Kubeflow Pipelines orchestrates and manages machine learning workflows on Kubeflow.
Open source
24 alternativesCML
CML provides continuous machine learning and CI/CD workflows for machine learning projects.
About CML
CML (Continuous Machine Learning) is an open-source command-line tool for continuous integration and delivery (CI/CD) in machine learning projects, with a focus on MLOps. It is used to automate workflow steps such as machine provisioning, model training and evaluation, comparing ML experiments across project history, and monitoring changing datasets. The tool can train and evaluate models and generate a visual report with results and metrics automatically on each pull request.
CML works with GitLab, GitHub, or Bitbucket accounts. It uses DVC to codify data and models instead of pushing them to a Git repository. Optional cloud storage and self-hosted or cloud runners, such as AWS EC2 or Azure, can be added, and the source states that no separate databases or additional services are required. Setup requires a platform account, and GitLab use requires a personal access token. Pricing is not stated in the source.
Key features
- Automates model training and evaluation on each pull request
- Generates visual reports with results and metrics for ML experiments
- Launches runners locally or on cloud providers with cml runner launch
- Posts markdown reports as comments in GitLab or GitHub workflows
- Creates GitHub checks and pull requests from report files
- Connects experiments to a Tensorboard.dev link
Best for: Machine learning teams that already use GitLab, GitHub, or Bitbucket and want model training and metric reports tied to pull requests.
Good for
- Open source, with the code and license available in the public repository
- Runs on existing Git hosting platforms without requiring additional services
- Pre-built Docker images include NodeJS, Python 3, DVC, and CML on an Ubuntu LTS base
Watch out for
- Requires an account on GitLab, GitHub, or Bitbucket to begin
- GitLab use requires a personal access token
- Self-hosted setups may need NodeJS and Python to be installed separately
CML at a glance
- Website
- github.com/iterative/cml
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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CML FAQ
Which platforms does CML work with?
The source says CML works with GitLab, GitHub, and Bitbucket. Setup guides are provided for each of these.
Does CML need a separate database or service?
The source states that no databases or additional services or complex setup are needed to build an ML platform on GitLab, Bitbucket, or GitHub. Cloud storage and cloud or self-hosted runners are optional.
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