plans are described as suitable for development and testing.