MLRun provides an open-source MLOps platform for managing machine learning applications, pipelines, and CI/CD delivery.
Open source
24 alternativesKubeflow Pipelines
Kubeflow Pipelines orchestrates and manages machine learning workflows on Kubeflow.
About Kubeflow Pipelines
Kubeflow Pipelines is an open source repository that is part of the Kubeflow machine learning toolkit, designed to simplify the orchestration, management, and scaling of ML workflows on Kubernetes. It provides a dedicated service and SDK for building, running, and tracking end-to-end machine learning pipelines, with support for both standalone deployment and integration with the full Kubeflow platform.
Users can create reusable pipeline components and full workflows to streamline ML experimentation, reduce redundant development work, and standardize end-to-end ML processes. The system uses the Argo Emissary executor for pipeline runs, and includes official documentation, sample pipelines, and community resources for both end users and contributors. It is suited for data scientists, ML engineers, and teams that build and deploy machine learning workloads on Kubernetes infrastructure.
Key features
- Orchestrates end-to-end machine learning workflows on Kubernetes
- Includes a Python SDK for building reusable ML pipelines
- Deploys as a standalone service or part of Kubeflow Platform
- Enables reuse of pipeline components to speed up ML development
- Uses Argo Emissary executor for pipeline runs
Best for: It is most beneficial for data science and ML engineering teams that build, test, and deploy machine learning workflows on Kubernetes.
Good for
- Open source with no licensing fees for use or modification
- Portable and scalable for Kubernetes-based ML deployments
- Supports pipeline component reuse to reduce redundant work
- Includes documentation and community resources for users and contributors
Watch out for
- Requires Kubernetes infrastructure to deploy and run
- Argo Workflows 3.x is deprecated for future KFP 3.0 releases
- AI-generated DeepWiki documentation may contain inaccuracies
Kubeflow Pipelines at a glance
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
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Kubeflow Pipelines FAQ
What is Kubeflow Pipelines used for?
It orchestrates and manages end-to-end machine learning workflows on Kubernetes, with tools for experimentation and reuse of ML pipeline components.
Can Kubeflow Pipelines run without the full Kubeflow platform?
Yes, it can be deployed as a standalone service separate from the full Kubeflow platform.
Is Kubeflow Pipelines free to use?
It is open source, so there are no licensing fees for use or modification.
What executor does Kubeflow Pipelines use for pipeline runs?
It uses the Argo Emissary executor, which operates independently of the Kubernetes container runtime.
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