From the course: MLOps Essentials: Model Deployment and Monitoring
Join today to access over 24,700 courses taught by industry experts.
Tools and technologies for deployment
From the course: MLOps Essentials: Model Deployment and Monitoring
Tools and technologies for deployment
- [Instructor] The tools and technologies used for deploying non-ML services apply to ML services also. Let's briefly look at the tools that are available today for deployment. For managing applications that are deployed in a cluster, Kubernetes and OpenShift are the most popular ones. For deployment of applications, there are a variety of tools available including Docker, Spinnaker, Argo CD, and GitLab. They have integrations with other services that make it easy to build automated pipelines. For deployment automation, there are tools like Ansible, Jenkins, Terraform, and Chef that are available. This space is again evolving, and we will continue to see new capabilities and integrations in this space.
Practice while you learn with exercise files
Download the files the instructor uses to teach the course. Follow along and learn by watching, listening and practicing.
Download courses and learn on the go
Watch courses on your mobile device without an internet connection. Download courses using your iOS or Android LinkedIn Learning app.
