Kubeflow
A Kubernetes-native set of open-source projects for running data, ML and AI workloads.
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About Kubeflow
Kubeflow is a collection of modular open-source projects that together form a stack for data and AI workloads on Kubernetes. Teams can mix and match subprojects such as the Spark Operator across the AI lifecycle, from training jobs to serving models and AI agents.
It aims to let the same code run on a laptop, on-premises or in any cloud without deep Kubernetes knowledge. Kubeflow is a graduated CNCF project and suits platform teams running ML at scale on their own clusters.
Strengths
- Modular subprojects you can adopt separately
- Runs on-premises or in any cloud
- Graduated CNCF project with a large contributor community
Limitations
- Requires a Kubernetes cluster
- Aimed at platform teams rather than individual users
Details
- Pricing
- FreeFree and open source.
- License
- Apache-2.0
- Developer
- The Kubeflow contributors
- Platforms
- Self-hosted
- How it runs
- Self-hosted
- Account
- Not required
- Best suited for
- Platform teams running ML training and serving on Kubernetes
- Categories
- Container tools, AI developer tools
- Last verified
- Added
- Sources
Alternatives to Kubeflow
Compare allSoftware that can replace Kubeflow for an important use case, and what changes if you switch.
ZenML
An open-source framework for writing ML pipelines and AI agents in Python and running them on your own infrastructure.
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.
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.
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.
Kubeflow as an alternative
Listings that name Kubeflow as an alternative.
KServe
A Kubernetes-native platform for serving predictive and generative AI models at scale.
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 necessarily a direct replacement.
NVIDIA Triton Inference Server
An open-source inference server for deploying machine learning models from many frameworks on GPUs and CPUs.
GPUStack
An open-source GPU cluster manager for serving AI models with vLLM and SGLang on your own hardware.
Weights & Biases
A hosted platform for tracking machine learning experiments, evaluating models and tracing LLM applications.
TensorBoard
A visualization toolkit for inspecting machine learning training runs, metrics and model graphs.
