There has been a gigantic growth of AIOps in the last two years. It has successfully transitioned from an emergent category to an inevitability. Companies adopted AIOps to automate and improve IT operations by applying big data and machine learning (ML).

AIOps is applying cognitive computing like AI and Machine learning techniques to improve IT operations. AIOps refers to the spectrum of AI capabilities used to address IT operations challenges–for example, detecting outliers and anomalies in the operations data, identifying recurring issues, and applying self-identified solutions to proactively resolve the problem, such as by restarting the application pool, increasing storage or compute, or resetting the password for a locked-out user
IT teams have adopted microservices, cloud providers, NoSQL databases, and various other engineering and architectural approaches to help support the demands their businesses are putting on them. It can get extremely difficult to understand the interactions between various systems and the impact they are having on cost. So with AIOps, there is the potential for achieving scale and efficiencies.

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