What is the AI in AIops?

You don’t have to look very hard to find technology platforms that advertise ML (machine learning), automation, and AI (artificial intelligence) capabilities. Once devops became mainstream, it bred process, technology, and IT culture movements with similar names, including cloudops, dataops, sysops, and AIops.

This may leave some of you skeptical about whether applying machine learning in IT operations can deliver business and IT value. Being skeptical is healthy, but you shouldn’t be surprised. I assure you that there are significant opportunities, and AIops is one of my devops capabilities to boost in 2021.

IT environments have become more complex during the past decade, with autoscaling public and private clouds, edge computing infrastructure supporting IoT (Internet of Things), machine learning experiments on massive-scale databases, new integrations, frequent application deployments, mission-critical legacy systems, and highly leveraged microservices. There are also plenty of variables outside of IT control, such as security incidents, disparate end-user computing configurations, and volatile application usage patterns.

It’s a challenging environment if your job is to respond to incidents, resolve application problems, perform root cause analysis, diagnose complex user issues, validate operational risks, identify security weaknesses, or forecast computing costs.

This is where AIops solutions aim to help. In a previous article, I wrote about how AIops helps IT and SREs improve application monitoring and resolve incidents. But I still wanted to know more about how different solutions implement data cleansing, analytics, machine learning, and automation to simplify IT and deliver business impact.

Six AIops solution providers shared some answers that paint a broad picture of what problems AIops solves for the business and IT, what types of machine learning algorithms are used in their solutions, and how their products support automation.   

Copyright © 2021 IDG Communications, Inc.

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