Apache Airflow vs. Red Hat Ansible Automation Platform

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

I'm going to say it is best suited for configuration management. Like I said, patching even with security, things of that nature. Probably less suited is hardware management, but Red Hat IBM/IBM has Terraform for that. So it's a trade off.

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

• Debugging is easy, as it tells you exactly within your job where the job failed, even when jumping around several playbooks.
• Ansible seems to integrate with everything, and the community is big enough that if you are unsure how to approach converting a process into a playbook, you can usually find something similar to what you are trying to do.
• Security in AAP seems to be pretty straightforward. Easy to organize and identify who has what permissions or can only see the content based on the organization they belong to.

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

• Better documentation of how all the options/parameters are meant to be used (when creating things like jobs, templates, inventories, etc)
• More recommendations of best practices as far as the best way to organize job templates, workflows, roles. Much can be found on how to organize pure Ansible, but not so much for AAP specifically.
• I have found some things that seem like they should be easy but are not possible. Things like moving a host from one inventory to a different inventory. As far as I know this is not possible and requires deletion and recreation. Maybe I just don't know how this could be done or don't understand the design decisions behind this?

Incentivized

Even is if it's a great tool, we are looking to renew our licence for our production servers only. The product is very expensive to use, so we might look for a cheaper solution for our non-production servers. One of the solution we are looking, is AWX, free, and similar to AAP. This is be perfect for our non-production servers.

Incentivized

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

Incentivized

It's overall pretty easy to use foe all the applications I've mentioned before: configuring hosts, installing packages through tools like apt, applying yaml, making changes across wide groups of hosts, etc. Its not a 10 because of the inconveinience of the yaml setup, and the time to write is not worth it for something applied one time to only a few hosts

Incentivized

Great in almost every way compared to any other configuration management software. The only thing I wish for is python3 support. Other than that, YAML is much improved compared to the Ruby of Chef. The agentless nature is incredibly convenient for managing systems quickly, and if a member of your term has no terminal experience whatsoever they can still use the UI.

Incentivized

There is a lot of good documentation that Ansible and Red Hat provide which should help get someone started with making Ansible useful. But once you get to more complicated scenarios, you will benefit from learning from others. I have not used Red Hat support for work with Ansible, but many of the online resources are helpful.

Incentivized

I spoke on this topic today!

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

I used puppet prior to moving to open source Ansible and eventually to Red Hat Ansible Automation Platform. I appreciate the agentless approach of Red Hat Ansible Automation Platform and feel that its deterministic approach to applying code is superior to puppet

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

• POSITIVE: currently used by the IT department and some others, but we want others to use it.
• NEGATIVE: We need less technical output for the non-technical. It should be controllable or a setting within playbooks. We also need more graphical responses (non-technical).
• POSITIVE: Always being updated and expanded (CaC, EDA, Policy as Code, execution environments, AI, etc..)

Incentivized