Coined by Gartner in 2016, the term ‘AIOps’ refers to the combining of big data AI and machine learning to automate and improve IT operations processes. Back then, this very broad definition led to some confusion, with different IT vendors characterizing AIOps differently, depending on what they were actually offering.
As the years went by, leading vendors defined the reality of what AIOps actually was through their products, which aimed to answer the challenges their customers were facing. As a result, AIOps is now more clearly understood and its definition more focused, with practical applications and trends, as can be seen in the latest annual Market Guide for AIOps Platforms recently released by Gartner.
Whilst AIOps platforms enhance a broad range of IT practices and functions – I&O, DevOps, SRE, service management and more – it is specifically in the I&O domain that Gartner sees real benefits, including anomaly detection, diagnostics, event correlation, and root cause analysis (RCA) – all of which work to improve monitoring, service management and automation tasks across the board.
In the Market Guide for AIOps, Gartner also touches on the main components of what vendors recognise as today’s incident management lifecycle, and how an AIOps platform can assist in each of them:
- Ingestion – the collection and normalization of events or telemetry from multiple domains, vendors or sources.
- Enrichment – the assembly of a unified topology of IT assets, including applications, across domains.
- Correlation and compression of events to high-level incidents, reducing noise and unnecessary human intervention.
- Root cause analysis – to enable the detection of an incident’s cause.
- Remediation – either by offering a recommendation, automating a response, or triggering an external automation system.
So, now that we’re aligned on how Gartner and the market understands AIOps, let’s take a look at some key takeaways from their report.
AIOps is important, growing and here to stay
“AIOps platform adoption is growing rapidly across enterprises” says Gartner. The reason is simple – with gigabytes of data being generated per minute, across dozens of domains, it simply isn’t feasible to rely on humans to derive the necessary insights through manual analysis.
Looking forward, Gartner contends, the AIOps market will see “a compound annual growth rate of around 15% between 2020 and 2025”, thanks to digital transformation, and the transition from reactive to proactive response to issues.
The future of AIOps is domain-agnostic
Gartner identifies two categories of AIOps solution which we’ve discussed in the past: monolith and best-of-breed, or domain centric and domain agnostic.
Domain-centric AIOps solutions offer a restricted set of use cases focused on one specific domain, or data specific to a framework or practice – usually involving a monolith solution supplied by the vendor that is used by the organization for most of its IT needs. As such, they are relevant to organizations that have limited data variety and prioritize a one-off, specific or small number of focused use cases, and therefore have little need or ability to look simultaneously at data across multiple silos.
Emerging as a stand-alone market distinct from domain-centric AIOps platforms, are the best-of-breed or domain-agnostic AIOps platforms, which are designed to be general purpose. Able to ingest data streams from most existing monitoring tools, they therefore cater to the broadest use cases.
These platforms have various advantages, the first being enhanced flexibility, in that they simultaneously process diverse datasets across multiple siloes (such as observability, topology and change data), including historic and real-time streaming, and offer a progressive roadmap. Secondly, domain-agnostic AIOps solutions enable support of multiple use cases across IT Ops management, including I&O, DevOps, SRE, and in some cases, security practices, using a single platform. What’s more, these use cases go beyond anomalies to include behavior analysis, customer engagement and identification of underlying opportunities.
How do you choose the right AIOps solution for you?
The Gartner report explores all the ins and outs of AIOps, shares its market analysis of vendors and the platforms that are currently available, and then details specific AIOps adoption recommendations for I&O leaders who are focused on infrastructure, operations and cloud management:
- Adopt an incremental approach that starts with replacing rule-based event analytics and expands into domain-centric workflows like application and network diagnostics.
- Use domain-centric AIOps features built into a monitoring tool for a one-off, specific use case, and deploy a domain-agnostic stand-alone solution with a roadmap straddling multiple use cases.
- Enable task automation, knowledge management and change analysis by selecting an AIOps platform that supports bidirectional integration with ITSM tools.
- Select the AIOps vendor best suited to deliver out-of-box capabilities for the first step on the roadmap and to provide a platform that is aligned to the organization’s roadmap.
Another important guideline is to ask your vendor about time to value. Some AIOps solutions can take six months to two years to deploy, configure and deliver value, which for many organizations is just too long to wait for a payoff. However, vendors are working to respond to this concern, so make sure you check before signing on the dotted line.
Since its introduction in 2016, AIOps has developed greatly to become a practical, necessary and winning technology, used by leading enterprises from all market segments to enable the services they provide their customers.
To learn more about the AIOps landscape, read the full report – and if you want to learn about BigPanda’s AIOps-driven Event Correlation and Automation platform and how it aligns with the Garter report, start here.
Gartner Market Guide for AIOps, Pankaj Prasad, Padraig Byrne, Josh Chessman, April 6 2021
Gartner, Inc. does not endorse any vendor, product or service depicted in its research publications and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.