ret Manager, Azure Key Vault, and Hashicorp Vault.Secrets are sensitive data that you don't want to store in your code or configure alongside your stacks and pipelines. ZenML includes a centralized secrets store that you can use to store and access your secrets securely.

Collaboration

Collaboration is a crucial aspect of any MLOps team as they often need to bring together individuals with diverse skills and expertise to create a cohesive and effective workflow for machine learning projects. A successful MLOps team requires seamless collaboration between data scientists, engineers, and DevOps professionals to develop, train, deploy, and maintain machine learning models.

With a deployed ZenML Server, users have the ability to create their own teams and project structures. They can easily share pipelines, runs, stacks, and other resources, streamlining the workflow and promoting teamwork.

Dashboard

When you start working with ZenML, you'll start with a local ZenML setup, and when you want to transition you will need to deploy ZenML. Don't worry though, there is a one-click way to do it which we'll learn about later.

VS Code Extension

ZenML also provides a VS Code extension that allows you to interact with your ZenML stacks, runs and server directly from your VS Code editor. If you're working on code in your editor, you can easily switch and inspect the stacks you're using, delete and inspect pipelines as well as even switch stacks.

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Last updated 15 days ago