There is little chance you haven't heard about Apache Airflow yet. It is one of the most popular tools for managing data pipelines. Let's go through this framework's features so you can decide if it suits your needs.

What is Apache Airflow? 

If you are in need of an open-source workflow automation tool, you should definitely consider adopting Apache Airflow. This Python-based technology makes it easy to set up and maintain data pipelines. Directed Acyclic Graphs (called DAGs, in short ) help users manage, structure and organize the processes of extracting data from an input source and then transforming this data and loading it into database or data warehouse in order to perform analysis or create a report (sets of such processes are known as ETL pipelines).

Apache Airflow enables you to schedule your automated workflows, which actually means that after doing so, they will run on their own, and you can focus on other tasks. This tool provides you with quite an intuitive Web UI, so it is easy to use. Executing tasks through a command-line interface is, in fact, very useful if you need to deal with some of them outside of already set workflows. So, the question is - aside from everything we've already mentioned - why should you use Apache Airflow for managing workflows in your company?

The most important Airflow elements 

As with all frameworks, Airflow has some core elements which allow users to manage data pipelines efficiently. 

Resourceful User Interface 

A good user interface should make a difference even for the most experienced specialists, and Airflow UI does that. It is well-equipped, and it can be extended with extra menu items.  With Airflow, configuring the platform and setting workflows become very easy.

Direct Acyclic Graphs 

DAGs are collections of all the tasks you want to run, written in Python so as to define the relationships and dependencies of all tasks. With this structure you can schedule every task to be performed whenever you want - exactly when you want. You can make as many DAGs as you need to. Let's imagine that a given DAG consists of three tasks, like: 

• T1 - preparing data to make a report 

• T2 - making the report 

• T3 - sending an email notification that the report is ready 

You can organize the whole process by defining the rule that T1 runs first and T2 cannot start before the T1 is done. Now, you can also decide that T2 will be restarted 3 times (or more if you wish) if it fails. In case everything goes according to plan, and a report is created, you can schedule an email notification (T3) just after T2 is finished. There are many ways to benefit from Airflow's custom email alerts.

Tasks 

All tasks in a DAG are somehow related.  They are units of work which are parts of some DAGs and are represented in Python as nodes. Tasks can go through various stages from start to completion. The User can observe status changes in the User Interface. Tasks can have the following statuses: 

• running 

• failed 

• skipped 

• rescheduled

• retry 

• queued 

• no status 

• succeed 

A task has "no status" before it is processed in the Scheduler. After being scheduled, it is queued in the Executor and then performed by the Worker (those are three components of Airflow).

Scheduler

As we just mentioned scheduling tasks, having its own scheduler is certainly one of the biggest advantages of Apache Airflow - many workflow management tools go without it. Using a scheduler, you can monitor all tasks and DAGs in your framework.

X-COM

What makes working with complex pipelines even simpler is X-COM. This feature allows Airflow users to pass information through various tasks using its own database. Thanks to it, you don't have to use any additional tool for that purpose.

Advantages of using Apache Airflow - why should you use it in your company? 

There are many advantages of Apache Airflow. The tool is extendable and has a large community, so it can be easily customized to meet your company's individual needs.  It is used widely by many companies. It is a great tool for managing various dependencies between tasks. After learning Apache Airflow, your experts will surely appreciate your choice, as it provides an intuitive and simple monitoring and managing interface which makes work fast and easy. If you need an effective and easy to use tool for managing workflows, contact DS Stream consultants, to learn more about Apache Airflow advantages so you can decide if it is the proper tool for your company.