Apica acquires Circonus with Ranjan Parthasarathy

This is Textron tv. Hi everyone. Welcome back here to Textron tv.

Our next guest is Mr. Ranjan Par Sohi. Ranjan is the chief product on tech and technology officer at a peka, and he joins us today.

Ranjan, welcome to Techstrong tv. Uh, hey, great, great to be here and, uh, um, look forward to, you know, connecting with you and your audience. Uh, and, uh, you know, we are excited to talk about aika today, uh, absolutely.

And the very interesting things that, you know, we feel we bring to the market, uh, and we look forward to having a great, uh, next 15 minutes with you and your audience. Thank you, Rajan. Rajan, before we get to a peaker in some of the discussion, I always like to give our audience a sense of who they're talking to.

So if you don't mind, I, I mean, I mentioned you a chief product and technology officer, but give people a little bit of your background of your history. Uh, sure. Yeah.

So, I, I'm Ranjan, I run product and tech at oe a, uh, prior to oe a I ran my own, uh, company in the data space, uh, which Oe a acquired last year. Uh, prior to that, uh, I've been in the tech industry for about 25 years, working in, in a variety of companies, including, like of Sun Microsystems, Oracle Nutanix, uh, have been an entrepreneur, uh, uh, since 2015. Uh, and have enjoyed the journey, uh, and really excited about what's happening in the data space.

Uh, and you know, how, you know, we think data is changing and how data consumption is coming for businesses. So really excited to be here. Absolutely, man, hearing sun brings back memories, brings a smile to me.

For me anyway, at my age. You know, sun represented kind of the pinnacle of, of innovation, of, of exciting things. You know, whether it was the, the internet really catching on, or, I mean, hardware, software, it was just what a company.

Um, anyway, it's a pleasure to have you here today and welcome. You know what, I, I don't know if everyone, as a matter of fact, I'm sure that everyone in our audience, or not everyone is familiar with aika. There may be some.

So why don't we, if you don't mind, give our our audience a little bit of a sense of, you know, a pika. What, what's, what's the, uh, company's story there? Uh, sure.

Yeah. So, uh, Pika, uh, is headquartered, uh, out of Sweden. Um, and it has global operations in the United States, in, in India.

Uh, and we as a company, um, provide a data platform for enterprises, uh, which covers pretty much the management of data through the data life cycle, you know, all the way from data generation, data collection, you know, data storage, data organization, uh, data consumption, you know, things like data analytics, optimization. It really helps, uh, businesses and teams do more with their operational data or machine data as we call it. Uh, so our focus really is machine data and operational data.

So we, we deal with things that come out of cloud environments, systems, applications, uh, and tend to be, you know, generated in a wide variety of formats. Uh, and that that's what makes it more challenging to, to kind of, uh, deal and handle with all of this variety and this complexity and, uh, and the sprawl that we see in enterprises today. Um, so, uh, we are excited about, you know, what we offer as a platform, uh, because history itself, you know, started as a synthetic monitoring company, which is really around data that tends to be more from a digital user experience perspective, right?

So you're trying to understand KPIs on things like service endpoints, websites, mobile applications, uh, more dealing with KPIs on, on end user performance. Uh, and that really answers the question of, you know, what's going wrong with, you know, a software or a stack that you may be operating? But what it did not answer prior, you know, to, to us evolving as a data platform was really why something was going wrong.

And so if you look at now the, the platform that we offer, we can actually connect the what with the why, uh, which is, you know, what's failing, and then answer the question why it's failing. Uh, and this is, this is a significant transformation that we have made as a company. Um, and we really are, you know, bringing together digital user experience KPIs with things like observability of operational data, kind of into a single platform, uh, while solving for problems like, you know, long-term data retention, things like enterprise compliance, uh, in a turnkey form factor, which really makes it easy for enterprises to solve the complex data problems that they have today.

Excellent, excellent. Um, you know, you mentioned they, uh, PIKA has, uh, based in Sweden, us, uh, India, uh, how long has, has been a PIKA been around? So the, the aika synthetic monitoring platform, uh, was born, uh, you know, uh, a decade ago, but the transformation of aika into a more data platform and a data fabric has that journey started about two years back.

