AIOps is artificial intelligence for IT operations and is gaining interest from Information Technology managers due to the potential for simplifying operational aspects. Artificial intelligence for IT operations has become the umbrella term for the application of big data analytics, machine learning plus other artificial intelligence technologies which can automate the identification and resolution of common information technology issues.
Gartner’s analysis of AIOps discusses how the implementation of such systems can help pave the move away from siloed IT data, and instead lead to the aggregation of observational data and engagement data (like event recording). This can help herald in a new Information Technology culture.
New platforms designed to achieve AIOps can use collected data to monitor assets and gain visibility into dependencies relating to IT. According to Forbes, examples of AIOps include capacity planning, where workloads can be mapped to the right configuration of servers and virtual machines through the use of artificial intelligence. A second area is with predictive scaling, where artificial intelligence uses infrastructure to intelligently adjust itself based on historical data trends.
For these reasons AIOps is growing in popularity. A new survey from OpsRamp has found that a majority of IT managers (68 percent of those surveyed) are wconsidering AIOps for IT operations. The main reason cited is through the potential of AIOps to differentiate between legitimate signals and inconsequential noise, thus allowing meaningful insights related to system alerts. The survey also found that 74 percent of those keen to use AIOps wish to automate tedious tasks; and 66 percent said they think AIOps can help to improve root-cause analysis
AIOps also has the ability to accurately highlight data outliers by pinpointing the actual source. This approach, ZDNet notes, which can help IT teams in performing efficient root cause analysis in real-time.
