kubeflow/arena

What it solves

Arena simplifies the process of running and monitoring machine learning training jobs on GPU clusters. It removes the need for data scientists to have deep knowledge of Kubernetes, Helm, or Kubeflow, allowing them to manage distributed training as if they were working on a single machine.

How it works

Arena provides a command-line interface (CLI) that abstracts the complexity of the backend infrastructure. It uses Kubernetes, Helm, and Kubeflow in the backend to orchestrate training jobs, while offering simple commands to launch, monitor, and check results. It also includes a top command to help users track available GPU resources within the cluster.

Who it’s for

Data scientists who need to utilize the power of GPU clusters for machine learning training (specifically TensorFlow) without needing to become experts in Kubernetes orchestration.

Highlights

• Command-line interface for easy job management and monitoring.
• Support for solo and distributed TensorFlow training.
• Integrated GPU resource and node management via a top command.
• Abstracts Kubernetes, Helm, and Kubeflow complexity for the end user.