Server & SDK

Changelog for ZenML OSS and ZenML UI.

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

0.93.1 (2026-01-14)

See what's new and improved in version 0.93.1.

🎛️ Schedule Management Enhancements

You can now pause and resume pipeline schedules directly from the CLI, giving you better control over automated pipeline executions. Use the new commands to activate or deactivate schedules on demand:

zenml pipeline schedule deactivate <schedule_id>
zenml pipeline schedule activate <schedule_id>

Currently available for the Kubernetes orchestrator. PR #4328

Schedules now support archiving as a soft-delete operation. When you delete a schedule, it's archived instead of permanently removed, preserving historical references so your pipeline runs maintain their schedule associations. PR #4339

🖥️ Dashboard Improvements

Stack Management: You can now update existing stacks directly from the UI without having to delete and recreate them. A new dedicated stack update page lets you add or replace stack components (orchestrators, artifact stores, container registries, etc.) efficiently. PR #978

Step Cache Management: View and manage step cache expiration directly from the step details panel. The cache expiration field shows when a step's cache will expire (or "Never" if no expiration is set), with expired caches clearly marked. You can also manually invalidate a step's cache with a single click. PR #976

Enhanced Logs Experience: Pipeline runs now have a dedicated logs page with a sidebar for navigating between run-level and step logs. The new logs viewer features virtualized rendering for better performance with large outputs, search and filtering capabilities, and step duration display. PR #985

⚡ Performance & Reliability

Kubernetes Orchestrator Improvements: The Kubernetes orchestrator now runs more efficiently with configurable DAG runner workers, optimized cache candidate fetching, and better error handling for failed step pods. PR #4368

Database Backup Speed: A new mydumper/myloader backup strategy delivers dramatically faster operations:

• 30x faster database backups

• 2.5x faster database restores

• 10x lower storage space requirements

PR #4358

🚀 Orchestrator Features

AzureML Dynamic Pipelines: Dynamic pipelines are now fully supported on the AzureML orchestrator, expanding your options for flexible pipeline execution. PR #4363

Kubernetes Init Container Templating: When configuring init containers for the Kubernetes orchestrator, you can now use an "{{ image }}" placeholder that will be automatically replaced with the actual orchestration/step container image. PR #4361

Fixed

• Fixed per-step compute settings not being applied correctly PR #4362

• Fixed database migration script to handle pipelines with zero runs PR #4360

• Fixed working directory in dynamic pipeline containers (was /zenml instead of /app) PR #4379

• Fixed pipeline run status updates in CONTINUE_ON_FAILURE execution mode PR #4379

• Fixed component setting shortcut keys when running snapshots PR #4379

• Improved error messages during source validation and for string type annotations PR #4359

• Fixed log storage in Kubernetes orchestrator by propagating context vars to DAG runner threads PR #4359

• Pipeline source code now included for runs triggered by snapshots/deployments PR #4359

View full release on GitHub

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0.93.0 (2025-12-16)

See what's new and improved in version 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

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0.92.0 (2025-12-02)

See what's new and improved in version 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

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0.91.2 (2025-11-19)

See what's new and improved in version 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

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0.91.1 (2025-11-11)

See what's new and improved in version 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

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0.91.0 (2025-10-25)

See what's new and improved in version 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

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0.90.0 (2025-10-02)

See what's new and improved in version 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

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0.85.0 (2025-09-12)

See what's new and improved in version 0.85.0.

Pipeline Execution Modes

• Flexible failure handling configuration

• Control what happens when steps fail

• Better pipeline resilience

Read the documentation | PR #3874

Value-Based Caching

• Cache artifacts based on content/value, not just ID

• More intelligent cache reuse

• Cache policies for granular control

PR #3900

Airflow 3.0 Support

• Full compatibility with Apache Airflow 3.0

• Access to latest Airflow features and improvements

PR #3922

UI Updates

• Timeline View: New way to visualize pipeline runs alongside the DAG (#799)

• Client-Side Structured Logs (#801)

• Default Value for Arrays (#798)

Improved

• Enhanced caching system with value-based caching (#3900)

• More granular cache policy control

• Better pipeline execution control (#3874)

Breaking Changes

• Local orchestrator now continues execution after step failures

• Docker package installer default switched from pip to uv (#3935)

• Log endpoint format changed (#3845)

View full release on GitHub

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0.84.3 (2025-08-27)

See what's new and improved in version 0.84.3.

