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Azure Environment

How to configure an environment for Azure.

Before You Begin

You must have dbnd-azure plugin installed.

To Set up an Environment for Microsoft Azure

  1. Open the project.cfg file and add Azure to the list of environments.
  2. Review the [azure] section and configure it in accordance with your login settings.
  3. Optionally, provide a root bucket/folder for your data:
root = https://<your_account>
spark_engine = databricks
  1. Configure access to your Blob storage:
dbnd airflow connections --delete --conn_id=azure_blob_storage_default
dbnd airflow connections --add --conn_id=azure_blob_storage_default --conn_login=<acount name> --conn_type=wasb --conn_password=<acount key>

[azure] Configuration Section Parameter Reference

  • env_label - Set the environment type to be used. E.g. dev, int, prod.
  • production - This indicates that the environment is production.
  • conn_id - Set the cloud connection settings.
  • root - Determine the main data output location.
  • local_engine - Set which engine will be used for local execution
  • remote_engine - Set the remote engine for the execution of driver/tasks
  • submit_driver - Enable submitting driver to remote_engine.
  • submit_tasks - Enable submitting tasks to remote engine one by one.
  • spark_config - Determine the Spark Configuration settings
  • spark_engine - Set the cluster engine to be used. E.g. local, emr (aws), dataproc (gcp), etc.
  • hdfs - Set the Hdfs cluster configuration settings
  • beam_config - Set the Apache Beam configuration settings
  • beam_engine - Set the Apache Beam cluster engine. E.g. local or dataflow.
  • docker_engine - Set the Docker job engine, e.g. docker or aws_batch

What’s Next