Server & SDK

Changelog for ZenML OSS and ZenML UI.

Stay up to date with the latest features, improvements, and fixes in ZenML OSS.

0.93.0 (2025-12-16)

See what's new and improved in version 0.93.0.

ZenML 0.93.0

Breaking Changes

The logging system has been completely redesigned with a new log store abstraction that now captures stdout, stderr, and all logger outputs more comprehensively. If you have custom integrations that relied on the previous logging behavior or accessed logs directly from the artifact store, you may need to update your code to use the new log store APIs. PR #4111
The REST API endpoint /api/v1/pipelines/<ID>/runs has been removed. Use /api/v1/runs?pipeline_id=<ID> instead to fetch runs for a specific pipeline. PR #4350
The logs field has been removed from the response models of pipeline runs and steps. Additionally, RBAC checks for fetching logs, downloading artifacts, and visualizations have been tightened. If you were accessing logs through these response models, you will need to use the dedicated log fetching endpoints instead. PR #4347

Enhanced CLI Experience

The ZenML CLI now provides a more flexible and user-friendly experience with improved table rendering and output options. Tables are now more aesthetically pleasing with intelligent column sizing, and you can pipe CLI output in multiple formats (JSON, YAML, CSV, TSV) by properly separating stdout and stderr streams. This makes it easier to integrate ZenML commands into scripts and automation workflows. PR #4241

Dynamic Pipeline Support

Dynamic pipelines can now be deployed and run with the local Docker orchestrator, including support for asynchronous execution. This expands the flexibility of local development and testing workflows, allowing you to leverage dynamic pipeline patterns without requiring cloud infrastructure. PR #4294, PR #4300

Pipeline Run Tracking

Each pipeline run now includes an index attribute that tracks its position within the pipeline's execution history, making it easier to identify and reference specific runs in a sequence. PR #4288

Orchestrator Health Monitoring

The Kubernetes orchestrator now includes enhanced health monitoring capabilities with configurable heartbeat thresholds. Steps that become unhealthy are preemptively stopped, and pipeline tokens are automatically invalidated when pipelines enter an unhealthy state, improving reliability and resource management. PR #4247

New Integrations

Alibaba Cloud Storage: Added support for Alibaba Cloud OSS as an artifact store, expanding ZenML's cloud storage options. PR #4289
Generic OTEL Log Store: Introduced a new log store flavor that can connect to any OTEL/HTTP/JSON compatible log intake endpoint, enabling integration with a wider range of observability platforms. PR #4309

Azure ML Enhancements

The AzureML orchestrator and step operator now support shared memory size configuration, giving you more control over resource allocation for your workloads. PR #4334

Fixed

MLflow Experiment Tracker: Fixed crashes when attempting to resume non-existent runs on Azure ML. The tracker now validates cached run IDs and gracefully creates new runs when necessary. PR #4227
Kubernetes Service Connector: Resolved failures in the ZenML server related to the Kubernetes service connector caused by incompatible urllib3 and kubernetes client library versions. PR #4312
Datadog Log Store: Improved log fetching with proper pagination support, handling the Datadog API's 1000-log limit per request through cursor-based iteration. PR #4314
Deployment Log Flushing: Eliminated blocking behavior when flushing logs during deployment invocations, preventing potential hangs at pipeline completion. PR #4354

View full release on GitHub

0.92.0 (2025-12-02)

See what's new and improved in version 0.92.0.

ZenML 0.92.0

Dynamic Pipeline Support Expansion

This release significantly expands support for dynamic pipelines across multiple orchestrators:

AWS Sagemaker Orchestrator: Added full support for running dynamic pipelines with seamless transition from existing settings and faster execution through direct use of training jobs. PR #4232
Vertex AI Orchestrator: Dynamic pipelines are now fully supported on Google Cloud's Vertex AI platform. PR #4246
Kubernetes Orchestrator: Improved dynamic pipeline handling by eliminating unnecessary pod restarts. PR #4261
Snapshot Execution: For Pro users, the new release enabled running snapshots of dynamic pipelines from the server with support for specifying pipeline parameters. PR #4253

Improved

Enhanced step.map(...) and step.product(...) to return a single future object instead of a list of futures, simplifying the API for step invocations. PR #4261
Improved placeholder run handling to prevent potential issues in dynamic pipeline execution. PR #4261
Added better typing for Docker build options with a new class to help with conversions between SDK and CLI. PR #4262

GCP Image Builder Regional Support

Added regional location support to the GCP Image Builder, allowing you to specify Cloud Build regions for improved performance and compliance:

Optional location parameter for specifying Cloud Build region
Uses regional Cloud Build endpoint ({location}-cloudbuild.googleapis.com) when location is set
Maintains backward compatibility with global endpoint as default
Includes input validation for location parameter

PR #4268

Integration Updates

Evidently Integration: Updated to version >=0.5.0 to support NumPy 2.0, resolving compatibility issues when installing packages requiring NumPy 2.0+ alongside ZenML. PR #4243

View full release on GitHub

0.91.2 (2025-11-19)

See what's new and improved in version 0.91.2.

