Fri, 01 Feb 2019 16:51:11 GMT
Hi, i'm new in DevOps world, I have been assigned a thesis in which I have to create a small pipeline DevOps in which I pretend to develop and release a software, and to this pipeline I have to apply some machine learning algorithm to improve the work.
First I started studying machine learning and how DevOps works, later I looked for information on how to integrate the two things, but I found only some advice, nothing concrete. So I'll have to invent something myself.
I wanted to ask, which DevOps tools do you recommend to use for my purpose? I started using Jenkins and Docker, but I wanted to know if there is anything more suitable for my purpose.
Do you have any advice on how to apply machine learning in DevOps?
Tue, 19 Feb 2019 09:07:12 GMT
In practice, some key examples of applying ML to DevOps include:
Tracking application delivery.
Ensuring application quality.
Securing application delivery.
Managing alert storms.
Troubleshooting and triage analytics.
Preventing production failures.
Thu, 25 Apr 2019 07:01:34 GMT
Look beyond the threshold
Learn from the history of data
Looking for faults
Drilling down to the root cause