Kubeflow Pipelines orchestrates and manages machine learning workflows on Kubeflow.
Open source
24 alternativesZenML
ZenML provides a platform for machine learning pipelines and AI agents.
About ZenML
ZenML is an open-source, Python-based platform for building machine learning and AI workflows, including traditional ML use cases, LLM workflows and agents. Users write pipelines that run on pluggable infrastructure backends (stacks) and can embed any Python logic, such as model training or an agentic loop. ZenML then automatically containerizes and tracks code, records individual runs with metrics, logs and metadata, and abstracts away infrastructure complexity while integrating existing tools such as MLflow, LangGraph, Langfuse, Amazon SageMaker and Google Cloud Vertex.
The project uses a client-server architecture with an integrated web dashboard. It can run locally, or the server can be deployed separately in production and reached by clients through a login command. An MCP server allows querying pipelines and workflow state. The repository points to documentation, tutorials and example pipelines covering agents, RAG, batch inference, model deployment and fine-tuning. Pricing details are not stated on the repository page.
Key features
- Write Python pipelines that run on any infrastructure backend (stacks)
- Embed model training, LLM or agentic loop logic in pipelines
- Automatic containerization and tracking of code
- Run tracking with metrics, logs and metadata
- Integrations with MLflow, LangGraph, Langfuse, SageMaker, Vertex
- MCP server for querying pipelines and workflow state
- Client-server architecture with an integrated web dashboard
Best for: ML and AI engineers in company settings building traditional ML, LLM or agent workflows who want infrastructure-agnostic pipeline orchestration.
Good for
- Open-source Python framework distributed through GitHub and installable via pip
- Pipelines can target any infrastructure backend and connect to existing tools
- Supports both local development and a separately deployed production server
Watch out for
- Pricing for ZenML Pro is not given on the repository page
- No geographic restrictions, usage limits or data-handling details are stated in the source
ZenML at a glance
- Website
- github.com/zenml-io/zenml
- 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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ZenML FAQ
Who is ZenML built for?
ML or AI engineers working on traditional ML use cases, LLM workflows or agents in a company setting.
How is ZenML installed?
Install with pip install "zenml[server]" for server capabilities, or pip install zenml for a slimmer client, then run zenml init and zenml login.
Can ZenML run both locally and in production?
Yes. pip install "zenml[local]" runs both client and server locally, while in production the server is deployed separately and clients connect with zenml login .
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