Github Actions
Automate your ML models lifecycle using GitHub Actions
Introduction
Welcome to the JFrog ML GitHub Actions Workflows documentation!
This guide is designed to walk you through the process of automating your machine learning model building and deployment using GitHub Actions.
Whether you're new to CI/CD or an experienced developer, you'll find actionable insights on how to leverage JFrog ML custom GitHub Actions like build-action and deploy-action to streamline your MLOps pipeline.
By the end of this guide, you'll be able to set up a fully automated workflow that builds, tests, and deploys your JFrog ML models, all within the GitHub environment.
What are Github Actions Workflows
GitHub Actions Workflows are automated pipelines that enable you to build, test, and deploy code right from your GitHub repository.
They are defined in YAML files and can be triggered by various GitHub events like push, pull requests, or manual invocation. Workflows can run jobs in parallel, have conditional execution, and can even call external APIs, making them highly flexible for CI/CD and other automation tasks.
Updated 3 months ago
Automate JFrog ML Build and Deploy with Github Actions.