Operations | Monitoring | ITSM | DevOps | Cloud

January 2022

The State of AIOps SaaS and the Vacuum Left by Traditional Solutions

Modern workflows are primarily aimed at one thing—reducing operational complexities so that stakeholders can focus on initiatives that boost business and innovation. For IT teams, Artificial Intelligence and Machine Learning play key roles in bringing this goal to life. And even though AIOps is considered to be not yet in mature stages, there is no denying that IT teams that do not adopt AI processes will be left behind. By 2023, the market for AIOps tools is predicted to reach $11.02 B.

6 AIOps Myths You Should Be Wary Of

AIOps myths and how to avoid them Gartner coined the term AIOps in 2016 to refer to the combining of “big data and machine learning to automate IT operations processes, including event correlation, anomaly detection and causality determination.” In the five years since, AIOps has grown leaps and bounds — last year, AIOps was at the peak of the Gartner hype cycle.