AiThority Interview Series with Edmond Baydian, Chief Strategy Officer at Optanix

Most people use performance monitoring after the fact for historical analysis. We’re using it at the speed needed for operational runtime.

How are managed service providers evolving? How are they dealing with the increased complexity of IT infrastructures and services?

There have been great strides in the performance world. There are many algorithmic approaches that the performance management vendors have brought to market over the last couple of years. When we think about AIOps and machine learning, we see it adding multiple layers of value. Advanced automation, for example, can provide incredible value to an assurance strategy and service delivery model.

Our customers are drowning in data. What we’re doing is we’re guiding them to take an integrated approach to get the most value from their data. For us and our customers, using the data we collect is a mantra.

What are you hearing from your customers?

Our customers love the fact that Optanix is an MSP with our own intellectual property. They have been asking for us to use that intellectual property sometimes without managed services. They wanted productization of what we were doing with our own internal business practices built into our technology.

One of the things we did was follow through on our ‘voice of the customer’ survey that we conducted. It turned out to be incredibly valuable. We reached out to more than 120 enterprises and managed services providers and concentrated on what enterprises want from their service assurance solution, whether delivered by their MSP or done internally and what they want out of their service assurance tools. And we were already very focused on the service assurance aspect of how the tools support a business process, and how they support the business impact.

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We have traditionally focused our business on contact center environments and the integration of underlying VoIP infrastructure and networks supporting those environments, particularly in the Cisco ecosystem. From years of operations, experience and iterations on the Cisco product set we have gained a solid understanding of those operating environments and the need to manage what complex interdependencies in large distributed applications. We leverage them within our platform to drive business outcomes, particularly when we provide managed services for each customer in those environments.

Is that part of your new release of the Optanix Platform? 

Absolutely. Version 5.6 is an important release for us because we provide a managed software experience where we’re providing the management of our service assurance software. In doing that, we’re addressing our customer demand.

So, we’ve been on this journey of basically democratizing our intellectual property so that others can use it. We’ve been busy unpacking what we do and making it applicable to people outside of our company to consume directly – MSPs and their customers.

What other capabilities are in 5.6?

One of the things that we’ve traditionally done well is to integrate network-based root cause analysis with a stateful understanding of system interdependencies. And the integration of fault and performance was the number one thing that people in the survey expressed they struggle with, so we’ve ramped up our game there and will continue to do so.

Optanix provides many of our customers with monitoring and event correlation value and ties it to their ITSM solutions. Those customers that also add to performance management capabilities are able to achieve a higher value than most.

But all of their stuff is very disjointed. Their tools and data are siloed and only being connected at the ticket level for awareness. Integration of the information value is needed directly at the monitoring layer. With 5.6 our goal is to help them get value out of that data. What they are looking for is to have their tools derive more value for them by automatically understanding things, so what we did with 5.6 is a layer in performance attributes that we call smart analytics.

How does that create value?

We are taking an algorithmic approach to using the performance data that we collect. That drives meaningful impacts where we can look using advanced calculations to rapidly spot changes within an environment. We’re helping customers get value out of their performance analytics in a real-time manner. Most people use performance monitoring after the fact for historical analysis. We’re using it at the speed needed for operational runtime.

Our decision engine drives automation. In the past, it was driven by event correlation. But now, with machine learning applied to performance monitoring as inputs into the decision engine, we’re generating a higher degree of fidelity by automatically using the data we collect as we collect it.

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So that’s what we call using the data. Not just for capacity management and historical trending, but to help highlight how real-time trends are impacting the environment right now.

I mentioned the integration of capabilities. We have an automation layer that’s integrated with the same system that does the performance and fault and event monitoring and the root cause. This automation allows us to leverage the insights that are gained from the root cause analysis from different perspectives – topology awareness, for example.

It’s exciting. We can leverage the insights we gain from looking at performance analytics and actually go back into the environment and use automation to test a variety of validations if needed. We can then refine what that “something” is with positive and negative feedback looks before presenting anything to an operator or ITSM system. Some of our customers are asking us to use these capabilities to make corrective actions on an automated basis in their environment, and having an automation platform built directly into our service assurance platform allows us to greatly reduce the time spent on incidents.

Are people taking advantage of the Automation?

Absolutely.

Our customers use runbook automation that has been introduced at the IT service management layer. But those run-books occur after performance collections, after events, after root cause analysis. You typically have process and time lag as you go. But while underlying collections are occurring, taking the sensory input and telemetry from the customer environment, we are actually executing automation at the collection layer before they get presented to the ITSM solutions.

By bringing automation value down to the service assurance layer, we’re able to react far more rapidly and reduce the number of incidents people look at. We can drive a greater level of fidelity in terms of the information in the analysis by being able to drive immediate positive feedback loops. Or we can leverage additional sources of valuable real-time information that are not presented as telemetry. But because we can automatically interact with the monitored systems, we can enrich our understanding with operational context.

Because of our integrated approach, our customers can leverage information coming from what would traditionally be multiple monitoring silos within a server assurance stack in one single place. And that’s what they asked for, the reception has been great.

What’s next in your development cycle?

Where we’re heading next in our AIOps journey, and the investments that we’re making in additional machine learning is around driving insights to how that automation is being used – and how effective the automation is. We have our eye on addressing the chasm between network/systems monitoring and application performance monitoring.

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Thank you, Edmond Baydian! That was fun and hope to see you back on AiThority soon.