In the past, many organizations grew and managed their own data centers. Some still do. And many are still developing their own automated incident management (aka Autonomous Operations) tools. But as IT grows and becomes evermore complex and fast-moving, the reality of what it means to do so kicks in, and organizations are re-evaluating their strategies.

Since the term ‘AIOps’ came into use in the monitoring sector a couple of years ago, there has been much confusion about what it means. We hear from users asking if they need it – a difficult question given that the answer depends on how you define it. Since there isn’t a broadly accepted definition, a range of vendors now market their products as AIOps offerings, even though these products cross subsectors and may not be directly competitive.

DevOps is fast, glamorous and agile. It is key to keeping modern, fast-moving IT environments up and running. And it is no stranger to automation: DevOps has been relying on automation for many years now to ensure the rapid delivery of applications in this ever-changing landscape. Yet even the most agile and advanced DevOps teams cannot escape the growing complexity, scale and pace of the modern IT stack.

The ever-growing complexity, scale and pace of IT environments puts a huge burden on IT Ops, NOC, and DevOps teams, who are tasked with keeping these environments up and running. One of the biggest challenges is Root Cause Analysis (RCA). When something breaks, they need to determine what broke it, and they need to do it fast.

My 2nd Gartner IOCS experience ended with a bang, just like my first one, with an amazing presentation by Jason Walker at Blizzard Entertainment (part of the $42B Activision-Blizzard gaming powerhouse) on how they use AIOps to deliver an amazing gaming experience for hundreds of millions of gamers around the world, 24×7. But before I get to that, let me share some more key takeaways from the conference.

Critical and sev1 incidents are always a priority, but what about those dozens and often hundreds of lower priority ones that often sit in a queue waiting for a first response engineer to get to them? Do you find that no matter how much effort your team puts into minimizing the number of queued incidents, their number always seems to grow? If this sounds familiar – this blog is for you.

Root Cause Analysis (RCA) is an all-encompassing process. It is usually very complicated and often requires many people with many different skills – all trying to tackle an incident to determine what happened, when, why, how and ultimately who (to blame). There is, however, secret sauce today that can help solve many issues before a “full-scale” RCA process is initiated – and that is Root Cause Changes (RCC).

TL;DR: Fast-moving IT stacks see frequent, long and painful outages. Thousands of changes – planned, unplanned and shadow changes – are one of the main reasons behind this. Until now, IT Ops, NOC & DevOps teams didn’t have an easy way to get a real-time answer to the “What Changed?” question – the answer that can help reduce the duration of outages and incidents in these fast-moving IT stacks. Now, with BigPanda Root Cause Changes, they do.