APMdigest asked the experts who is the target user for AIOps: SREs, DevOps, ITOps, NetOps?
Start with: Discovering AIOps - Part 1
"While AIOps, partly because of its name, has been associated primarily with core operations teams, EMA has seen value across all the groups mentioned above, as well as service management/service desk teams, security, and non-IT business professionals," says Dennis Drogseth, VP at Enterprise Management Associates (EMA).
"This diversity has, not surprisingly, led to some marketplace confusion about just what AIOps can and should mean," Drogseth continues. "The values shared should stretch across these groups and may include improved service availability and performance, better business outcomes and value, faster time to deliver services, optimization of IT infrastructure including cloud assimilation, improved levels of security, and improved IT efficiencies."
"AIOps has benefits for all these roles," Gagan Singh, VP of Product Marketing, Observability, at Elastic, confirms. "Although each role analyzes different data points, they have similar functional needs in evaluating and analyzing. SREs analyze cloud and application signals, NetOps analyzes networking signals, DevOps looks at the efficiency of builds, etc. The ability to correlate specific metrics (latency, errors, etc.), logs, and traces, find patterns and anomalies and potential causes, predict and prevent issues, and execute specific actions in remediation are all relevant to these roles. All these actions require machine learning to continuously analyze signals without the user having knowledge of ML. Hence, it's important to have a ubiquitous system capable of understanding the different signals."
"Traditionally, people think about IT/infra automation as the output from AIOps, but that's probably because it's been easier to automate some of those functions than it has been to automate others — say, engineering or business functions," says Camden Swita, Senior Product Manager at New Relic. "With recent advancements in LLMs/generative AI, though, any and all of these personas can see huge productivity gains by letting an AIOps solution/assistant handle some analytical and operational tasks on their behalf."
IT's Front Line Responders
Traditionally, AIOps is the application of automation to IT Operations tasks, explains Thomas LaRock, Principal Developer Evangelist at Selector. However, there is a blurred line between roles and responsibilities for the "Ops" family — DevOps, NetOps, SecOps, etc. Therefore, every group benefits from the introduction of AIOps into their enterprise. Essentially, any group responsible for responding to an incident or outage will benefit from AIOps.
"Site reliability engineers, IT operations and DevOps spend more time than they'd like reacting to, mitigating damage from, and fixing problems that have already occurred," explains Bill Lobig, VP Product Management of Automation at IBM. "And when there's a problem, it's never just one person solving it — whole teams are affected as everyone works to limit the downtime that could potentially cost the business millions of dollars. With AIOps, individual practitioners are empowered to preemptively address and avoid problems, which benefits entire teams that no longer have to spend time investigating whether their part of the application supply chain is contributing to an adverse incident — and saves businesses from losing millions in cost of downtime."
"Everyone benefits from AIOps but really we think it is most impactful for teams and individuals tasked with day-to-day analysis and troubleshooting," adds Asaf Yigal, CTO of Logz.io. "These are the people with a potential workload of … infinity. It's really about any of these roles, and enabling the analysts with the right capabilities to work smarter and more efficiently. So it applies across the board."
SRE and DevOps
While most experts agree that AIOps serves multiple different IT roles, several of the experts see AIOps benefiting the Site Reliability Engineer (SRE) and DevOps specifically.
"The benefits of AIOps will assuredly help businesses create growth to compete in an ever-increasing digital economy," says Leo Vasiliou, Director of Product Marketing at Catchpoint.
"But the path to those benefits will go through IT teams who have to balance business innovation with systems reliability. In fact, the most recent SRE survey showed reliability practitioners believe AIOps will be most useful in managing capacity and writing code — a tie at 44%. This is great news for SRE and DevOps teams who perform both development and operational activities."
AIOps plays a pivotal role for DevOps and SRE teams by automating the processes of deploying, monitoring, and scaling applications, says Brian Emerson, VP & GM, IT Operations Management at ServiceNow. It facilitates a deeper understanding of application performance and infrastructure bottlenecks, thereby expediting the delivery of applications with greater efficiency.
