Overview

Polyaxon experimentation is a set of tools for:

• Processing data and Training ML models
• Running Notebooks and Tensorboards, and launching apps and dashboards
• Running distributed jobs using cloud-native operators
• Tracking metrics and artifacts
• Driving analyses and visualizing results

Features

Polyaxon experimentation tools are:

• Reproducible: Code, environment, and specification are versioned, dependencies are containerized, and every execution is tracked and reproducible.
• Serverless and Kubernetes native so they benefit from all the benefits containerization provides: portability, scalability, reliability.
• Massive scale: Fully distributed, several scheduling strategies, fault-tolerant, scale to multiple nodes, clusters, and hundreds of thousands of concurrent executions.
• Sharable: Any component can be promoted with typed inputs and outputs to be sharable and reusable.