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.
I love structured, step-by-step plans (blame my engineering training) and Charley Rich, a Research Director at Gartner, did not disappoint.
His 5-step plan to realizing value with AIOps was spot-on, and closely echoes how customers that adopt AIOps using BigPanda see value in just 8 – 12 weeks.
Stage 1 – Reduce the noise! (95%+ noise reduction)
Stage 2 – Detect patterns and glean insights (BigPanda’s take on explainable AI, our very own Open Box Machine Learning generates the patterns for you!)
Stage 3 – Stop P3s and P2s in their tracks and *prevent* horrible P1s and P0s from happening
Stage 4 – Identify the root cause (and with BigPanda only, the Root Cause Changes that cause 85%+ problems) and slash MTTR (50%+, with BigPanda) Stage 5 – Improve your services and make your customers and BUs happy 🙂
But of course, not all AIOps tools are created equal.
And as we heard at our action-packed booth over and over across three days, enterprises are hungry for pragmatic AIOps tools that
- can be adopted quickly,
- don’t require that enterprises rip and replace their tools or processes, and
- deliver compelling value (95% noise reduction, 85% ticket volume reduction and a 50% MTTR reduction) rapidly.
[PS: I have a recommendation if you’re looking for one.. ;-)]
And the writing is on the wall.
Gartner thinks that enterprises face an adopt-or-be-left-behind moment. A full 25% of large enterprises, they estimate, will be using AIOps in just 3 short years:
But it made me worry about the other 75% though…
Switching gears, let’s talk about one large, global enterprise that’s already using AIOps successfully, Blizzard Entertainment.
First of all, who is Blizzard?
Not many may know the name, but many – hundreds of millions of us across the globe – have enjoyed playing one of their many successful games, no doubt…
World of Warcraft, Overwatch and Diablo are just a few of the many blockbuster Blizzard games and gaming franchises adoring fans across the world play every day!
Among other things, in his session, Jason described Blizzard’s
- current root cause and incident response process,
- the evolution of their tech stack over the last few years,
- how they moved from manual remediation and monitoring in 2015 towards automated remediation and orchestration in 2018, and
- how BigPanda fits into their AIOps solution architecture.
Notably, Jason described the dramatic improvement in Blizzard’s signal-to-noise ratio and the rise in their availability metrics over the critical 99.8% threshold.
While the full details of his talk probably merit another dedicated blog post, it was heartening for me to hear how Blizzard, under Jason’s leadership, was able to automate and successfully scale their IT Ops team over the last 3-4 years to meet the needs of a highly-demanding, globally-distributed gamer base.
Following Jason, Elik Eizenberg, BigPanda’s CTO & Co-Founder closed the session by talking about the challenges faced by enterprises (such as Blizzard) with complex and fast-moving IT stacks.
These enterprises – and their IT Ops teams – are plagued by painful and crippling outages and incidents that are largely caused today by changes (thousands of weekly changes are the norm inside these enterprises, every week and sometimes every day).
Elik talked about BigPanda’s game-changing Root Cause Changes feature (launched a few weeks ago) that uses the Machine Learning to automatically analyze and match the thousands of changes generated in these environments with the hundreds of thousands of alerts generated in these environments…so that, finally, enterprises can get a real-time answer to the question: “What changed?”
Elik also discussed, briefly, another game-changing feature BigPanda also launched a few weeks ago, called the Real-time Topology Mesh.
In addition to changes, enterprises – and IT Ops teams inside these enterprises – deal with topologies that change by the minute…making it super difficult to understand the impact of IT incidents.
As Elik memorably put it,
By letting you stitch together a real-time full-stack topology based on topology information gleaned from all sources of topology in today’s fast-moving IT stacks, BigPanda’s Real-time Topology Mesh cures that problem.
The hundreds of people in attendance at the session seemed to get it…
And for me, that, being able to reach large enterprises whose IT stacks are increasingly hybrid and complex and moving faster than ever – and being able to offer a path forward with Root Cause Changes and Real-time Topology Mesh, made it the best way to end 2019!
I wish you and your families Happy Holidays, Merry Christmas, and a Happy New Year!
All the best for a successful and meaningful 2020!