Understand the project
Practical overview
When it fits
Use Polyaxon when experiments need repeatable orchestration, tracking, tuning, or distributed execution across Kubernetes-oriented infrastructure.
Who it is for
- Machine-learning and deep-learning teams
- Data-science teams using Kubernetes-based infrastructure
- Teams managing experiments, hyperparameter searches, notebooks, and distributed training
Documented uses
- Build, train, and monitor deep-learning applications
- Run and track machine-learning experiments
- Coordinate distributed training jobs
- Manage hyperparameter optimization experiments
- Connect Jupyter or JupyterLab workflows with managed AI runs
Before you choose
Requirements & limits
The project is publicly available as open-source software under the Apache-2.0 license.
- Kubernetes is central to the documented deployment and workload model.
- The repository includes a CLI, dashboard, notebook, and TensorBoard workflows.
- Distributed-job support depends on the framework-specific operator, code adaptation, and an updated Polyaxon configuration.
- Hyperparameter tuning is organized through experiment groups defining a search algorithm, search space, and model.
- The project supports multiple documented ecosystems, including Jupyter, JupyterLab, Keras, and Kubernetes.
Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.
Evidence and transparency
Sources & review
Source record details
- Source availability
- Active
- Sources checked
- 30 September 2026
- Original website title
- polyaxon/polyaxon · Official homepage title · retained in its source language