"We see some pushback from SRE and DevOps teams to AIOps, primarily because it has been often overpromised and underdelivered," counters Heath Newburn, Distinguished Field Engineer at PagerDuty. "However, SRE groups in particular can greatly benefit from AIOps. These groups are usually charged with managing the entire stack, which can be difficult and particularly challenging for less experienced team members. In complex failures, identifying probable cause can be difficult. Being able to rapidly eliminate the noise, and driving automated response can be a boon to those teams in particular. But no IT team — NOC or others — wouldn't be better off with less noise and more focus."
Just Getting Started
APMdigest also asked the experts about the market penetration of AIOps. How widespread is the actual usage of AIOps?
"Adoption of AIOps is pretty low," observes Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA. "I don't have real numbers, but it's hard to find people who are using it when I'm interviewing people for my research. Sometimes they don't even know that they're using it because someone above their paygrade has added AIOps features into incumbent tools without telling staff."
"This question is tricky because there are degrees of AIOps use," says Dennis Drogseth from EMA. "Analytics have become fairly pervasive, but often in siloed use cases. Among those companies using advanced analytics at some level for IT, about a third are in process of working with or deploying AIOps across silos, which EMA views as core. These deployments are typically coupled with more progressive levels of automation."
"Companies using AIOps are in the minority now, but I don't think they will be for much longer. I recently read that the global market for AIOps platforms in 2018 was around $2.5 billion and is estimated to reach $11.02 billion in 2023 and $32.4 billion by 2028," says Swita from New Relic.
"On a related note, the industry has also seen how rapidly infrastructure is moving to the cloud," Swita continues. "AIOps and cloud infrastructure are complementary, and the more business moves to the cloud, the easier it will be for more businesses to seek and adopt AIOps — which is why I expect companies using AIOps to move into the majority in the coming years."
Ready for Takeoff
AIOps adoption is growing at a significant rate, especially among larger, forward-thinking enterprises seeking to enhance their IT operations, says Bharani Kumar Kulasekaran, Product Manager at ManageEngine.
According to a recent study conducted by ManageEngine, based on a survey of over 470 IT decision-makers across the globe, nearly 45% stated that their organizations plan to invest in AI and ML capabilities in 2023, and 54% said their organizations plan to implement AIOps by the end of the year.
Additionally, nearly 31% of respondents stated that their organizations already employ AIOps in their daily operations or are in the process of implementing it.
"It's clear that AIOps is becoming more pervasive as organizations aim to streamline their IT operations with business goals," Kulasekaran adds. "These goals include enhanced forecasting and decision-making; improved security, detection, and root cause analysis; and increased automation and productivity."
Monika Bhave, Product Manager at Digitate adds, "According to the 2022 Gartner Market Guide for AIOps Platforms, 40% of all Gartner client inquiries on IT performance analysis were related to AIOps. AIOps is continuing its growth and influence on the IT operations management market with a projected market size to be around $2.1 billion by 2025 with an annual growth rate (CAGR) of around 19%."
AIOps Is the Future
"Today, AI is more prevalent than ever across service and operations management, both in distributed systems and the mainframe," says Ali Siddiqui, Chief Product Officer at BMC.
"AI is actively reshaping society, permeating various industries such as architecture, education, IT, and software development. This impact is compelling organizations to recognize that data, analytics, and AI discussions are no longer limited to CIOs and CTOs; they have evolved into board-level concerns, fueled by breakthroughs like ChatGPT and Google's Bard. In the upcoming months and years, generative AI will significantly influence the spending decisions of enterprise tech buyers and shape the scalability strategies of enterprise software companies."
"Consequently, IT teams must proactively consider how to incorporate AIOps into their products," Siddiqui adds. "Failing to do so will leave them lagging behind the curve in this rapidly evolving landscape."
"Most every enterprise I speak with is looking at AIOps or using it to some degree, even if they are not using the terminology," Carlos Casanova, Principal Analyst at Forrester Research, concludes. "Frankly, it's because it doesn't make any sense not to. Every enterprise has siloed data sprawled across the enterprise that they struggle to manage, never mind make sense of. So why wouldn't they all want to reduce the noise, elevate the signal and proactively act to improve business outcomes?"
Go to: Discovering AIOps - Part 4, covering the advantages of AIOps.
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