IBM’s new OEM Application Resource Management offers a tool to improve applications by using automation.
AI for IT Operations (or AIOps, for short) is quickly becoming seen as a critical tool for businesses. By harnessing the power of AI and applying it to large data sets, the tool offers a simple solution for scaling IT operations and by 2023, Gartner predicts that the use of AIOps for large enterprise use will jump to 30%, from merely 5% in 2018.
The enterprise is still adopting this new technology for IT departments—and IBM is offering a way for developers to discover new ways to invest in AI-powered automation to help solve decentralized, microservices-based applications, Eric Wright, technology evangelist at Turbonomic, explains.
Turbonomic powers IBM’s OEM (short for Original Equipment Manufacturer) Application Resource Management (ARM), which Wright described recently at the AIOps & Integration Digital Developer Conference. The ARM, Wright says, can offer higher levels of automation to APM solutions through AIOps. And developers can use this tech to manage whole sets of resources across the hybrid cloud.
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IBM and Turbonomic’s partnership aims to support “mission-critical cloud native applications,” according to the company. This tech can help a range of industries, from big financial to small credit unions to education to health services. Nearly every vaccine provider, for instance, is powered by IBM and Turbonomic, Wright said.
“We’ve had AI ‘washing’ for a long time,” says Wright, referring to the marketing effort that claims AI is involved in a company’s products, even if it’s a loose connection. But now, he says, “Our focus is using the power of AI to make sure applications get the resources they need, when they need them, continuously and automatically. It sounded bold 11 years ago, when we founded the company, but we’ve proven it out.”
Wright calls it “sentiment analysis for your IT environment,” essentially, a way to better understand IT operations, which includes more than real-time diagnostics but can give insight into long-term analysis. According to Wright, it’s no longer just a marketing phrase.
“We have these huge environments that are growing,” he explained. “We’ve got cloud adoption, we’ve got Kubernetes,” he says, referring to the open source container system for the automation of app deployment and scaling first designed by Google.
“It’s no longer just in the science-project phase,” he says.
These new systems require automation, he argues. “If you’ve got a large open-shift environment, you certainly can’t throw people at it to manage it the way that we used to, with physical and virtual servers.”
SEE: The Essential Guide to AIOps (TechRepublic)
Using automation, Wright contends, can help CIOs who need applications to respond. They need “healthy apps,” he said. For instance, a major bank in New York that sees performance issues, or code flow problems, can check if they are meeting requirements to hit the service level objective. “And so this is the move from just waiting until it goes wrong and then trying to investigate to really preventatively moving towards, How can I automate and operate my environment so that developers just deploy the app?'” Wright said. “The app literally is fully automated in what it chooses.”
The goal of automation, Wright said, is to save time for employees: To help them do something new, instead of reviewing processes. So there’s been a shift toward building code. “They couldn’t do that before because they were literally just trying to keep the lights on,” he said.
“This is a new standard I think for CIO—that they just won’t accept that we’re just going to toss engineers at it to try and solve the problem. So automation is now sort of the standard-bearer in every layer of the stack,” Wright added, “which is pretty fantastic.”