Artificial Intelligence in IT operations (Aiops); How can organizations prepare? managed it service urolime

Artificial Intelligence in IT operations (AIOps); How can organizations prepare?

Advancement in the application of AIOps (originally called Algorithmic IT Operations, now Artificial Intelligence for IT Operations) in the IT has become the game changer for the industry. IT operations can use AI to monitor data and lessen outage times. It combines machine learning functionalities and Big Data for the enhancement of primary IT operations. Industry experts such as Gartner are predicting a transformative long-term impact of AIOps in the industry within a very few years because of its astounding capability to partially or completely replace the fundamental IT operational functions such as availability and execution monitoring, event correlation and analysis, and IT service management and automation. Although the use of AIOps is still sparse, analysts say its prevalence will continue to grow rapidly in the near future.

The term itself was coined by Gartner in 2017, and this definition provided by Andrew Lerner provides a much sharper image.

“AIOps platforms utilize big data, modern machine learning and other advanced analytics technologies to, directly and indirectly, enhance IT operations (monitoring, automation and service desk) functions with proactive, personal and dynamic insight. AIOps platforms enable the concurrent use of multiple data sources, data collection methods, analytical (real-time and deep) technologies, and presentation technologies.”

Industry big shots are pretty much enthusiastic about the promise of applying AI on IT operations but as DevOps teams lean on AIops, administrators will need to tackle a new set of skills to get the most out of the types of operational automation AIOps provides. From the current state of research and experimentations, it is proven that AIOps will reduce the complexity of the workforce.

“They need to retool themselves from admin-oriented activities to scripting/reporting-oriented tasks, and they need to be more application aware than ever before as infrastructure becomes a commodity,”

– Ravi Raghavenderrao, vice president of service delivery at NetEnrich

Future proofing your career with AIops can be a perplexing task since the management is altering their AIops career requirements in such a way to ascertain the root cause of the problems and solving them by designing solutions creatively. Rise of AIops won’t diminish the need of IT professional but will intensify the demand for domain expertise.

According to Devops experts and industry magnets, the most coveted professionals would be AIOps Architects, ITOps Data Scientists, and Augmented Intelligence Analysts. All this might be pretty much familiar for the ones who are adapted to DevOps transformations while the others should consider propping themselves with additional knowledge of data science, AI and system architecture.


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