What Can AIOps Do For DevOps? - Part 1
October 25, 2021

AIOps has gained the reputation as a must-have technology for IT operations. Simply put, AIOps is the combination of Artificial Intelligence (AI) and IT Operations — the use of AI to better understand the mountains of data collected by IT Ops, and use that information to ensure better IT performance and other advantages.

But why are we talking about AIOps on a site devoted to DevOps?

"Recent EMA research, AI(work)Ops examined the State of AIOps 2021," explains Valerie O'Connell, Research Director Digital Service Execution, Enterprise Management Associates (EMA). "Not surprisingly, AIOps is delivering high value — both quantifiable and qualitative — and, at the very least, paying for itself as it goes. What was a little more surprising was the ascendancy of DevOps as the major beneficiary of AIOps capabilities, edging out ITOps' more traditional ITSM constituency. The one-two punch of AIOps and automation has a direct impact on the speed of development innovation into production and the quality of the resultant services. In fact, AIOps puts both muscle and brains in modern DevOps initiatives — not to mention the fast-rising SRE function."

"The need for AIOps in DevOps has only accelerated with the increased adoption of hybrid and multi-cloud environments," adds Spiros Xanthos, VP of Product Management, Observability & IT Ops at Splunk. "Operational complexity across DevOps teams has expanded as the amount of data developers and site reliability engineers (SREs) have to sift through to triage and resolve outages has grown exponentially. Observability has elevated our ability to quickly detect problems and ask questions of our systems, and coupled with AIOps, DevOps teams have the power to automate the path from development to production. AIOps helps teams automatically respond to changes in how the production environment is performing. Machine learning helps by detecting anomalies, predicting performance problems, conducting root cause analysis and more — providing guidance on where DevOps teams should focus their energy to optimize workflows. Through continued automation, developers and SREs can increase collaboration and speed, ultimately saving organizations time, resources and money."

Clearly AIOps delivers benefits to DevOps teams and developers, as well as the obvious expected beneficiaries on the IT Ops side. This DEVOPSdigest list explores just what those benefits are.

To produce this list, DEVOPSdigest asked the top minds in the industry — consultants, analysts and technology vendors — what they think AIOps can do for DevOps and developers. Over this week and next week, DEVOPSdigest will post their answers in 6 installments

As usual with the lists published on DEVOPSdigest, many of the advantages of AIOps listed overlap each other, just as they do in the real world. The goal of the list is not to produce a clean, definitive catalog of all the benefits of AIOps, but rather to explore and showcase just how many different advantages AIOps can produce and how many different perspectives the IT community has of AIOps — and hopefully to give you a greater vision of the potential for AIOps to impact your DevOps initiative and development operation.

And if you would like to hear more about AIOps, you should also check out a similar list posted on APMdigest: What Can AIOps Do For IT Ops?


DevOps teams have become business critical. Due to the recent push for application modernization, these new application stacks are generating so much data that humans are no longer able to quickly monitor, diagnose, and troubleshoot issues. With AIOps, developers actually save time by detecting issues faster and automating routine tasks and processes that would otherwise have been executed by IT operations teams.
Abel Gonzalez
Director of Product Marketing, Sumo Logic

AIOps frees developers to work on more complex and rewarding issues and it saves time, all while minimizing risks but none of that is guaranteed. If developers aren't working with the right AIOps tools specialized for their needs, AIOps can make their jobs more complicated or simply lack real value. For example, Panaya specializes in Salesforce business domains, and in those cases, standard tools are woefully insufficient.
Zinette Ezra
CPO, Panaya


By combining the power of sophisticated AI technology with modern application development, guesswork and repetitive tasks are eliminated from the development process enabling devs to maximize their creativity, speed, and power when building applications. AI assists developers at critical phases in the application building process by automating, guiding, and validating design choices, enabling more companies to innovate at a faster pace and increasing the quality of application builds.
Antonio Alegria
Head of AI, OutSystems

Service outages not only cause customer facing events that have a direct business impact, but they are also a significant source of heartburn for DevOps teams. These teams end up running against the clock to triage and fix the outages which in turn interrupts and takes them away from their core activity of writing code. AIOps can help DevOps teams create insights from vast amounts of machine and user-generated data while providing automated remediation to resolve issues proactively. DevOps teams get the speed and efficiency, using AI and ML-driven workflows to resolve issues without sacrificing their time chasing bottlenecks. Because the source of outage can originate anywhere in the flow, we believe that the best approach is one where there is a single connected data model from ideation to operation.
Anand Ahire
Senior Director, Product Management, DevOps, ServiceNow


DevOps engineers want to maintain flexibility and agility. AIOps can help with this. AIOps event correlation solutions, for example, allow developers to get more value out of the specialized tools and processes they already use, while leveraging a centralized event processing layer that they are freed from having to maintain.
Mohan Kompella, VP Product Marketing,
Adam Blau, Director of Product Marketing,
Anirban Chatterjee, Director of Product Marketing, BigPanda


It's impossible for DevOps to reach its maximum efficiency without AIOps. Too many things have to be measured and adjusted and the only way to do that is at machine speed, using AI. AIOps toolkits give a holistic, birds-eye view of systems that enables better team and app performance, better reliability, and lower costs, making for successful DevOps projects. AI and machine learning adapt systems to the environment and help DevOps teams take the right actions.
Peter Nickolov
Co-Founder and VP of Engineering, Opsani


By combining the power of sophisticated AI technology with modern application development, guesswork and repetitive tasks are eliminated from the development process. AI assists developers at critical phases in the application building process by automating, guiding, and validating design choices throughout the application life cycle. Essentially, AI in DevOps cycle enables to shift-left the quality assurance in a more guided and automated way.
Antonio Alegria
Head of AI, OutSystems


As a user of traditional monitoring methods, you have to observe vast amounts of data on charts and set alerts based on your assumptions. Sometimes reality bypasses your assumptions. By the time you spot the problem, you're already in the middle of a severe incident that takes hours or days to resolve, not to mention the aftermath. We designed computers to work with vast amounts of data better than humans. With the latest AI results, they can outperform humans to do the observation work, letting you stay in the flow of feature implementation — unless there is something you have to care about instantly.
Arpad Tamasi
Principal Product Manager, Rollbar


AIOps creates an environment where code is always ready for a release.
Muraleedharan Vijayakumar
Senior Technical Manager, GAVS Technologies

Go to: What Can AIOps Do For DevOps? - Part 2

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