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ZenML

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Introduction

Core Concepts

Installation

Deploying ZenML

One Click Deployment using CLI

Deploying with Docker

Deploying ZenML on cloud using Docker or Helm

Deploying with Helm

A collection of architecture diagrams that shows the interactions of different environments in mature productions settings.

Architecture Diagrams

Resources to learn how to use ZenML practically.

Examples

Pipelines

How to use ZenML's native dashboard to monitor your pipelines

Dashboard Overview

Fetching Pipelines

Step Parameterization and Caching

How to configure MLOps tooling and infrastructure with stacks

Stacks

Registering stacks, components, and flavors.

Registering Stacks

You can manage stacks in many different ways.

Managing Stacks

How to collaborate with your team in ZenML

Collaboration

Connect to a simply deployed ZenML on the cloud.

Connecting to a Deployed ZenML

How to add users to your ZenML deployment

Inviting Users

How roles and permissions work within ZenML

User Roles & Permissions

In-depth Configuration

Configuring pipelines, steps, and stack components in ZenML.

Runtime Settings

How ZenML uses Docker images to run your pipeline

Containerization (Docker)

How to use materializers to pass custom data types through steps

Passing Custom Data Types through Steps (Materializers)

Specifying Step Resources

How to ensure your pipelines or steps run on GPU-backed hardware

Enabling GPU-backed hardware

Schedule runs to add automation to your pipelines

Scheduling Pipeline Runs

How to use step fixtures to access the active ZenML stack from within a step

Accessing Metadata within Steps

How to control the order in which steps get executed

Controlling the Step Execution Order

Extending Stacks

How to write a custom stack component flavor

Writing Custom Flavors

How to start, stop, provision, and deprovision stacks and stack components

Managing Stack Component States

How to manage external, longer-lived services

Managing External Services

Practical MLOps

Introduction to Stack recipes which help you deploy a full MLOps stack in minutes!

Stack Recipes

Switching orchestrators to run in the cloud

Switching Orchestration

Secrets Management

Tracking Experiments

Validate data as it flows through your pipelines

Validating Data

Deploy models to the cloud using production-grade stacks

Deploying Models and Batch Inference

Categories of MLOps Tools

Overview of third-party ZenML integrations

Integration Overview

Orchestrators

Local Orchestrator

How to orchestrate pipelines locally in Docker

Local Docker Orchestrator

How to orchestrate pipelines with Kubeflow

Kubeflow Orchestrator

How to orchestrate pipelines with Kubernetes

Kubernetes Orchestrator

How to orchestrate pipelines with Vertex AI

Google Cloud VertexAI Orchestrator

How to orchestrate pipelines with Amazon Sagemaker

AWS Sagemaker Orchestrator

Tekton Orchestrator

How to orchestrate pipelines with Airflow

Airflow Orchestrator

How to orchestrate pipelines with GitHub Actions

GitHub Actions Orchestrator

Develop a Custom Orchestrator

How to set up the persistent storage for your artifacts

Artifact Stores

How to store artifacts on your local filesystem

Local Artifact Store

How to store artifacts in an AWS S3 bucket

Amazon Simple Cloud Storage (S3)

How to store artifacts using GCP Cloud Storage

Google Cloud Storage (GCS)

How to store artifacts using Azure Blob Storage

Azure Blob Storage

Develop a Custom Artifact Store

How to set up the storage for Docker images

Container Registries

Default Container Registry

How to store container images in DockerHub

DockerHub

How to store container images in Amazon ECR

Amazon Elastic Container Registry (ECR)

Google Cloud Container Registry

Azure Container Registry

GitHub Container Registry

How to develop a custom container registry

Develop a Custom Container Registry

Secrets Managers

Local Secrets Manager

AWS Secrets Manager

Google Cloud Secrets Manager

Azure Secrets Manager

GitHub Secrets Manager

HashiCorp Vault Secrets Manager

Develop a Custom Secrets Manager

How to enhance and maintain the quality of your data and the performance of your models with data profiling and validation

Data Validators

How to use Great Expectations to run data quality checks in your pipelines and document the results

Great Expectations

How to test the data and models used in your pipelines with Deepchecks test suites

Deepchecks

How to keep your data quality in check and guard against data and model drift with Evidently profiling

Evidently

How to collect and visualize statistics to track changes in your pipelines data with whylogs/WhyLabs profiling.

Whylogs

Develop a Custom Data Validator

Experiment Trackers

How to log and visualize experiments with MLflow

MLflow

How to log and visualize experiments with Weights & Biases

Weights & Biases

How to log and visualize experiments with neptune.ai

Neptune

How to develop a custom experiment tracker

Develop a Custom Experiment Tracker

How to deploy your models and serve real-time predictions

Model Deployers

How to deploy your models locally with MLflow

How to deploy models to Kubernetes with Seldon Core

Seldon

How to deploy models to Kubernetes with KServe

KServe

How to deploy your models locally with BentoML

BentoML

Develop a Custom Model Deployer

How to execute individual steps in specialized environments

Step Operators

How to execute individual steps in SageMaker

Amazon SageMaker

How to execute individual steps in Vertex AI

Google Cloud VertexAI

How to execute individual steps in AzureML

AzureML

Spark

Develop a Custom Step Operator

How to send automated alerts to chat services

Alerters

How to send automated alerts to a Slack channel

Slack Alerter

Develop a Custom Alerter

Feature Stores

How to manage data in Feast feature stores

Feast

Develop a Custom Feature Store

Annotators

How to annotate data using Label Studio with ZenML

Label Studio

Develop a Custom Annotator

Image Builders

Local Image Builder

How to build container images with Kaniko

Kaniko Image Builder

Develop a Custom Image Builder

Best practices, recommendations, and tips from the ZenML team

Best Practices

Global Configuration

How to control ZenML behavior with environmental variables

System Environmental Variables

How to migrate from ZenML 0.13.2 to 0.20.0

Migration Guide 0.20.0

Contribution Guide

A guide to debug common issues and get help.

Debugging Guide

External Integration Guide

What are the usage statistics ZenML collects

Usage Analytics

All possible ways for our community to get in touch with ZenML.

Community & Content

Glossary

Find answers to the most frequently asked questions about ZenML

Getting Started

Starter Guide

Advanced Guide

Guidelines

Misc

Reference

CLI Cheat Sheet