Steps to Create & Configure Apache Airflow DAGs on Ubuntu 20.04 LTS

Apache-Airflow is an open source workflow management tool, written in Python. It is a workflow management solutions tool &used for monitoring the workflow. Using Airflow, we can easily create own Directed Acyclic Graph (DAGS ). DAGS is used for designing a workflow.

There are some steps to create Apache Airflow DAGS in Ubuntu:

Step 1: Update the System.

apt-get update

Step 2: Install Apache Airflow on system so click on link

Step 3: Create a DAGs in Apache Airflow.

  • Go to airflow home directory.

cd ~/airflow

  • List the files.


  • Here is the command output.

root@ip-172-31-36-75:/home/ubuntu# cd ~/airflow
root@ip-172-31-36-75:~/airflow# ll
total 688
drwxr-xr-x 3 root root 4096 Feb 5 14:39 ./
drwx------ 8 root root 4096 Feb 5 14:33 ../
-rw-r--r-- 1 root root 43937 Feb 5 13:46 airflow.cfg
-rw-r--r-- 1 root root 634880 Feb 5 14:35 airflow.db
drwxr-xr-x 4 root root 4096 Feb 5 14:08 logs/
-rw-r--r-- 1 root root 4695 Feb 5 13:46

  • Here,create a folder.

mkdir dags

  • Change the directory.

cd dags

  • Create a .py file.


  • Add the following lines:

from datetime import datetime
from airflow import DAG
from airflow.operators.dummy_operator import DummyOperator
from airflow.operators.python_operator import PythonOperator
def print_hello():
return 'Hello world from first Airflow DAG!'
dag = DAG('hello_world', description='Hello World DAG',
schedule_interval='0 12 * * *',
start_date=datetime(2017, 3, 20), catchup=False)
hello_operator = PythonOperator(task_id='hello_task', python_callable=print_hello, dag=dag)

Step 4: Now Go to the python-virtual Environment.

cd /home/ubuntu/airflow_example/bin

  • Run the following commands:

source activate
export AIRFLOW_HOME=~/airflow

  • Here is the command output.

root@ip-172-31-31-134:~/airflow/dags# cd /home/ubuntu/airflow_example/bin/
root@ip-172-31-31-134:/home/ubuntu/airflow_example/bin# source activate
(airflow_example) root@ip-172-31-31-134:/home/ubuntu/airflow_example/bin# export AIRFLOW_HOME=~/airflow

Step 5: Run the DAG.

  • we need to run the Airflow scheduler command.

airflow scheduler

  • Here is the command output.

  • Type ctrl+c to stop the command.

Step 6: Open the Apache Airflow web interface.

airflow webserver -p 8080

  • Without stopping the command,Open the Apache-Airflow web interface using URL.


  • Here is the command output.
  • Provide the login credentials like username & password.

  • Now Search the created DAG.

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