Airlfow Dag Datadog Agent Check

The purpose of this check is to use the Airlfow CLI to check and then report on the statuses of Dag Jobs.

Installation

checks.d/airflow_dag.py must be copied to the agent's checks.d directory. On a linux system that is /etc/dd-agent/checks.d.

Configuration

All Environments

• A config file needs to be defined for the Agent
  • An example config file for the Agent can be found in conf.d/airflow_dag.yaml.example

Development Envrionment Only

• The Datadog API key needs to be defined in playbooks/roles/datadog/vars/main.yml
  • An example of the variable file can be found in playbooks/roles/datadog/vars/main.yml.example

Development

Requirements

• Vagrant
• Ansible
  • This was built and tested using Ansible 2.2.0.0.
• A Datadog account and API Key
  • To keep namespaces for the checks as clean as possible, setting up a free trial is advised

Testing

Generating Airflow Data to be Detected

The Airflow Dag has been set up to be able to run via the Scheduler. To use it, run airflow scheduler from within the Vagrant environment. This script expects to be run in a daemon-like setup, so you may wish to create another SSH session to your Vagrantenvironment to run it.