Jeff Collins Podcast Transcript
Jeff Collins joins host Brian Thomas on The Digital Executive Podcast.
Welcome to Coruzant Technologies, home of the Digital Executive Podcast.
Brian Thomas: Welcome to the Digital Executive. Today’s guest is Jeff Collins. Jeff Collins, CEO of WanAware, has over 25 years of experience driving profitable growth by transforming brands, companies and cultures. He is passionate about leading disruption through insight driven strategies that activate brands and companies, attract customers, inspire stakeholders and create community.
In 2020, Jeff began developing WanAware after recognizing the need for an effective IT observability solution due to the limitation of outdated legacy tools and antiquated models. He also holds leadership positions at 21Packets as the chairman and Lightstream as the chief strategy officer. Jeff serves on the boards of multiple technology companies, contributing his expertise in cybersecurity, AI, networking, and data transformation.
Well, good afternoon, Jeff. Welcome to the show.
Jeff Collins: Thanks, Brian. Thanks for having me.
Brian Thomas: Absolutely. I appreciate you making the time. I know we do a lot of podcasts during the week and getting to see and hear everybody virtually, of course, across the globe. And I know today you’re hailing out of that great place of Boulder, Colorado.
I’m just an hour ahead of you, but appreciate it. Let’s just jump right in, Jeff. With over 25 years of experience in transforming brands and companies, what pivotal moments have shaped your approach to driving profitable growth?
Jeff Collins: That’s a great question, Brian. I mean, when I look back in my history, you know, starting in the late 90s and technology, you know, we’ve had so many points where the industry has had transformative moments.
When I think about the late 90s, we had things like, you know, VM were creating a hypervisor and doing things like that and being able to change the way that we Deploy servers and services the way that the industry does that and each one of those paradigm shifts that we’ve had It’s created great opportunities for me throughout my career.
And as I’ve looked at each one of those, those pivotal moments have allowed me to kind of think about things differently. Because every time somebody goes out and does something transformational or transformative, it creates opportunities. So in the late 90s, when that happened, we had a whole bunch of other things that started changing.
Security started changing, and I’m sure Everybody that’s listening remembers how security requirements changed so much at that point in time. We stopped securing things like a castle when we started thinking about, well, how do we secure things that might be moving around and might be changing? You know, our, our security isn’t dedicated just to this room inside of our building.
Where we have our servers and all of our infrastructure. So all those things have kind of created those paradigm shifts. And then leveraging that has allowed me to create that continuous profitable growth in my businesses and in all of the companies and environments that I’ve been in over that 25 years.
So it’s been really exciting for me. And, you know, Post that point, we’ve had all kinds of other events like that that have happened. You know, we’ve had crises that have happened from a global economic perspective, and those have created opportunities. You know, when we have crisis, it changes the way people buy technologies and it Changes the way that people leverage technology and those things have allowed me to think about ways to deploy things differently and build technologies differently.
You know, today we think about from a technology perspective, there’s so many different ways of deploying technology and deploying technology and means that aren’t so monolithic. Those types of shifts have allowed those to grow so much and allowed our businesses to grow accordingly. So really those are kind of some of the big pivotal moments I would say over the last 25 years that have changed things for me and have driven that profitable growth of my businesses.
Brian Thomas: That’s awesome. There’s always something going on, especially in the tech world, as you know, it’s like leapfrogging, especially the last, just gosh, a couple of years during COVID and AI and everything else, but really do appreciate that. Whether it’s a transformational change or there’s a challenge, whatever it is, you can always expect change to be constant.
So I appreciate that. And Jeff, in 2020, you founded WhenAware, To address the limitations of legacy I. T. Tools. Can you elaborate on the specific challenges you identified and how when a wears intelligent observability platform addresses them?
Jeff Collins: Yeah, that’s a great question. So when I started when aware, I actually built it based on a lot of those things that I had seen, you know, let’s call it in the previous 20 years, you know, when we think about observability and knowing about what is going on inside of an environment.
That’s really hard for most companies, most companies that exist today, regardless of if you’re a small company, maybe a five people or you’re a really big company, and maybe you have hundreds of thousands. Understanding what’s going on with your technology stack is hard. There’s lots of technologies out there to do that.
A lot of them are hard to implement. A lot of them are hard to build. They’re hard to integrate. They cost a ton of money. And in most regards, they don’t do what they say they’re supposed to do. And so that’s one of the things that over that, you know, let’s call it a little over 20 year period up until 2020.
Those were the things that I saw as well as I went out and bought these same tools that really everybody’s using today. They were really difficult. And so when I built WanAware, it was originally built to solve those problems for me. I originally built the product to help us internally with some of our other companies.
