AIOps is an umbrella term used to describe the use of machine learning and artificial intelligence in IT operations. It is about tapping into the data across the IT operations to use machine learning and analytics to help enterprise IT do operations more efficiently. Gartner has predicted that the use of AIOps will increase from 5% in 2018 to 30% in 2023. There are a few trends that are reshaping IT operations with AIOps:
When you think of AIOps, don’t imagine a scenario where autonomic computing takes over where machine intelligence handles all the IT operations. AIOps is about augmenting existing IT teams to be more efficient and proactive in their tasks.
IT is challenged by the large volumes of monitoring data and logs. Analysing such data with the traditional rules based approach is time-consuming. It doesn’t help IT to quickly stop outages from happening. Also, with multi-cloud and use of more distributed computing like containers, the amount of data IT has to handle has increased multifold. AIOps is about using compute power to help IT make sense of all the data and take proactive actions to stop any problems before they occur. AIOps platforms consume all the monitoring and performance data along with logging to detect events and apply machine learning (and deep learning in some cases) to inform IT operations about any issue or outages. AIOps goes beyond preventing outages to stopping runaway costs, security, and policy violations.
Some of the advantages of AIOps are:
AIOps makes IT operations more efficient by helping them take actions to prevent outages, security, and policy violations. By proactively managing resources and costs, organizations can even realize dramatic cost savings. In short, AIOps helps the IT Operations team to be part of the innovation center rather than a cost center.