ZenML Pro Service Account Authentication

• CLI login support via zenml login --api-key

• Service account API keys for programmatic access

• Organization-level access for automated workflows

PR #3895 | PR #3908

ZenML Pro Service Account Authentication

• CLI login support via zenml login --api-key

• Service account API keys for programmatic access

• Organization-level access for automated workflows

PR #3895 | PR #3908

Improved

• Enhanced Kubernetes resource name sanitization (#3887)

• Relaxed Click dependency version constraints (#3905)

View full release on GitHub

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0.84.2 (2025-08-06)

See what's new and improved in version 0.84.2.

Kubernetes Orchestrator Improvements

• Complete rework using Jobs instead of raw pods

• Better robustness and automatic restarts

• Significantly faster pipeline compilation

PR #3869 | PR #3873

Kubernetes Orchestrator Improvements

• Complete rework using Jobs instead of raw pods

• Better robustness and automatic restarts

• Significantly faster pipeline compilation

PR #3869 | PR #3873

Improved

• Enhanced Kubernetes orchestrator robustness (#3869)

• Faster pipeline compilation for large pipelines (#3873)

• Better logging performance (#3872)

View full release on GitHub

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0.84.1 (2025-07-30)

See what's new and improved in version 0.84.1.

Step Exception Handling

• Improved collection of exception information

• Better debugging capabilities

PR #3838

External Service Accounts

• Added support for external service accounts

• Improved flexibility

PR #3793

Kubernetes Orchestrator Enhancements

• Schedule management capabilities

• Better error handling

• Enhanced pod monitoring

PR #3847

Dynamic Fan-out/Fan-in

• Support for dynamic patterns with run templates

• More flexible pipeline architectures

PR #3826

Step Exception Handling

• Improved collection of exception information

• Better debugging capabilities

PR #3838

External Service Accounts

• Added support for external service accounts

• Improved flexibility

PR #3793

Kubernetes Orchestrator Enhancements

• Schedule management capabilities

• Better error handling

• Enhanced pod monitoring

PR #3847

Dynamic Fan-out/Fan-in

• Support for dynamic patterns with run templates

• More flexible pipeline architectures

PR #3826

Fixed

• Vertex step operator credential refresh (#3853)

• Logging race conditions (#3855)

• Kubernetes secret cleanup when orchestrator pods fail (#3846)

View full release on GitHub

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0.84.0 (2025-07-11)

See what's new and improved in version 0.84.0.

Early Pipeline Stopping

• Stop pipelines early with Kubernetes orchestrator

• Better resource management

PR #3716

Step Retries

• Configurable step retry mechanisms

• Improved pipeline resilience

PR #3789

Step Status Refresh

• Real-time status monitoring

• Enhanced step status refresh capabilities

PR #3735

Performance Improvements

• Thread-safe RestZenStore operations

• Server-side processing improvements

• Enhanced pipeline/step run fetching

PR #3758 | PR #3762 | PR #3776

UI Updates

• Refactor Onboarding (#772) & Survey (#770)

• Stop Runs directly from UI (#755)

• Step Refresh (#773)

• Support multiple log origins (#769)

Improved

• New ZenML login experience (#3790)

• Enhanced Kubernetes orchestrator pod caching (#3719)

• Easier step operator/experiment tracker configuration (#3774)

• Orchestrator pod logs access (#3778)

Fixed

• Fixed model version fetching by UUID (#3777)

• Visualization handling improvements (#3769)

• Fixed data artifact fetching (#3811)

• Path and Docker tag sanitization (#3816 | #3820)

Breaking Changes

• Kubernetes Orchestrator Compatibility: Client and orchestrator pod versions must match exactly

View full release on GitHub

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