ZenML 0.91.2

Kubernetes Deployer

Deploy your pipelines directly on Kubernetes
Full integration with Kubernetes orchestrator

Learn more | PR #4127

MLflow 3.0 Support

Added support for the latest MLflow version
Improved compatibility with modern MLflow features

PR #4160

S3 Artifact Store Fixes

Fixed compatibility with custom S3 backends
Improved SSL certificate handling for RestZenStore
Enhanced Weights & Biases experiment tracker reliability

UI Updates

Remove Video Modal (#943)
Update Dependencies (CVE) (#945)
Adjust text-color (#947)
Sanitize Dockerfile (#948)

Fixed

S3 artifact store now works with custom backends (#4186)
SSL certificate passing for RestZenStore (#4188)
Weights & Biases tag length limitations (#4189)

View full release on GitHub

0.91.1 (2025-11-11)

See what's new and improved in version 0.91.1.

ZenML 0.91.1

Hugging Face Deployer

Deploy pipelines directly to Hugging Face Spaces
Seamless integration with Hugging Face infrastructure

Learn more | PR #4119

Dynamic Pipelines (Experimental)

Introduced v1 of dynamic pipelines
Early feedback welcome for this experimental feature

Read the documentation | PR #4074

Kubernetes Orchestrator Enhancements

Container security context configuration
Skip owner references option
Improved deployment reliability

UI Updates

Display Deployment in Run Detail (#919)
Announcements Widget (#926)
Add Resize Observer to HTML Viz (#928)
Adjust Overview Pipelines (#914)
Fix Panel background (#882)
Input Styling (#911)
Display Schedules (#879)

Improved

Enhanced Kubernetes orchestrator with container security context options (#4142)
Better handling of owner references in Kubernetes deployments (#4146)
Expanded HashiCorp Vault secret store authentication methods (#4110)
Support for newer Databricks versions (#4144)

Fixed

Port reuse for local deployments
Parallel deployment invocations
Keyboard interrupt handling during monitoring
Case-sensitivity issues when updating entity names (#4140)

View full release on GitHub

0.91.0 (2025-10-25)

See what's new and improved in version 0.91.0.

ZenML 0.91.0

Local Deployer

Deploy pipelines locally with full control
Perfect for development and testing workflows

Learn more | PR #4085

Advanced Caching System

File and object-based cache invalidation
Cache expiration for bounded lifetime
Custom cache functions for advanced logic

Read the documentation | PR #4040

Deployment Visualizations

Attach custom visualizations to deployments
Fully customizable deployment server settings
Enhanced deployment management

PR #4016 | PR #4064

Python 3.13 Support

Full compatibility with Python 3.13
MLX array materializer for Apple Silicon

PR #4053 | PR #4027

UI Updates

Deployment Playground: Easier to invoke and test deployments (#861)
Global Lists: Centralized access for deployments (#851) and snapshots (#854)
Create Snapshots: Create snapshots directly from the UI (#856)
GitHub-Flavored Markdown support (#876)
Resizable Panels (#873)

Improved

Customizable image tags for Docker builds (#4025)
Enhanced deployment server configuration (#4064)
Better integration with MLX arrays (#4027)

Fixed

Print capturing incompatibility with numba (#4060)
Hashicorp Vault secrets store mount point configuration (#4088)

Breaking Changes

Dropped Python 3.9 support - upgrade to Python 3.10+ (#4053)

View full release on GitHub

0.90.0 (2025-10-02)

See what's new and improved in version 0.90.0.

ZenML 0.90.0

Pipeline Snapshots & Deployments

Capture immutable snapshots of pipeline code and configuration
Deploy pipelines as HTTP endpoints for online inference
Docker, AWS, and GCP deployer implementations

Learn more about Snapshots | Learn more about Deployments

PR #3856 | PR #3920

Runtime Environment Variables

Configure environment variables when running pipelines
Support for ZenML secrets in runtime configuration

PR #3336

Dependency Management Improvements

Reduced base package dependencies
Local database dependencies moved to zenml[local] extra
JAX array materializer support

PR #3916 | PR #3712

UI Updates

Pipeline Snapshots & Deployments: Track entities introduced in ZenML 0.90.0 (#814)

Improved

Slimmer base package for faster installations (#3916)
Better dependency management
Enhanced JAX integration (#3712)

Breaking Changes

Client-Server compatibility: Must upgrade both simultaneously
Run templates need to be recreated
Base package no longer includes local database dependencies - install zenml[local] if needed (#3916)

View full release on GitHub