October 26, 2019 • Vijay Kurkal, Chief Operating Officer

As published in Digitalization World.

Today, most IT teams find themselves facing a number of challenges presented by the new and increasingly complex infrastructure that accompanies digitization, including an exponential increase in data volumes and types. In fact, Gartner estimates that the data volumes generated by IT infrastructure and applications are increasing two- to three-fold every year (and that’s compounding growth). There’s clearly too much data for the humans on the IT team to sort through on their own.

Expanding infrastructure also results in 1000s of events streaming in every day to overtasked admins on the front lines. Given the immense volumes and the high rate of false alarms, IT teams are forced to simply ignore many of these alerts. On top of that, teams are tasked with tracking a dynamic, ever-morphing infrastructure that is heavily virtualized and spread across hybrid environments in the cloud and multiple data centers. Despite these challenges, IT is still expected to resolve requests, incidents, and performance issues in seconds, not days – without introducing more people to their already overburdened teams.

AIOps, particularly when combined with automation, can help IT teams survive and thrive in this new era of increasing complexity. AIOps is a term coined to describe the use of artificial intelligence (AI) to aid in IT operations. AIOps technologies harness AI, machine learning, and advanced analytics to aggregate and analyze immense volumes of data collected from a wide variety of sources across the IT infrastructure. In doing so, AIOps quickly identifies existing or potential performance issues, spots anomalies, and pinpoints the root cause of problems. Through machine learning and advanced pattern matching, these solutions can even effectively predict future issues, enabling IT teams to automate proactive fixes before issues ever impact the business.

AIOps technologies also offer advanced correlation capabilities to determine how alarms relate to one another. This separates the signal from the noise and ensures IT teams focus their attention in the right place, streamlining operations. Additionally, many AIOps solutions can automatically map the dependencies between dynamic, changing infrastructure components to provide real-time visualization of the relationships between applications and underlying technology. This makes it much easier to see how things are connected when troubleshooting and significantly reduces the time to solve problems.

While AIOps on its own drives tremendous value, the magic really happens when it is combined with robust automation capabilities that can take immediate and automated actions on the insights powered by the AI. When these technologies come together, they deliver a closed-loop system of discovery, analysis, detection, prediction, and automation, bringing IT closer to achieving the long-awaited promise of truly “self-healing IT.”

We encourage you to learn more about how Resolve is helping companies leverage AIOps and automation to transform IT operations. Request a demo here ›

Vijay Kurkal

About the Author, Vijay Kurkal:

Vijay Kurkal serves as the Chief Operating Office for Resolve where he oversees the strategic growth of the company as it helps maximize the potential of IT automation in enterprises around the world. Vijay has a long history in the tech industry, having spent the last twenty years working with numerous software and hardware companies that have run the gamut from mainframe to bleeding-edge, emerging tech. Before joining Resolve, he held leadership positions at IBM, VMware, Bain & Company, and Insight Partners, playing a critical role in accelerating the growth of a wide array of technology companies and introducing state-of-the-art product lines. Vijay has a passion for helping IT organizations achieve digital transformation by embracing new technologies and for bringing innovative solutions to market. He frequently speaks and writes about topics related to the journey to automation in modern enterprises. Vijay’s own foray into technology began with a degree in electrical engineering, followed by an MBA from Columbia University.