“In the last three years we have made two more releases and the positioned them to combine AI and automation in a cognitive way to get work done,” said Rahul Kelkar, Chief Product Officer at Digitate. “From that positioning we have kind of matured into what we call a three pillars strategy.”

The first of these pillars is unified observability, which provides visibility and control across IT and business across hybrid multi-cloud states. It takes care of the vertical stack observability right from your infrastructure, cloud platforms, applications, all the way to business functions.

“It also takes care of horizontal observability, which is all the business transactions that are going across multiple hops in your various business functions, with AI-powered insights,” Kelkar said. “These first two capabilities preparing for accruing the benefits by bringing in the observability then deriving insights from it. That’s the second pillar.”

While these first two pillars are in some sense preparing for accruing the benefits by bringing in the observability, then deriving insights from it, it is the third pillar that actually delivers value to the enterprise, with adaptive observability and closed loop automation.

“Of course, there is value in observability and transparency, but the real tangible value in terms of effort and improved availability comes when all the three pillars all play together,” Kelkar stated.

A focus of the new release is what Digitate calls the transformation to a “ticketless enterprise,” in which advanced AI and machine learning, combined with powerful elimination and prediction engines, minimize the need for manual ticketing and enable proactive issue resolution before they manifest and generate IT tickets.

“Ticketless enterprise has been our vision for the last almost two and a half, three years, and when I say ticketless, it’s not really avoiding the recording of work items or what is happening,” Kelkar stated. “It’s not aimed at eliminating the auditing and recording, but it is aimed at changing the perspective from everything associated with the ticket. Typically, enterprises measure everything through SLAs and this happens more often when there is multiple service providers involved and as a result everything starts getting focused on SLAs experience and efficacy and all of those start becoming secondary as long as SLAs are made everybody feels like they are happy. So our idea behind ticketless is actually eliminate before automate, whereas most enterprises take the automation path and they try to reactively automate incidents or requests and things like that.”

Kelkar said that even if an issue happens in your system, Flamingo can identify all diagnosable recurring issues that keep on happening, even if they are getting fixed through either automation or manually.

“It will identify the root cause of why these issues are happening and eliminate that root cause so that these issues stop happening, and you are not just reactively keeping on fixing the issue,” he noted. “With this release we have actually released the first two major use cases in this area.”

Doing this with vertical stack observability is now table stakes, because it’s something that observability tools focus on.

“They will do a good job of monitoring your metrics, events, logs, traces and things like that, which is right from infrastructure to cloud, platforms, and applications,” Kelkar indicated. “These tools have been around for quite some time, doing this full stack observability as they call it. It is, however just vertical stack observability and that is just one part of the three things that need to be done.”

Kelkar said that the second part that they have experienced in the last 10 years that we have been trying to deploy is new.

“It is horizontal observability and what I mean by that is typically a business transaction so you take a retail store kind of a scenario where somebody is coming in and trying to check out some stuff,” he noted.  “This process actually is realized on multiple applications, and is order management that comes into the picture, including merchandising, inventory, payment, loyalty and so on. So a bunch of applications involving a transaction of checking out some stuff from a store actually flows through multiple hops across multiple applications. And though each one of those applications may be individually monitored, there are various scenarios where the horizontal business transaction actually does not go through smoothly. Either it chokes or gets delayed and there could be a lot of reasons for that. Horizontal observability compounds that with horizontal business transaction observability across multiple hops and that sort of creates the quadrilateral for us.”

Kelkar emphasized that while both vertical and horizontal observability are good, they are not sufficient.

“The third piece is actually what we call as adaptive observability,”  he said. “What I mean by that is a point in time picture of vertical stack and a horizontal observability along with the thresholds that are configured so that any anomalous transaction or any anomalous behavior of the system that goes beyond those thresholds can be flagged as an incident or alert. The problem is that in today’s global and enterprises, everything keeps on changing. The workloads change, the configurations change, policies change, everything changes. As a result, the normal behavioral model of this entire vertical stack and horizontal transaction needs to be updated on a continuous basis so that it captures significant persistent change all the time and that’s what I mean by observability. The way the vertical stack and a horizontal observability are configured, any anomalous transaction or any anomalous behavior of the system that goes beyond those thresholds can be flagged as an incident or alert.”

By doing these three things together we believe that we are not comprehensive in terms of our definition and realization of unified observability, but they are also very effective for the other two pillars that I just talked about to take over.”

Generative AI has also been upgraded in the new release.

“There are new AI-driven assistants for support, product queries, insights, and code generation/conversion to streamline operations and accelerate time-to-value,” Kelkar stated. “Also, the new Flamingo release features a new integrated Gen-AI powered agent, ignio AI Assist. Trained on Digitate’s extensive knowledge database, it is designed to offer intelligent conversation for faster diagnosis and resolutions, propelling IT to transition towards a more technology-first approach. With advanced analytics and predictive recommendations, ignio AI Assist delivers contextual and actionable insights that significantly reduce time-to-resolution, serving as an expert to optimize cost, performance, and capacity for autonomous actions.”

This version also introduces noiseless Adaptive Event Management, an AI-based semantic search that auto-suppresses irrelevant alerts, drastically improving noise filtering. Its human in loop approach increases control and accuracy.