What is Polyaxon used for?

Polyaxon is an open-source AI control plane for Kubernetes that schedules, runs, debugs, observes, and automates AI/ML workloads, agents, and sandboxes on your own infrastructure. It is a good fit for training and fine-tuning models on Kubernetes, serving and deploying ML applications, and running interactive sandboxes and notebooks.

Is Polyaxon open source?

Yes. Polyaxon is open source under the Apache-2.0 licence. Its source code is on GitHub at polyaxon/polyaxon.

Yes. Polyaxon is open source, so the software itself is free to use.

Can I self-host Polyaxon?

Yes. Polyaxon can be self-hosted on your own server or infrastructure.

What is Polyaxon an alternative to?

Polyaxon is an open-source alternative to Amazon SageMaker, Google Vertex AI, Weights & Biases and Dataiku. Other open-source alternatives to Amazon SageMaker include Kubeflow, MLflow and Backend.AI.

Is Polyaxon actively maintained?

Yes. The most recent commit to Polyaxon was on 13 October 2026. The project has 3.7k stars on GitHub.

Polyaxon: open-source alternative to Amazon SageMaker

About Polyaxon

Polyaxon is an open-source AI control plane designed to run on Kubernetes. It enables scheduling, tracking, and governance of AI/ML workloads, including GPU training, agent sessions, and sandboxes, all within self-hosted deployments. The platform supports training, services, and sandboxes using shared specs, queues, governance, and data connections.

It provides a unified interface for training and fine-tuning models, serving inference, running notebooks, and managing interactive sessions. Polyaxon integrates with various frameworks, clients, and APIs, and offers governance features such as organizations, teams, authentication, audit logs, and policies. It is suitable for teams that need to manage AI workloads on their own clusters and storage backends.

Key features

Scheduling and orchestration of runs, experiments, and batch jobs
Training and fine-tuning with support for LoRA and SFT
Services for serving, inference, notebooks, TensorBoard, and ML apps
Sandboxes with SSH, tmux, interactive, and background modes
Governance with organizations, teams, authn/authz, audit logs, and policies
Execution controls via agents, queues, connections, and presets

Good fit for

Training and fine-tuning models on Kubernetes
Serving and deploying ML applications
Running interactive sandboxes and notebooks

Built with: MDX tools; Kubernetes tools
Tags: ai; kubernetes; mlops; orchestration; training; control-plane

Polyaxon: questions and answers

What is Polyaxon used for?: Polyaxon is an open-source AI control plane for Kubernetes that schedules, runs, debugs, observes, and automates AI/ML workloads, agents, and sandboxes on your own infrastructure. It is a good fit for training and fine-tuning models on Kubernetes, serving and deploying ML applications, and running interactive sandboxes and notebooks.
Is Polyaxon open source?: Yes. Polyaxon is open source under the Apache-2.0 licence. Its source code is on GitHub at polyaxon/polyaxon.
Is Polyaxon free?: Yes. Polyaxon is open source, so the software itself is free to use.
Can I self-host Polyaxon?: Yes. Polyaxon can be self-hosted on your own server or infrastructure.
What is Polyaxon an alternative to?: Polyaxon is an open-source alternative to Amazon SageMaker, Google Vertex AI, Weights & Biases and Dataiku. Other open-source alternatives to Amazon SageMaker include Kubeflow, MLflow and Backend.AI.
Is Polyaxon actively maintained?: Yes. The most recent commit to Polyaxon was on 13 October 2026. The project has 3.7k stars on GitHub.