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Applying machine learning to DevOps

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? Thanks.

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 production. 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 Monitoring tools Measuring orchestration Looking for faults Drilling down to the root cause