We never actually thought we were going to actually build a product that went to market, but after building it internally and utilizing it and seeing the benefits that we had, inevitably some of our really large customers found out about it. And they heard about the technology we were using internally, and they were seeing the benefit that we had.
And some of our engineers, as engineers often do, and I’m sure everybody who’s listening to this right now knows that this happens. You know, engineers get excited about something, and then they start telling people, Hey, we have this cool thing, let me show it to you. And with that, our big customers started seeing that.
And then those customers came to us and said, Hey, we would really like to buy that thing. Well, we never had built it to sell to customers, and so what we ended up having to do is we ended up taking that, certainly building it more capable, because we built it for just one customer, us, and so we had to build scale into it and build it more capable.
And then as we did that, you know, our customers gave us a lot of feedback on what they wanted to see and what types of benefits and how they wanted to understand observability, whether that’s performance or availability or security, observability, and really building that out to address those issues and to be able to provide them insight around their environments.
One of the things that one of our really large customers gave us was they told us that observability platforms, well, You know, there’s lots of them out there. One of the things that’s really hard is most of those observability platforms don’t understand the assets that the customer has and think of assets as I.
T. assets or O. T. or I. O. T. or whatever it might be, and that was one of the things that they always had difficulty with is, you know, understanding what they have feeding that into the plot. form and as their environments change, be able to do those things. And so that was one of the great things we got from one of our large customers.
That’s one of the things that’s really helped make the intelligent observability platform exist is the fact that we understand what customers have those known and those unknown assets. And we’re able to pull those in, be able to deal with those, and then ultimately give that actionable intelligence that customers look for so that they can ensure that their environment’s operational at scale.
Regardless of their size and be able to remediate that as necessary and applicable. Those are kind of some of the big things that we saw as we built this platform and dealt with kind of some of those limitations.
Brian Thomas: Thank you. That’s awesome. I love the story. You built it for yourself and the word got out and I just love how that works.
Something that works really well. Obviously, you know, your best sales channel is word of mouth. So love the story and I love what you’re doing because we all know. Anything that’s connected to the network. We see, gosh, that is such a mess. Why do we still have that legacy equipment? Right? So appreciate that.
And Jeff, my next question for you, WanAware platform integrates AI machine learning and advanced graph database infrastructure, can you discuss how these technologies work together to identify patterns and mitigate risks within it ecosystems?
Jeff Collins: Yeah, that’s another great question. AI is the buzz today.
All of us hear about it all the time. You know, if you go to CNN or whatever news source you want to go to, there’s three topics about AI and all those things going on. When we started with this back in 2020, AI really wasn’t a thing at that point in time. It wasn’t in the mainstream. So when we started building this, you know, we were building it with very rudimentary versions of what we see today.
You know, we didn’t have things like open AI. We didn’t have things like Google’s Gemini or, or any of those types of things. And so when we built this platform, we had to start out. like most of us had prior to let’s call it 18 or 24 months ago. And so when we did that, the good thing was we focused a lot on making sure that the blocking and tackling were done effectively.
And I always bring that up to people when they talk about our platform and why it works because oftentimes we get that from people is like, well, Why does your platform work and other people’s don’t? Well, it’s not because, you know, we created something that was absolutely amazing and we did at the end of the day.
But the reality is we focused on the blocking and tackling doing the things, you know, keeping the house in order. So when we think about AI and machine learning, the reason why those work for us is because we made sure our data model was really good. The data that we’re bringing in is clear. It’s concise.
It doesn’t have false positives. Those are things that are important. And when we do get things like a false positive in the environment, because sometimes you will get an event or an alert that is in that manner, because we’re able to contextualize that data and we understand dependencies and interdependencies, You know that asset piece we talked about in the last question that’s allowed us to bring in a lot of capability to understand what customers are truly doing with their environment and to be able to make intelligent decisions and perform what we call intelligent observability.
But really, what that is, is knowing what a customer is doing. Customers today deal with that with people. You know, they hire really great heroes, and whether those heroes exist in their level one, level two, or level three support or engineering desks, those people are what find those anomalies. And they understand if those anomalies actually affect their environment.
Well, what we did is by using all these pieces together, AI, machine learning, our algorithms that we’ve built, as well as a robust rules engine, What that’s allowed us to do is leverage technology to pick up a lot of those analysis components so that customers don’t have to use their frontline people, their level one or level two people, to find out this is actually a false positive or it’s something that doesn’t exist in their environment.
And that’s one of the big things that’s really helped. Now when we think about risks, we also can use that same paradigm to understand risk. You know, risk, if we talk from a security perspective, might be a vulnerability. And those risks are all about the context of how a customer is using an environment.
So if I go in and I understand that a customer is using a certain version of Apache, great. There may be a vulnerability with that. But the reality is, is based on compensating controls, or based on a configuration that a customer may have, they may be mitigating that inside of their environment automatically.
