AIOps Emerges as ‘Air Traffic Control’ for IT

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Along with reducing IT administrators’ work load by automating manual tasks, so-called AI operations, or AIOps, platforms are also being touted as helping to resolve IT performance issues as well as “anomaly detection.”

In a vendor survey released on Monday (Aug. 20), hybrid IT management specialist OpsRamp said more than two-thirds of administrators it polled are experimenting with the automation approach. Of those trials, most early adopters are testing AIOps as a way of reducing tedious and time-consuming tasks.

However, a growing number are looking to the capability as a way to distinguish operational alerts from false alarms that are beginning to overwhelm IT administrators. “We know from the survey data that even a relatively small reduction—up to 25 percent—in the number of alerts received by IT operations teams would be considered a success in terms of a company’s AIOps strategy,” said Mahesh Ramachandran, vice president of product management at OpsRamp.

Survey partner Gartner Inc. (NYSE: IT) defines AIOps as platforms that “combine big data, AI/machine learning and other technologies to support all primary IT operations functions with proactive, personal and dynamic insight.”

Two-thirds of survey respondents reported that AIOps technology speeded resolution of operational alerts by improving root-cause analysis used to pinpoint, understand and eliminate faults. Overall, respondents said they are looking to AI and machine learning for “scalable improvements in [IT] efficiency,” the survey found.

While AIOps are gaining the most traction within hybrid IT operations, the use of AI technology also is extending to areas such as semiconductor design. As chip makers shift operations to the cloud, they are using AIOps for datacenter migration tasks aimed at mapping out and identifying IT network issues.

In one example, AIOps provider FixStream helped mixed signal-semiconductor manufacturer Maxim Integrated (NASDAQ: MXI) migrate its operations to the cloud, reducing the expected transition from two years to about six months, the company claimed. The approach used AI algorithms to pinpoint IT network problems and quickly get to the root cause. The FixStream algorithms are used to automate analysis of IT operations data.

Meanwhile, San Diego-based OpsRamp offers an AIOps inference engine it positions as a cloud-based “air-traffic control” system for IT operations. The vendor survey found that experimenters are using the hybrid management platform to sort through and prioritize operational alerts that about half of respondents said are “too noisy, too high, or both.”

Early users placed the most value on ease of AIOps deployment and orchestration along with “knowledge capture” and the ability to use the tools in a hybrid cloud or on-premises setting.

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