Azkaban

Azkaban

Azkaban is an open source workflow scheduler created at LinkedIn to run Hadoop jobs. It allows users to easily create, schedule and monitor workflows made up of different jobs. Azkaban provides a web interface and scheduling capabilities to manage dependencies between jobs.
Azkaban image
workflow scheduler hadoop jobs open-source

Azkaban: Open Source Workflow Scheduler

A workflow scheduler for managing Hadoop jobs, allowing users to create, schedule and monitor workflows with web interface and scheduling capabilities.

What is Azkaban?

Azkaban is an open source batch workflow job scheduler created at LinkedIn in 2012. It is used to schedule and run Hadoop jobs, manage dependencies between jobs and prevent jobs from failing or running simultaneously. Azkaban provides an easy to use web user interface to create and schedule workflows and provides capabilities to monitor running workflows.

Key features of Azkaban include:

  • Web-based user interface to upload jobs, build workflows and set schedules
  • Workflow definition language to easily build dependencies between jobs
  • Schedule workflows to run at particular times or dates
  • Alerts and notifications when workflows fail or complete
  • Monitor running workflows on a visual graph
  • Role based access control to manage users
  • Track history and stats of previously run workflows

Azkaban is written in Java and can be configured to run on a single machine or a Hadoop cluster. It is widely used by companies to schedule recurring ETL, analysis and machine learning jobs. The automated scheduling helps improve efficiency and prevents manual errors.

Azkaban Features

Features

  1. Web-based workflow scheduler
  2. Allows creating, managing and monitoring workflows
  3. Built-in authentication and authorization
  4. Supports workflow dependencies
  5. Provides execution logs and metrics
  6. Plugin system for extensibility
  7. Alerting and failure handling

Pricing

  • Open Source

Pros

Open source and free

Easy to use interface

Scalable and reliable

Integrates well with Hadoop

Good documentation and community support

Cons

Limited visualization and monitoring

Steep learning curve for advanced features

Not ideal for real-time workflows

No commercial support offered


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