It’s been a long time coming, at least in mind anyway, but I’ve finally got some great news to announce. We have just published four AIOps-related reports that I’m really excited for you all to finally read and provide feedback on. Read on below to get a synopsis of the three reports. The fourth report is the Now Tech: Artificial Intelligence For IT Operations, Q2 2022, which was also just released and has a separate announcement.
AIOps Journeys From The Trenches
Aren’t you always curious about the journeys people ahead of you have made? Maybe you want to understand what they were thinking when they started and what they were trying to achieve to see if you can learn from their experiences. Well, this report is for you, because I interviewed nine infrastructure and operations leaders from around the world and across a variety of industries to get answers to these questions. These individuals were selected because they started their AIOps journey several years ago, when AIOps was just a budding thought in a few forward-looking minds.
These individuals saw the future challenges ahead of them. They knew that they couldn’t handle the increasing volumes of data and knew they didn’t have insight into actionable information. It’s not the 1848 gold rush, but these folks traveled similarly uncharted paths. The gold nuggets they were seeking to discover were day-to-day operational processes into which they could infuse AI to help with their problems. I’m far from a historian, but capturing the thoughts of these individuals when they began their journey is important for everyone to understand. Anyone looking to travel in their footsteps should take a look at this report and find their nuggets of gold in the stories from these AIOps journeys.
Report Description — The AIOps Journey: Seeking Value And Clarity
The mystery of AI for IT operations (AIOps) began as soon as it surfaced in the late 2010s. At the time, there was little guidance beyond the promise of AI- and machine-learning-driven insights, and tactical details were nearly nonexistent. Some tech leaders set out on this journey anyway, charting their own path forward, while some vendors hijacked the AIOps term, further obscuring its capabilities. Confusion remains, but some organizations did make progress. This report looks at how some technology leaders persevered through their AIOps journey and delivered value for their organizations.
Please Stand: The AIOps Reference Architecture Has Arrived!
These next two reports are just the start of what I plan to be an extensive series of reports around AIOps. Everyone who has spoken with me since I started at Forrester last fall knows that I set out on a mission to provide guidance around what AIOps was and wasn’t. My background as an executive advisor, enterprise architect, electrical engineer, and OOA&D (object-oriented analysis and design) architect told me that we needed a picture that, at a high level, described the bounds of AIOps. Some background on why we needed this picture is also important. That is what these two reports are about. While they aren’t nearly to the level of depth still needed, they are the start of the series that I have in my plans to release over the coming months and years.
The AIOps Reference Architecture series begins with The Forrester AIOps Reference Architecture: The Need For Clarity. It speaks to the background of AIOps and why we need this picture. It seeds the AIOps discussion with common terms and a clear image of AIOps expansiveness. It illustrates the five functional tiers of capability and two structural pillars that ensure accuracy and improvements. The second report, AIOps Reference Architecture: Defined, is the official announcement and introduction of the first-ever Forrester AIOps Reference Architecture.
This was a heavy undertaking that I could not have accomplished without the input from nearly a dozen Forrester analysts from across our organization and feedback from 28 different vendors, from startups to billion-dollar entities. There is no way I could have accomplished this without their input. One of the most important components of these reports is the new and improved formal definition of AIOps, which is below. Forrester defines AIOps as:
A practice that combines human and technological applications of AI/machine learning, advanced analytics, and operational practices to business and operations data. AIOps enhances human judgment, proactively alerts on known scenarios, predicts likely events, recommends corrective actions, and enables automation. It is fueled by coalescing and transforming sensory data into AI-enriched actionable information. A retrospective causal analysis and governance structure fuels foundational improvements and trust.
As I mentioned, these are the first two reports of what I expect to be an ongoing list in the series. There will be reports focused on putting it into practice, executive guides, and some that will be use-case-specific. I’m mostly excited, however, about reports that my colleagues such as Julie Mohr have slated that will look at how AIOps and AI more generally are impacting their operational areas. Keep an eye out for her report, Understanding AI In Knowledge Management: A Multilevel Review, planned for an October 2022 release — I will collaborate with her on writing it.
Buckle up, everyone, because there’s a lot more yet to come. These four reports are not even the tip of the iceberg. The full series will speak to both leaders setting strategy and practitioners responsible for the implementation. As I’ve written about in my blogs, observability is in my sights, as well. It’s vital that we similarly understand all the moving parts in an observability solution and how they differ from an AIOps solution. Enjoy the ride, and please reach out and provide feedback to make sure that this information is relevant and valuable to everyone.
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