Artificial_Intelligence_for_IT_Operations
Artificial Intelligence for IT Operations
Machine learning term
Artificial Intelligence for IT Operations (AIOps) is a term coined by Gartner in 2016 as an industry category for machine learning analytics technology that enhances IT operations analytics.[1] AIOps[2][3] is the acronym of "Artificial Intelligence Operations".[4][5][6] Such operation tasks include automation, performance monitoring and event correlations among others.[7][8]
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There are two main aspects of an AIOps platform: machine learning and big data. In order to collect observational data and engagement data that can be found inside a big data platform and requires a shift away from sectionally segregated IT data, a holistic machine learning and analytics strategy is implemented against the combined IT data.[9]
The goal is to enable IT transformation,[10] receive continuous insights which provide continuous fixes and improvements via automation. This is why AIOps can be viewed as CI/CD for core IT functions.[11]
Given the inherent nature of IT operations, which is closely tied to cloud deployment and the management of distributed applications, AIOps has increasingly led to the coalescence of machine learning and cloud research.[12][13]