As the rapid digital transformation has put a lot of pressure on IT organizations to be more proactive and agile, DevOps principles and practices have been an invaluable resource. However, to remain at the top of the game, organizations need an even stronger solution. So, what’s the answer? AIOPs (artificial intelligence for IT operations), of course! By adopting and leveraging AIOps, IT organizations can automate and enhance IT operational practices and access continuous insight into their business performance.
But there is still a lot of confusion over what AIOps is and does. I recently sat down with Carlos Casanova, Forrester Principal Analyst, and Gowrisankar Chinnayan, heading product management at ManageEngine, to discuss what AIOps is and hear about some predictions for its future.
Ok, what is AIOps?
When I posed the question to Carlos he gave an interesting answer.
“I guess the first thing for everyone to realize is that it is not just a technology; it is really a practice,” he said. “You take some human aspects, some processes, some capabilities, some experiences that we have and add [them] with the technological aspects. When you bring all that together under the umbrella of artificial intelligence (AI) and machine learning (ML), that is really where AIOps starts to play. It enhances human judgment, improves decision-making and enables automation.”
To put it simply, AIOps uses big data, machine learning, and analytics to efficiently and proactively manage the IT landscape.
Can AIOps make ITOps better?
The experts say yes. Understand that AIOps is not here to replace ITOps—its here to enhance it.
Carlos made sure to narrow down the reasons why adopting AIOps is best for your IT environment.
Proactive footing
By unifying all the manual IT operations under one single entity, AIOps enables IT operation teams to respond more quickly, even proactively, with full stack visibility and context.
Incident response
With AI-backed insights and intelligence, root cause analysis is made faster, enabling a dramatic decrease in response times.
Faster MTTD and MTTR
By identifying signals out of the noise and sifting through data from multiple IT environments, AIOps easily identifies root causes faster and resolves them accurately to drive down the MTTD and MTTR.
Put AIOps in action and see the results!
To date, IT teams do numerous IT-related tasks manually. AIOps helps by automating the workflows and cutting down on the time spent on repetitive and time-consuming operations. So, the main aim of IT operation teams is to recognize such difficulties and deploy AIOps to create a better user experience for their clients.
Gowri gave us an excellent example with our network monitoring tool OpManager.
OpManager has different set of built-in monitors, each having its individual threshold configuration. Initially, customers spent hours or even days configuring it based on the number of monitors. Through a lot of trial, error, and feedback from our customers, we finally introduced AIOps to sift through the data. AIOps can analyze and identify patterns, trends, and seasonality.
In the end, OpManager was able to set a threshold for every hour (i.e. adaptive threshold) and reduce the manual effort and time required to none—all thanks to AIOps!
Carlos agreed that the adaptive thresholds were indeed the key to user experience, providing us with another scenario.
That is it for part one of my summary of our conversation with Carlos and Gowri. Next time we will discuss why organizations should adopt AIOps and the challenges they might face. Stay tuned!
