How We Got to AIOps

The trajectory of the application performance monitoring (APM) industry was a short, fast-moving, ever-changing journey — from a simple app-only monitoring tool in the mid-2000s to a complex, five-stage artificial intelligence-driven process today. The relatively short development history of APM-to-AIOps dovetails with the equally rapid development the cloud, IT digitization and AI commercialization.

This historical background of the APM industry is the focus of conversation between Rackspace Technology CTO Jeff DeVerter, and guest, Will Cappelli, Field CTO at Moogsoft, an AIOps and observability platform. Their discussion ran the gambit from the business disruption of APM to the overnight demand for digital solutions triggered by the advent of COVID-19.

Cappelli understands the evolution of this critical technology better than most people. While working as a Research VP at Gartner for 15 years he discovered the advent of APM industry in the mid-2000s. Cappelli then mapped its growth from its simple beginnings to its complex development today as a sophisticated and dominant IT solution that impacts nearly every aspect of an IT enterprise.

“After a simplistic beginning around 2005, some vendors began to see the value of merging APM with AI about 2015,” said Cappelli. “At that time, I predicted that the merger of AI and ITOps was going to become a significant event, because it was only through the development of cognitive enhancements in APM that we were going to be able to understand the behaviors of the emerging complexity of our systems and predict instances that might emerge in the future.”

Understanding how we got to this point and what it means to the present and future of IT can help enterprises take the next step into AIOps. You can gain this vital insight by listening to the latest Cloud Talk episode. In just under 45 minutes, Cappelli and host DeVerter cover this wide range of topics:

• The 15-year path of AIOps from simplistic to complex capabilities
• Mapping the intertwined trajectory of APM, AI and digital technology
• Five critical stages of an advanced AIOps algorithm chain
• The rise of the adoption of cloud-based IT
• A solution to the advent of big data challenges
• The history of the commercialization of AI technology
• The overnight digitization of IT organizations during COVID-19

DeVerter shared insight on the impact of AIOps in Rackspace Technology. “We have 40 data centers around the world managing 100s of 1,000s of virtual machines for our customers. Thanks to the advancement of AIOps, we’re able to automate the resolution of over 60% of all initiated tickets. This allows these systems to do what they do best, and frees up our Rackers to help our clients, such as solving problems or designing complex solutions.”

AIOps gained an unintentional proof-of-concept during COVID-19. “Overnight, organizations had to digitize their IT operations to keep their businesses running,” explains Cappelli. “The companies that had already began planning for their digital modernization transition were ahead of the pack and better prepared to make the critical switch.”