Alternatives to Kubeflow

A Kubernetes-native set of open-source projects for running data, ML and AI workloads. The listings below can replace it for an important use case. Each note says what changes if you switch.

Replacements

Listings that take over the same core job as Kubeflow.

  • ZenML

    An open-source framework for writing ML pipelines and AI agents in Python and running them on your own infrastructure.

    FreemiumOpen sourceSelf-hostedCommand line

    ZenML writes ML pipelines in plain Python that are portable across orchestrators and clouds under Apache 2.0, without requiring a Kubernetes cluster.

  • Flyte

    An open-source orchestration platform for durable data, machine learning and AI agent workflows written in Python.

    FreeOpen sourceWebSelf-hostedCommand line

    Flyte orchestrates durable data, ML and agent workflows in Python with failure recovery and a local devbox, though Flyte 1 users must migrate to Flyte 2.

  • MLflow

    An open-source platform for tracing, evaluating and managing LLM applications, agents and machine learning models.

    FreeOpen sourceWebSelf-hostedCommand line

    MLflow covers experiment tracking, evaluation and model management with tracing, rather than Kubernetes-native training and serving, and needs a self-hosted server for teams.

Also worth comparing

These listings name Kubeflow as their own alternative, so the relationship runs both ways.

  • KServe

    A Kubernetes-native platform for serving predictive and generative AI models at scale.

    FreeOpen sourceSelf-hosted

    Kubeflow is a broader Apache-2.0 set of Kubernetes projects for training and serving ML workloads, adopted modularly and backed as a graduated CNCF project.

Similar software

Related functionality, not a direct replacement.