MIT Review: Global Business Leaders Turning to AIOps to Drive IT Performance

August 15 2019

A new MIT Technology Review report reveals how AIOps helps global leaders like FedEx drive innovation, reduce MTTR, and optimize business outcomes.

When a U.S. company experiences an application outage, the average cost to the business is well over $400,000.

So it makes sense that both IT and business leaders would do everything in their power to avoid such costly outages. Yet, in a recent global survey of more than 6,000 IT leaders, 97% of respondents reported that their organization has had at least one outage in the last six months alone. For IT and business leaders alike, this is a troubling data point. But when considered in the context of increasingly complex application environments, the situation takes on a new level of urgency. The takeaway then becomes clear: Businesses can’t afford to react to performance problems, they have to proactively solve for them.

But how?

The new frontier for IT operations

Today’s IT landscape is different than it was even just a few years ago. Increasingly complex application environments and distributed IT systems have made it more challenging to ensure reliability, as well as effectively monitor and manage the performance of applications and systems. Sticking with the same approach to application performance monitoring (APM) just doesn’t cut it anymore.

To stay competitive, a new report from MIT Technology Review reveals that global leaders like FedEx are increasingly turning to AIOps to drive IT and business performance. And they’re not alone: According to Gartner, 30% of large corporations are projected to exclusively use AIOps tools to monitor applications and infrastructure by 2023, up from just 5% in 2018. But before we can understand the true value of this emerging trend and why you might need it, we’ve got to define what it is.

What is AIOps?

AIOps — a term coined by Gartner and short for “artificial intelligence for IT operations” —refers to the use of artificial intelligence (AI) and machine learning (ML) to automate data correlation, enable root cause analysis, and deliver predictive insights for both IT teams and businesses. AIOps solutions leverage ML to not only automate routine tasks, but also gather and interpret large volumes of historical data to identify potential problems before they manifest themselves in IT environments.

If a server is reaching capacity, for example, AIOps technology can alert the IT team, giving them the opportunity to take action before it even impacts the end user. AIOps can also help IT departments predict capacity for data centers, measure the effectiveness of an organization’s main business applications, and perform cause-and-effect analysis of peak usage traffic patterns.

Why IT teams need an AIOps solution

There’s no arguing that traditional monitoring tools still play a vital role in any APM strategy. But today, IT leaders should also be thinking about building a more proactive approach to performance via AIOps technology.

With its AI and machine learning capabilities, AIOps empowers IT teams to drive innovation, reduce MTTR, and optimize business outcomes. By leveraging company-wide data, monitoring operational and usage statistics, and proactively solving performance problems, AIOps streamlines IT operations and has the potential to prevent outages that could damage a company’s reputation and bottom line.

AIOps in the real world

Given the capabilities of AIOps solutions, the MIT report points out that, “IT executives are increasingly seeking them out as a means to help organizations retrieve, analyze, and extract value from IT operations data.”

“IT executives are increasingly seeking [AIOps solutions] as a means to help organizations retrieve, analyze, and extract value from IT operations data.”

MIT Technology Review

FedEx and Stromberg & Forbes are two organizations that are using AIOps to build a more proactive approach to performance monitoring. While still in the early stages of their AIOps journeys, the technology has already delivered clear wins for both organizations.

At Stromberg & Forbes, CIO Steve Sommer estimates that AIOps shaves off “one-third to one-half” of the hours the company spends on routine maintenance and troubleshooting.

“AIOps is mission control and command central. [Without the technology] I as a human could spend days and weeks trying to navigate through large, complex data sets trying to find solutions to issues,” Sommer points out.

Similarly, AIOps has allowed FedEx to accelerate issue resolution and significantly reduce the manual intervention required to troubleshoot and solve performance problems. Sergio Puga, Senior Technical Program Manager at FedEx Services, says it best: “If our team investigated the same CPU utilization problem using current monitoring tools, it would take six-to-10 full-time employees two-to-five hours to find the source and perform remediation.”

Puga sums up the benefits of AIOps technology this way: “It’s going to drive innovation, streamline FedEx’s operations and make us more reliable, efficient, and competitive—and make my job a lot easier.”

The future of APM

The use of AIOps solutions is poised for exponential growth over the next five years.  And it’s easy to see why: AIOps has the power to deliver transformative benefits for both IT and the business.

Using artificial intelligence and analytics, AIOps can help IT teams avoid expensive outages and reduce MTTR. And, because AIOps is designed to uncover insights more efficiently, it can help the business improve the bottom-line and preserve the end user experience.

So, are you ready to usher in this new era of AIOps?

Get the free report from MIT Technology Review for deeper insights into why AIOps is the key to managing increasingly complex application environments.

AppDynamics Team

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