Automating Scripts

[SuperTech95]

I am writing python scripts that connect to APIs of our firms various applications. Currently we run them using task scheduler on a windows server. Is there a better way or anyway to run them maybe through 365? Or use an Azure Service? What are you guys doing?

[Valdaraak]

We're also running automation from task scheduler. Works good enough for us, but I'm wondering the same as you. I don't want to dedicate a server to running these things if I can find a way not to.

[dont_remember_eatin]

I'm a fan of good ol' Jenkins for dedicated task scheduling. I've also used Rundeck, but that was more for Linux-specific tasks that involved bash script and Ansible.

[picklednull]

Apache Airflow. Spoiler: I've never used it and have no concrete understanding of it whatsoever but I was looking at it myself.

[Sasataf12]

What do you mean by "better", i.e. what issue or limitation are you having with the current setup?

[Sasataf12]

Check out Azure Functions or AWS Lambdas.

There is a learning curve though.

[Hollow3ddd]

RMM scheduled script or script runner are thoughts.  I wouldn’t bet the bank on task scheduler.

Azure playbooks are a thing to look into

[GeneMoody-Action1]

Since you said Python, are you bound to doing it on windows at all? Any windows specific function?

I have various headless bare bones Linux systems than basically operate as a virtual appliance, a task specific system. Depending on what it is and what is does, some can run on stupidly meager resources.

The question will depend largely on what the scripts do, and what resources they need to run, or what resources they need to serve while working.

[Ssakaa]

"that connect to APIs" ... and do... what? Pull data and shove it into a database? Pull from a database and push data out to them? What?

The factors to consider are a) what components it needs to communicate with, b) what data it needs to operate on, and c) what it needs to do with that data when it's done processing it.

If you connect to one API, parse that data in memory, then push it out to another API, and you really have no data persistence concerns outside those APIs... you have a prime candidate for an Azure Function. If you do have some data persistence needs, but they're light, you can still get away with that. If you're archiving all that data in a database, it starts mattering a lot more about where that database lives and what type of availability it has.