This repo contains implementations of Airflow workflows and tasks called respectively DAGs and Operators.
- DAGs - Direct Acyclic Graphs - Python scripts defining workflows in a way that reflects their relationships.
- Operators - Python functions which define the individual tasks that are executed as part of a DAG run.
To learn how to write DAGs and Operators read about core concepts and follow the official tutorial.
This repository contains:
website_sync
: DAG to launch the Airbyte jobs for the status-website charts.spiff_sync
: DAG to synchronize Spiff workflows datadbt
: DAG to run all the dbt models,gh_sync
: DAG to synchronize data from repository (logos, waku, codex)
The DBT models run in some DAG are stored in
dbt-models
.
Changes pushed to master
are automatically fetched to our Airflow instance by the airflow-webhook
service.
This repos has 3 working branches:
prod
: used by https://airflow.bi.status.im.test
: used by https://airflow.test.bi.status.im to test DAGs modification.example
: contains examples of DAGs
All Airflow infrastructure is managed in the infra-bi repository.