#6262nd of 92 in Agent platforms
pipelines
ML pipeline orchestrator with a Python SDK, built on Argo Workflows
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- Stars
- 4.3k
- License
- Apache-2.0
- Last commit
- Nov 2026
- Last release
- Oct 2026
- Language
- Python
Missed the latest GitHub check; these facts may be older.
Overview
Kubeflow Pipelines runs reusable, containerized ML workflows on Kubernetes. Pipelines are written with the Python SDK (kfp) and executed through Argo Workflows using the Emissary executor, with experiment management and reusable components. It installs standalone or as part of the Kubeflow Platform; this branch (KFP 3.0) targets Argo Workflows 4.0 and 4.1 with MySQL 8.
Who it is for: Platform and ML engineers running ML workflows on Kubernetes
Strengths
- Pipelines defined in Python with the kfp SDK, published on PyPI
- Components and pipelines are reusable across experiments and runs
- Emissary executor is independent of the Kubernetes container runtime
- Installs standalone or as part of the Kubeflow Platform
Weaknesses
- Requires a Kubernetes cluster; no single-machine install described
- KFP 3.0 branch drops Argo 3.x; Argo must be upgraded to 4.x first
- Depends on Argo Workflows and MySQL 8, adding operational overhead
- General ML orchestration; no LLM or agent-specific features in the README
What it needs
- Needs Kubernetes, Argo Workflows 4.0/4.1, MySQL 8
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