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Deploying AI Projects Through a Jenkins Pipeline
- CI/CD automates the build, tests, and deployment of models, allowing large teams to collaborate and deploy seamlessly
- Jenkins facilitates building, testing, and deploying AI projects and has a user interface to track pipeline runs visually
- Steps to deploying AI projects through a Jenkins pipeline include prerequisites like a code hosting platform, KitOps, Jenkins, and a container registry
- After installation, the KitOps can be verified by running the 'kit version' command on the local terminal
- By logging in to the Jozu Hub, you can unpack any of the available ModelKits and grab a Qwen model from Jozu Hub
- Create Jenkins credentials to securely enter your Jozu Hub username and password, and then build your pipeline by configuring the pipeline to grab the Jenkinsfile from the GitHub repository
- It is very frustrating to deploy your AI projects manually every time you make a change, whereas Jenkins and KitOps automate the building, testing, and deployment of models and their dependencies in production
- Jenkins and KitOps improve team collaboration, resulting in faster, more reliable deployments
- You can automate deployment whenever a change is made using Jenkins and KitOps
- Use KitOps to package models and manage dependencies for automating the deployment process of AI projects
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