Well, Our technology, while we may go in and we may identify that that’s a vulnerability because of one data point, i. e. a specific Apache version, our ability to pull in that other information allows us to understand that that’s actually a false positive, there’s a compensating control, and we can clearly articulate that.
That’s kind of really how we do that by leveraging those core technologies and by tying all those together to make those intelligent decisions and identify those patterns or mitigate those risks.
Brian Thomas: Thank you, Jeff. That’s amazing. You know, just to highlight some of the things out of our conversation here.
You absolutely leverage some of the latest. You built maybe some proprietary algorithms for your platform. But what really stood out to me is you did the again, you call it block and tackling and you know your fundamentals for this. And when you get that right, you get it right with the customer. So I appreciate your insights there.
And then Jeff, the last question of the day looking ahead. What are your aspirations for WanAware’s role in the future of IT infrastructure management, and how do you envision the evolution of observability solutions in the next decade?
Jeff Collins: Yeah, this is a great question. You know, when I think about where we’re going, and the aspirations we have, I mean, our aspirations are really to make technology better tomorrow than it is today.
And, you know, I think from a technology company perspective, we all hear that. I think every technology company out there probably has a similar aspiration. One of the things that we do a little bit differently within that is Every single product we build, every single component we build inside of our platforms, we ensure that every person inside of our company thinks about that every single day.
You know, when we create a feature, or we create an offering, or we create anything, we focus a lot on making sure that we’re making the world better. And that we’re not building technology for technology’s sake, but that we’re building it to help companies be able to find out what’s going on inside of their environment faster.
You know, when we think about things like a blast radius, that’s one of the big things that customers deal with, you know, when we talk to our telecom customers or we talk to our large manufacturers who have tremendous amounts of IOT and OT devices within their environments. If one of those goes down, they need to understand that blast radius.
Well, when we think about the future, Technology is going to get much more complex than it is today. In the last five years, we’ve seen that. You know, if you go back five years, most manufacturers didn’t have intelligent manufacturing platforms leveraging sensors throughout and leveraging all these capabilities that they now have today.
Well, each one of those, if one of those fails, that can affect a lot of things within their environment. That blast radius gets really big. And so when we think about our aspirations in the future, it’s really to be able to help companies understand that make better decisions. And if there is a problem or when there’s a problem is probably what I should say when those things happen.
You’re able to find that in seconds or minutes instead of hours or days and I think that’s the big piece. Now when I think about the next part of that question, which is, you know, how do you envision this evolution of observability, observability is going to change a ton. You know, today, we, like a lot of companies within our space, deploy our technology as SaaS, and we provide people a portal, and we provide them a dashboard, and we provide them all these ways that they can get access to this data, or they can feed it downstream into one of their existing systems.
The reality is, I think the evolution of this is going to change a lot. When we think about AI and we think about AI and things like that, companies as they adopt more and more of that, they’re going to be leveraging those tool sets or those platforms to get the information that they’re looking for. You know, you’re going to go and you’re going to ask, you know, we’ll pick OpenAI.
You’re going to go in and tell OpenAI, hey, I would like to know, you know, what are my risks within this area, corporate wide. And that’s going to go out and we’re going to become one solution within that umbrella where we’re able to provide observability. Again, you want to minimize those false positives.
You want to minimize those risks that an observability tool can give. But the reality is, is that that’s where things will go. And I think from a timing perspective, we’re going to see that pretty quickly. The scale and cadence of what’s been going on from an AI perspective and the ability to provide actionable benefit for companies has been growing at a rapid pace.
And, you know, probably within the next, let’s call it six months, I think those things will happen. We’ve spent a lot of time on making sure that our platform becomes a great conduit where companies can leverage that they can leverage whatever LLM they decide they want to have or whatever generative component or whatever it may be, and they can leverage those to make those decisions.
And I think, you know, that’s going to be the huge evolution. As well as the really kind of the congruence of observability moving more out of the I. T. space and into technology holistically. I think that’s going to be very important for companies.
Brian Thomas: Thank you. And I really do appreciate that. We talk a lot about emerging tech and where it’s going for the future.
And today you provided some great gems around the evolution of observability and some of those solutions. We do know, as we mentioned earlier, change is constant. Technology is leapfrogging faster than we’ve ever seen in the last 20 years, as you know. So I appreciate that. And Jeff, it was certainly a pleasure having you on today, and I look forward to speaking with you real soon.
Jeff Collins: Sounds great. Thanks so much for having me, Brian. This was a great session. Thank you.
Brian Thomas: Bye for now.
Jeff Collins Podcast Transcript. Listen to the audio on the guest’s Podcast Page.