Um, and we are rapidly innovating in that space. Um, we have, uh, you know, uh, about a hundred plus customers globally, um, and we, uh, we cater to a wide variety of, uh, uh, you know, enterprises all the way from, you know, financial companies to manufacturing, you know, more cloud native companies. So it, it's across the board.

Um, and, uh, it, it's something that we see as a, you know, as something where a PIKA can help businesses no matter what industry and market you're in, data problems are common across the board, uh, and, uh, data challenges are common across the board. Um, and, you know, we can really address that, you know, what with what we have today. Excellent.

Okay. So a peak of, as you've been talking about recently announced its service level assurance platform, right? SLA mm-Hmm.

As we call 'em in the industry. Excuse me, if you wouldn't mind, why don't, why don't we start, you know, with that, and then talk a little bit about, you know, what it brings to the table, Right? Yeah.

So I think, uh, that's a good, good, uh, thing to segue into. So, you know, as I mentioned, right, we are now looking at data more holistically. Um, and, you know, synthetic monitoring tends to offer, uh, SLAs from a, you know, end user experience perspective, right?

And, and so going back to that thing, which I mentioned is it does answer the question of what's breaking with respect to your SLAs. Uh, but that's just one part of the problem, right? Once you know you're not meeting your SLAs, you would like, you would like to know why that is happening, because that is critical to figuring out how to address that problem.

Um, and so now if you look at the pka platform, you know, we can look at end user experience, we can connect that with, you know, backend system data, which traditionally comes under the domain of observability and connect the two together. And that's why when we talk about our platform, we call it active observability because digital user experience is now connected to observability. 9% of the enterprises.

Um, and that poses a problem because now you're talking about data sitting in two different silos, or maybe even more than two different silos, and somebody needs to now be aware of all these data silos, bring that intelligence and the data together, mine the data before, you know, concrete actions can be taken. Whereas with our approach, because this end-to-end connectivity comes from a single vendor, it becomes a lot easier, you know, to arrive at insights and make quick decisions about root cause much faster. I mean, that's how we see it.

Uh, and the way we are approaching this as a data platform is we are first solving for data unification. Uh, we want to eliminate data silos, right? Digital user experience data, observability data, data in the form of config, sitting in config management databases.

Once you unify them together, insights become a lot faster. Because at the end of the day, think about, you know, digital user experience, synthetic monitoring, observability, all of this. These are really a means to an end, right?

And the end really is, I want business continuity. I want to be able to troubleshoot things faster. Now, that cannot happen when data is so fragmented all over the place, right?

And that's the problem we want to address first. And we kind of always talk about how this problem has to be addressed first, as you know, the foundations of a skyscraper we are building, right? If the foundations are fixed first, the rest of the problems become a lot easier to solve.

Sure. You know, Ranjan, I've seen in the last two, three years what I call a return to the primacy of data, right? Um, for, for for many years, all of the action, all of the emphasis has been on your, the application building, your application that, you know, collects and analyzes and spits out data.

It's been on what my infrastructure stack looks like. Am I using containers and Kubernetes? Am I in the cloud?

Am I in, you know, private cloud, uh, bare metal or not? Um, and of course, security security's become primary, primary, no matter what you're doing, it has to be secure. But in the last two, three years, I've seen a shift where we're remembering it.

All of these other things exist to serve the data, right? It's 'cause it's about the data. That's, that's where the value is.

All these other things enable mm-hmm. The data, but it's the data itself. And, and so, you know, I I, I imagine the ika timeline of two years ago, kind of moving into this, coincides with this, it seems like we woke up 'cause we used to know that, right?

And then we got, like we do in technology, you know, went down a couple of different rabbit holes. But it, it is so, so much about the data. Now, one of the things we're hearing is like, I don't know if you're familiar with the term SLO service level objective, right?

From an SRE perspective versus SLAs and, you know, because SLAs are generally something we use in lawsuits when someone didn't do what they were supposed to do. Um, I'm wondering how that fits into your platform vision, Right? Right.

Yeah. So yeah, I think, I think very, very fair point. Um, I think we are all about data.

