Apache Airflow vs. Azure Automation

For a quick job scanning of status and deep-diving into job issues, details, and flows, AirFlow does a good job. No fuss, no muss. The low learning curve as the UI is very straightforward, and navigating it will be familiar after spending some time using it. Our requirements are pretty simple. Job scheduler, workflows, and monitoring. The jobs we run are >100, but still is a lot to review and troubleshoot when jobs don't run. So when managing large jobs, AirFlow dated UI can be a bit of a drawback.

Incentivized

We have found Azure Automation to be well-suited for tasks that must be performed on a scheduled basis. No matter how simple or tedious tasks are to perform manually, if they run on a scheduled basis, it makes sense to have them automated. If the tasks at hand are only performed once or infrequently, then it may be best to continue performing them manually.

Incentivized

• In charge of the ETL processes.
• As there is no incoming or outgoing data, we may handle the scheduling of tasks as code and avoid the requirement for monitoring.

Incentivized

• Scheduled automation of Microsoft 365 and Azure tasks
• Scheduled automation of scripting (e.g. Powershell)
• Perform periodic maintenance

Incentivized

• they should bring in some time based scheduling too not only event based
• they do not store the metadata due to which we are not able to analyze the workflows
• they only support python as of now for scripted pipeline writing

Incentivized

• An automation template library would be nice
• Clear estimation of costs - this goes for the entire Azure Automation platform
• It can be daunting at first due to all the settings and menu levels, but it is not difficult once you get started.

Incentivized

Easy to learn Easy to use Robust workflow orchestration framework Good in dependent job management

Incentivized

There are a number of reasons to choose Apache Airflow over other similar platforms- Integrations—ready-to-use operators allow you to integrate Airflow with cloud platforms (Google, AWS, Azure, etc) Apache Airflow helps with backups and other DevOps tasks, such as submitting a Spark job and storing the resulting data on a Hadoop cluster It has machine learning model training, such as triggering a Sage maker job.

Incentivized

We did not evaluate any other automation products since we are already using Microsoft 365 and the Azure platform. Additionally, Azure Automation allows for a reasonable number of tasks to be performed each month at no cost, which is especially nice when testing the platform. We found Azure Automate's integration of Powershell invaluable when working directly with Microsoft 365, Sharepoint, Azure AD, and other systems via API.

Incentivized

• A lot of helpful features out-of-the-box, such as the DAG visualizations and task trees
• Allowed us to implement complex data pipelines easily and at a relatively low cost

Incentivized

• Ensures tasks are not forgotten
• Saves times - routine tasks no longer have to be performed manually
• Complicated tasks are no longer an issue

Incentivized