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Principle:Datahub project Datahub Actions Framework Installation

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Metadata

Field Value
Principle ID P-DHACT-001
Title Actions Framework Installation
Category Event-Driven Automation
Status Active
Last Updated 2026-02-10
Repository Datahub_project_Datahub
Knowledge Sources GitHub - datahub-project/datahub, DataHub Documentation
Domains Event_Processing, Automation, Metadata_Management

Overview

The practice of installing the DataHub Actions framework for event-driven metadata automation. The Actions framework provides a plugin-based event processing pipeline that reacts to real-time metadata changes emitted by DataHub, enabling automated workflows such as notifications, tag propagation, and metadata synchronization.

Description

Actions framework installation provisions the datahub-actions CLI and all built-in action plugins. The framework is distributed as a Python package (acryl-datahub-actions) that bundles both the core pipeline runtime and a suite of pre-built action plugins.

The framework depends on:

  • Core DataHub SDK: acryl-datahub[datahub-kafka] for metadata model classes and Kafka integration
  • Pipeline runtime: Click CLI, PyYAML, Pydantic, tenacity (retry logic), prometheus-client (monitoring)
  • Kafka client: confluent-kafka[schemaregistry] for consuming metadata change events

Upon installation, the following built-in action plugins are registered via Python entry points:

Plugin Name Class Purpose
executor ExecutorAction Execute ingestion recipes remotely
slack SlackNotificationAction Send Slack notifications on metadata changes
teams TeamsNotificationAction Send Microsoft Teams notifications
metadata_change_sync MetadataChangeSyncAction Synchronize metadata changes across DataHub instances
tag_propagation TagPropagationAction Propagate tags through lineage
term_propagation TermPropagationAction Propagate glossary terms through lineage
snowflake_tag_propagation SnowflakeTagPropagatorAction Propagate tags to Snowflake
doc_propagation DocPropagationAction Propagate documentation through lineage

Usage

Use this principle when setting up event-driven automation that reacts to real-time metadata changes in DataHub. This is the required first step before configuring any action pipeline. Common scenarios include:

  • Setting up Slack or Teams notifications for metadata changes
  • Enabling automated tag or glossary term propagation across lineage
  • Deploying custom metadata synchronization workflows
  • Building custom actions that respond to DataHub events

Theoretical Basis

Plugin-based framework architecture: The Actions framework follows a core-plus-plugins design. The core framework provides the event pipeline infrastructure (Kafka consumer, event deserialization, pipeline orchestration, retry logic), while action plugins provide specific behaviors. Installation registers all plugins via Python entry points under the datahub_actions.action.plugins namespace, enabling the framework to discover and instantiate plugins by name at runtime. This architecture supports extensibility -- third-party plugins can be installed separately and discovered automatically through the same entry point mechanism.

Related

Implementation:Datahub_project_Datahub_Pip_Install_Datahub_Actions

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