Hall of Fame: Q&A with Appnomic’s Paddy Padmanabhan & Nitin Kumar

What were Appnomic’s beginnings? What is the company’s ethos?

Paddy Padmanabhan: I created the company because of my prior experience architecting a core banking solution and encountering the constant performance issues plaguing clients’ websites. To elaborate, any binary compiled code will not change its behaviour runtime, only variations in workload or an impairment in the infrastructure, including the network, storage and servers, can lead to issues. Aware of this, what I was on the lookout for was a way to quickly triage the problem and provide a lasting solution.

The Eureka moment came in 2007-2008 while I was studying machine learning algorithms. I found that I could potentially replicate my actions and decision-making criteria into a learning system that could take cognitive actions to prevent problems from occurring. That’s how the journey started.

How can Appnomic help the online travel market with application slowness?

Paddy Padmanabhan: One of our customers is an online travel portal. Any performance degradation or downtime hurts their present as well as future business owing to the multiple competing platforms that customers can easily switch between.

Also, since these portals are in the middle of connecting providers, payment gateways and consumers, they have to build complex interfaces which are susceptible to service disruptions. Given the many processing points and volatile usage demands, they need the ability to proactively fix issues and also on-demand resource scaling in order to save costs. Those are services which we offer in order to help our clients to remain competitive in a cutthroat industry.

What is your vision about Appnomic as a company?  Tell us more about the market and opportunity.

Nitin Kumar: I think this is a very exciting space that is evolving very quickly. Appnomic’s place as an enabler of self-healing enterprise is largely unparalleled based on the machine learning algorithm that we’ve built.

We believe that now we are in generation four where we’re seeing increasingly complex APIs, interfaces, and external innovation and R&D that’s being driven by outside partnerships and ecosystems.

The IT Operations market has evolved over the last 10 years in a variety of ways, including first-generation tools focused on network monitoring, infrastructure monitoring, database monitoring and application monitoring. Wave two brought intelligence and insight based on big data. The third wave, which we refer to as AIOps, has evolved in a myriad of ways. From metrics to logs to reporting to performance, there are numerous ways to look at it. We believe that now we are in generation four where we’re seeing increasingly complex APIs, interfaces, and external innovation and R&D that’s being driven by outside partnerships and ecosystems.

In the future, public cloud and edge are going to coexist in unison and the application stack is going to be spread across all three of these. Micro-services and workloads are going to be processed across all three infrastructure components. It’s important to take a workload centric view, which is why Appnomic comes with a top-down approach.

Each workload has unique characteristics based on what the application requires and what the infrastructure needs to process. Therefore, we take a workload centric view by analyzing unique signatures and processing workloads either holistically or partially, at the right place and time. We also use predictive methods whereby we take real-time data and make forward-looking projections. This is one of the best services that Appnomic delivers as it’s the first step toward enabling autonomous enterprise and creating a self-healing system.

What differentiates Appnomic in this crowded market?

Nitin Kumar: Appnomic differentiates itself in four key dimensions. First, we combine monitoring tools in order to provide top-down intelligence. Second, we have a number of patented tools that allow us to detect problems, predict future issues and self-heal them. Thirdly, our artificial intelligence core and machine learning libraries are unmatched. Back when the competition was still struggling with insight problems we were already focused on foresight problems (predicting the future).

Finally, we have the ability to provide autonomous operations across the premise, cloud and edge. We also want to emphasise the power of our team members, many of whom have more than five years of experience working with machine learning algorithms and high-volume transactions in banking, telecommunications and e-commerce.

AI is going to be embedded in everything that we use in future.

Who needs your solutions and why?

Nitin Kumar: Appnomic can help an enterprise client in three unique ways. Firstly, a consolidation of tools and secondly, unification of their ecosystem. Most enterprises have a fractured approach to monitoring, intelligence gathering and reporting. We do more than just bring these together into a dashboard; we deliver real outcomes by making predictions and suggesting various healing techniques. This results in a variety of operational, financial and technical benefits. For example, we can reduce the number of service desk tickets by preventing issues before they ever happen. Thirdly, we can help enterprises to keep their low latency applications running smoothly.

To summarise, our enterprise clients benefit by optimising operations and resources, reducing costs, gaining unified visibility and observability across the stack. Also, Appnomic can help to enhance service levels, service quality and the overall customer experience.

Paddy Padmanabhan: Any enterprise that has online transactions and deploys digital apps can face challenges as they have to deal with complex integrations. These integrations happen across applications that have been built with various technologies over periods of time and deployed in hybrid environments including on-prem and multi-cloud. Most of these relate to constant changes to applications and heavy volume demands that can occur at unpredictable time intervals.

It’s difficult to locate limits or bottlenecks in such environments so that potential issues can be addressed to avoid downtime. Our solution uses a descriptive ontology specific to application platforms and machine learning algorithms. These can crunch data in real-time across the entire landscape to deliver alerts proactively, thus keeping uptime to a maximum.

What excites you about working with AI and Machine Learning?

Nitin Kumar: AI is going to be embedded in everything that we use in future. It’s especially exciting because AI, to an extent never previously seen, is going to increase productivity and reduce errors. In AI adoption, the first level is automation and the second level is AI helping humans to work more efficiently. We need to master the AI-assisting-human dynamic in the years to come and then make a journey toward an autonomous future.

Paddy Padmanabhan: We started Appnomic with the objective of solving performance problems using AI/ML in 2007. We took a little longer to deliver a product that met our objectives, but it works as we imagined it would. Over the past few years the popularity of ML and easy availability of algorithm code is making it simpler to manage applications.

The real excitement for me is the possibility of creating ML systems that can look at wide swathes of data in real-time and make helpful suggestions that humans can act on. Although we’re a ways off from fully autonomous systems, Augmented Intelligence is still capable of adding a lot of value in the present.

What does the near future hold for Appnomic?

Nitin Kumar: Appnomic is already evolving in a few different ways. First, we are pioneers in self-healing enterprise. I think we are probably the only company which has broken away from the monitoring and reporting model. We are collecting a lot of data and feeding that into our AI algorithms in order to find patterns and self-heal enterprise systems.

Second, we are looking at information and operational technology when it comes to self-healing. We can process data from every device and application so that our focus is beyond just IT. Lastly, our vision is evolutionary; from automation to AI-assisted human action to fully autonomous implementations.

Paddy Padmanabhan: We are working with a few large and medium enterprises to solve their problems, and we look forward to scaling rapidly. We are well-positioned to do, as we have a VC firm backing us and have signed up multiple partners who can leverage our IP to help their customers. Our goal is to be a path-breaking company that can detect, diagnose and heal with as little human intervention as possible.

For more information, please go to http://appnomic.com/