Canonical MLOps
What Canonical MLOps is
Canonical MLOps is an open source platform for moving machine learning models from experimentation into production across the ML lifecycle. Its stack includes Charmed Kubeflow, Charmed MLflow, and Charmed Feast, with capabilities for experiment tracking, model registries, pipeline orchestration, and model serving. Kubeflow deploys, scales, and manages AI workflows across clouds, virtual machines, or bare metal. MLflow supports reproducible projects and model deployment, while Feast provides a feature registry, offline and online stores, real-time and batch ingestion, and pipeline versioning. The platform also provides automated workflows, security patching, and tooling integrations. Canonical lists Jupyter, Grafana, and Prometheus for use with Charmed MLflow. MLflow can run on a workstation, CNCF-conformant Kubernetes, or a public cloud; Kubeflow supports AWS, Azure, and GCP Kubernetes services. Canonical says components receive up to 15 years of security maintenance, regular updates, and CVE fixes.
Who it suits
Canonical MLOps suits teams building and operating machine learning workflows across cloud, Kubernetes, workstation, or bare-metal environments. It may also suit users who want open source components with optional support and security maintenance.
What it does well
- Open source stack includes Kubeflow, MLflow, and Feast.
- Supports experiment tracking, registries, and model deployment.
- Kubeflow supports AWS, Azure, and GCP Kubernetes services.
- Optional 24/7 support with SLAs is available.
- Security maintenance is stated for up to 15 years.
What to know first
- Paid support is billed per node, per year.
Plans
| Plan | Billed and limits | Price |
|---|---|---|
| Canonical MLOps support subscription | Per node, per year; price not stated on the page · Open source stack · security maintenance · optional 24/7 support with SLAs | On request |
As canonical.com lists them, read 5 Oct 2026. The maker's own page has the final word.
Verdict
Canonical MLOps combines tools for workflow management, experiment tracking, model deployment, and feature data. The stack is open source, while optional support is offered on a per-node, per-year basis without a listed price.
Facts from Canonical MLOps's own pages
- Automation
- The platform provides automated workflows, security patching, and tooling integrations for deploying and maintaining models. · canonical.com, 5 Oct 2026
- Cloud support
- Charmed Kubeflow supports AWS, Azure, and GCP Kubernetes services, including EKS, AKS, and GKE. · canonical.com, 5 Oct 2026
- Company
- Canonical says it has helped build the future of open source since 2004. · canonical.com, 5 Oct 2026
- Deployment
- Charmed MLflow can run on a workstation, CNCF-conformant Kubernetes, or a public cloud. · canonical.com, 5 Oct 2026
- Feast features
- Charmed Feast provides a centralized feature registry, offline and online stores, real-time and batch ingestion, and versioning for ML pipelines. · canonical.com, 5 Oct 2026
- Founded
- 2004 · canonical.com, 28 Sept 2026
- Headquarters
- London, United Kingdom · canonical.com, 28 Sept 2026
- Integrations
- Canonical lists Jupyter, Grafana, and Prometheus as tools to use with Charmed MLflow. · canonical.com, 5 Oct 2026
- Kubeflow
- Charmed Kubeflow deploys, scales, and manages AI workflows across clouds, virtual machines, or bare metal. · canonical.com, 5 Oct 2026
- MLflow features
- Charmed MLflow supports experiment tracking, reproducible projects, a model registry, and model deployment. · canonical.com, 5 Oct 2026
- Pricing limit
- The Canonical MLOps page describes a per-node, per-year subscription but does not state a price. · canonical.com, 5 Oct 2026
- Purpose
- Canonical MLOps is an open source platform for moving machine learning models from experimentation to production across the ML lifecycle. · canonical.com, 5 Oct 2026
- Security
- Canonical says its MLOps components receive up to 15 years of security maintenance, regular updates, and CVE fixes. · canonical.com, 5 Oct 2026
- Stack components
- Canonical’s MLOps stack includes Charmed Kubeflow, Charmed MLflow, and Charmed Feast. · canonical.com, 5 Oct 2026
- Support
- Optional 24/7 support with SLAs is available for Canonical’s MLOps stack. · canonical.com, 5 Oct 2026
Where Canonical MLOps stands on Freedom251
- MLOps Platforms#5 of 29