AIOps Evolution Podcast | Season 2
Interview with Jayanti VSN Murty from Digitate
In this episode of the AIOps Evolution Podcast , Sean interviewed Jayanti Murty, CTO (Americas) at Digitate. They discussed what’s fueling the AIOps trends now and what we can expect looking down the road in three to five years.
Currently, the AIOps market is slated to hit $10 billion USD by 2027 as enterprises look to simplify and optimize their IT and Security Operations. With a predicted market share like that, Jayanti and Sean both predict that AIOps trends will transform from “nice to have ‘new-fangled’ tech” to essential business driver.
What’s fueling AIOps as a movement?
Digital economies and the demand for digitized business experiences continue to ramp up well into the next decade. Gartner projects that by 2025, 95% of modern applications will be built using cloud-native strategies. The demand for hybrid and remote job working conditions will continue. Along with a shortage of qualified professionals to keep up with technological advancements, AIOps is a viable option for businesses looking to stay ahead of the curve.
Jayanti says that there are three “phenomena” fueling the current AIOps movement: Data growth, computing growth, business growth; the expanding landscape of enterprise IT and the push for scale. Diversity in technologies, including legacy applications or platforms retained while adopting new ones.
He expanded on them in his discussion with Sean. Here’s what he had to say.
We’ve had to reimagine the idea of IT Operations (ITOps) within the last decade, due to the rapid growth of data and technology demands. It’s become critical for machines to augment organizations due to the sheer depth and breadth of data points and technology requirements.
In ITOps there’s a lot of repeatable work and data use that take up too much time from human operators. This has created a need for the construct of AIOps – analytics and machine learning (ML) applied to a vast amount of data to break down complexity and siloes. Essentially, automation eliminates repeatable tasks.
The IT Talent Crunch
Furthermore, your best people are firefighting instead of building, designing and constructing. AIOps helps alleviate some aspects of the current IT talent crunch. For instance, when people leave, this creates a void where the rest of the Ops team has to “play catch up.” Digitizing this knowledge is essential to help with the continuity and sustainability of ITOps teams to scale as well as support larger business objectives and functions.
All of that has culminated in the rise of AIOps trends and its adoption by small, medium, and large enterprises around the world. It’s inevitable that this would happen because the Operations department is so data heavy, and with expanding parameters daily, it’s not humanly possible to effectively manage it all.
AIOps trends in five years
That brings us to the big question: Where will AIOps be in three to five years? Jayanti speculates there will be three “phases” contributing to the growth of the AIOps evolution in the near future:
- Technology demands
- The way it’s measured
- Adoption and expansion
AIOps Spans Multiple Domains
There is no doubt that the next five years will see AIOps moving beyond IT Operations. While it all started with predictable use cases, such as infrastructure extending to applications, it will expand into multiple domains. Jayanti predicts it will find relevant use cases in cybersecurity and business applications. Due to that, business stakeholders will take notice of this shift and get more involved in the AIOps journey. With decision-makers paying more attention to AIOps trends, greater care must be taken in strategizing for AIOps and putting it to use where it will be most gainful.
A lot of AIOps technology has to be ready to face the challenges posed by the modern multi-cloud environments we are using. When you have legacy, on-prem, data centers, and cloud, many current AIOps tools struggle to have use cases that span across all of these. Cloud and the option of cloud, especially as it expands, impacts the fundamental notion of cloud operations.
As these multi-cloud and hybrid environments become more mainstream, we’ll see AIOps dealing with more use cases and reaching new domains.
Taking AIOps to the Edge
We’ve learned a lot in the last year about how far on the edge we can work and function. This is no different for AIOps. As we continue to explore AIOps use cases, we will see it extend to critical “edge” components like naval vessels, remote oil rigs, cruise ships, and telecom towers. A lot of AIOps trends will go further out as there is a greater intake of AIOps on those fronts.
Sean used the example of the Navy as a prime candidate for AIOps. Naval vessels are far out to sea with limited bandwidth. There are thousands of people communicating on critical military projects using satellites. In these cases, cloud solutions are not applicable. Distributing AI to the edge in an independent, self-running system is key for remote locations such as these (oil rigs, aircraft carriers, etc).
Measuring the value of AIOps
Finally, Jayanti says another interesting piece contributing to the future of AIOps is the growth of the customer’s ability to measure the maturity of AIOps in their environment. This includes three components:
- Metrics around effectiveness
- Usefulness to business
As stakeholders pay closer attention to AIOps use cases in their enterprise, they will adopt it in a structured manner. It’s more than technology to try out now; it’s essential for business growth. So, we will see more fast-time to value for adoption models, greater out-of-box capabilities, and structured adoption. Operators are no longer looking for low-hanging fruit; they are talking about larger business impact and the transformational journey that comes with AIOps. We’re already seeing this with early adopters who are paving the way for others.
The AIOps evolution is not about buying “cool technology.” It’s evolving to encompass business values, effectiveness, and solving real problems. It’s about a very structured approach of trying to solve pertinent problems of today and tomorrow. And it’s essentially trying to get a headstart on the challenges that the technology landscape will throw at us in the near future.