CDM Spark Cluster Manager API

A simple API service for managing Spark clusters in Kubernetes for JupyterHub users. This service acts as an intermediary between user pods and Kubernetes, providing a secure way to manage Spark clusters without requiring direct Kubernetes access.

⚠️ Important: This API service is intended to be deployed only within a Kubernetes environment.

Features

• Create and manage Spark clusters for individual users
• RESTful API endpoints for cluster management
• Automatic cleanup of resources
• KBase user authentication and authorization

Setup Local Development Environment

Prerequisites

• Python 3.11+
• pip

Installation

1. Clone the repository:

   git clone [email protected]:kbase/cdm-kube-spark-manager.git
   cd cdm-kube-spark-manager
   

2. Install dependencies:

   uv sync --locked # only the first time or when uv.lock changes
   

Local Unit Testing

The project uses pytest for unit testing. To run the tests:

# Run all tests
PYTHONPATH=src pytest -v --cov=src --cov-report=xml tests

API Endpoints

Health Check

• GET /health - Check the health status of the service

Cluster Management

• POST /clusters - Creates a new Spark cluster for the authenticated user
• GET /clusters - Get the status of the Spark cluster for the authenticated user, if it exists
• DELETE /clusters - Deletes the Spark cluster belonging to the authenticated user.

Kubernetes Deployment

For instructions on deploying to local Kubernetes, see the Kubernetes README.