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MLOps vs AIOps

We all can agree on one thing. Every business is becoming a digital business now. Mostly the current pandemic situation has made digital transformation faster for a lot of companies. Let us start by understanding MLOps, DataOps, AIOps.

In this tech-centric era, companies aim to extract maximum business value from their data in order to stay relevant and efficient via data-driven business decisions. In order to do so, they rely on AI and Machine Learning.

MLOps, DataOps, AIOps — there are so many “Ops” prefixed words, it is getting difficult to understand. As the name suggests, there are some connections to the concept of DevOps — a group of concepts that aim to automate processes in any business.


What Is MLOps?

Machine Learning Operations, or MLOps, helps simplify the management, logistics, and deployment of machine learning models between operations teams and machine learning researchers. It is basically DevOps applied to the field of machine learning.

What Is AIOps?

AIOps is a new field and a confusing one. Only in 2017 did Google begin receiving a significant volume of Google search requests for AIOps, and most vendors are still refining their solution set. For clarity, we at define AIOps as solutions that use big data, AI, and ML to enhance and automate IT operations and monitoring.