And, and that's, that's the one thing I want to highlight here is everything else is relevant, but it is serving the end goal, which is I need high quality data when I need it, right? Whether it's security, whether it's being, you know, multi-cloud environment ready where you know, you or you can bridge legacy data with more, more modern cloud native data. At the end of the day, the goal is high quality data to the consumer when they need it.

Uh, and that's what we are solving for. Uh, and part of that S-L-A-S-L-O discussion is, is really around SLAs. You know, we need to be able to tell people when something goes wrong.

But when you think about SLOs, it's really about transparency of how do you make decisions? How do you understand what's happening with your data streams? 'cause you cannot arrive at objectives when you don't have the basic visibility into what's happening in, in a complex environment.

Um, and so objectives, when defined without that transparency usually tends to not work as well as expected. Uh, whereas when you define the objectives with full transparency, with, you know, how you're operating, how much data you're generating, how many data sources exist, what are the interesting characteristics of each of these data sources that, you know, we manage, then your objectives become more practical, more real, and more, you know, realistic, uh, uh, to, to, to, to first of all define and then to make some valuable insights and get some valuable insights from it. So that's how we look at it.

Our, for us data is paramount. We want to give all the knobs and controls that can surface enough information for you to define the right objectives, you know, to meet, you know, what you want to do. Uh, that's how we look at it.

It's all about open interfaces on all data fronts, whether it's collection, storage, metering, visibility into volume, visibility into cost. All of that factors in when you start defining objectives. Absolutely.

Um, we only have a few minutes left. I want to, for our audience out there who's, who maybe wants to check this out, right? Get their hands dirty a little in it.

What, what is, how should they engage with AP Pico? What's the best way to, I'm assuming this platform is available now for people to use. Yeah.

Um, what, what's the best way to get engaged? Yeah. I mean, connect, uh, connect with us at, uh, you know, Aika io that's our main website.

You know, there is, uh, enough resources there for you to read about, you know, who we are, what we do, why we do things differently, you know, why does that matter? To, to, to why should that matter to a business? Uh, and also, you know, we, you can request a, a free trial from the company.

Um, you can request a demo from our teams and we can, you know, help you, uh, understand, you know, how this can really help your, your business. Um, and then we can get started on an engagement, if that looks interesting. You know, of course we, uh, we offer various form factors for our product.

And we are a fully, you know, SaaS platform as well. We can also run on-prem. So that's another unique aspect of who we are, is we are not just a pure SaaS play.

We can also function in on-prem environments. We do hybrid SaaS where storage can be managed by you, which is your data. So never leaves your cloud, but we run the compute for you and we manage all the, the compute, which, which is something that you may not want to be involved in.

So, very flexible models in terms of data consumption, um, uh, as well as, you know, how you consume our platform. Uh, so just reach out to us. You would love to, you know, showcase what we have, explain why some of these things are things that you should start thinking about.

Because there is a shift happening in enterprises around data consumption. There are more standardization of data collection models. Things like open this domain is becoming big, but you have to answer these questions around, great, I want to embrace open telemetry, new standard.

What happens to my old data? Right? How does that play into this world?

And those are things that, you know, we have thought through and, and we are really helping businesses think through these challenges because it's not enough to solve the problem for newer data you're generating. 9% of your data is still gonna be old, right? And if that doesn't work in this world, then you're in for trouble.

Uh, and, and that's something that we want you to think about. Something I tell people all the time, if only everything we did was a greenfield yes. Right?

And there wasn't any muddy brown fields for us to worry about, what a great world it would be, but it's not the world we live in, right? A small percentage of stuff is new. Everything else is, we have to keep the wheels on and the lights on.

So, I, I agree with you. Anyway, Ronan, we're about out time again for people who want to get more information. io, correct?

Yeah. A p ica A do io. Check it out.

Ronan, thanks for being our guest here on Text Drunk tv. Good luck at Apica. We hope to have you on Zoom, maybe with some more news.

Awesome. Uh, you know, look forward to, you know, further discussions and, and thanks for having me on your show today. A pleasure.

Thank you. I'm John, part A-C-P-T-O at Appe here on Tech Drunk tv. We're gonna take a break.

We'll be right back.