0.6.2

ZenML 0.6.2 brings you the ability to serve models using MLflow deployments as well as an updated CLI interface! For a real continuous deployment cycle, we know that ZenML pipelines should be able to handle everything — from pre-processing to training to serving to monitoring and then potentially re-training and re-serving. The interfaces we created in this release are the foundation on which all of this will build.

We also improved how you interact with ZenML through the CLI. Everything looks so much smarter and readable now with the popular rich library integrated into our dependencies.

Smaller changes that you'll notice include updates to our cloud integrations and bug fixes for Windows users. For a detailed look at what's changed, see below.

What's Changed

• Updated notebook for quickstart by @htahir1 in #398
• Update tensorflow base image by @schustmi in #396
• Add cloud specific deployment guide + refactoring by @wjayesh in #400
• add cloud sub page to toc.md by @wjayesh in #401
• fix tab indent by @wjayesh in #402
• Bugfix for workflows failing due to modules not being found by @bcdurak in #390
• Improve github workflows by @schustmi in #406
• Add plausible script to docs.zenml.io pages by @alex-zenml in #414
• Add orchestrator and ECR docs by @wjayesh in #413
• Richify the CLI by @alex-zenml in #392
• Allow specification of required integrations for a pipeline by @schustmi in #408
• Update quickstart in docs to conform to examples by @htahir1 in #410
• Updated PR template with some more details by @htahir1 in #411
• Bugfix on the CLI to work without a git installation by @bcdurak in #412
• Added Ayush's Handle by @ayush714 in #417
• Adding an info message on Windows if there is no application associated to .sh files by @bcdurak in #419
• Catch matplotlib crash when running IPython in terminal by @strickvl in #416
• Automatically activate integrations when unable to find stack component by @schustmi in #420
• Fix some code inspections by @halvgaard in #422
• Prepare integration tests on kubeflow by @schustmi in #423
• Add concepts back into glossary by @strickvl in #425
• Make guide easier to follow by @wjayesh in #427
• Fix httplib to 0.19 and pyparsing to 2.4 by @jwwwb in #426
• Wrap context serialization in try blocks by @jwwwb in #397
• Track stack configuration when registering and running a pipeline by @schustmi in #429
• MLflow deployment integration by @stefannica in #415