ZenML Updates

Our monthly roundup: new features with 0.80.0 release, more new models, and an MCP server for ZenML

Our monthly roundup: Hamza visits the US, a new course built on ZenML and why workflows are better than autonomous agents!

ZenML 0.75.0 introduces dashboard enhancements that allow users to create and update stack components directly from the dashboard, along with improvements to service connectors, model artifact handling, and documentation. This release streamlines ML workflows with better component management capabilities, enhanced SageMaker integration, and critical fixes for custom flavor components and sorting logic.

ZenML 0.74.0 introduces key cloud provider features including SageMaker pipeline scheduling, Azure Container Registry implicit authentication, and Vertex AI persistent resource support. The release adds API Tokens for secure, time-boxed API authentication while delivering comprehensive improvements to timezone handling, database performance, and Helm chart deployments.

Our monthly roundup: AI Infrastructure Summit insights, new experiment comparison tools, and a deep dive into AI Engineering roles

ZenML's new Experiment Comparison Tool brings powerful experiment tracking capabilities to your ML pipelines. Compare up to 20 pipeline runs simultaneously through intuitive tabular and parallel coordinates visualizations, helping teams derive actionable insights from their pipeline metadata. Now available in the Pro tier dashboard.

ZenML 0.71.0 features the Modal Step Operator for fast, configurable cloud execution, dynamic artifact naming, and enhanced visualizations. It improves API token management, dashboard usability, and infrastructure stability while fixing key bugs. Expanded documentation supports advanced workflows and big data management.

ZenML 0.68.0 introduces several major enhancements including the return of stack components visualization on the dashboard, powerful client-side caching for improved performance, and a streamlined onboarding process that unifies starter and production setups. The release also brings improved artifact management with the new `register_artifact` function, enhanced BentoML integration (v1.3.5), and comprehensive documentation updates, while deprecating legacy features including Python 3.8 support.

This release incorporates updates to the SageMaker Orchestrator, DAG Visualizer, and environment variable handling. It also includes Kubernetes support for Skypilot and an updated Deepchecks integration. Various other improvements and bug fixes have been implemented across different areas of the platform.