Our “Pepperdata Profiles” series shines a light on our talented individuals and explores employee experiences. This month, we talked with Kirk Lewis, a Pepperdata field engineer. Kirk discussed what is unique about the Pepperdata product, and he explained how Pepperdata helps clients make sense of performance data.

Hey, Kirk. Let’s start at the beginning. How did your journey in the IT industry begin?

Kirk
I was an Intelligence Analyst in the Air Force. We used a lot of high-end systems to accomplish what we were doing. I became sort of the “before you call IT, call Kirk” guy. Then, after the military, I decided just to focus on IT as a career. From there, I spent time as a defense contractor, and then the bulk of my career was spent at American Express and in IBM’s financial services space. My primary client with IBM was also American Express (AmEx).

That’s a cool career arc. What did you do for AmEx?

My work centered around very large distributed systems, systems administration, systems architecture, storage administration, network administration, those sorts of things. It’s all the things you need to be able to move bits around and crunch data on a large scale. Because before it was big data, it was just sort of high-performance computing distributed systems; basically, how do you get multiple computers to work on one job? I spent over a decade with the technology division of AmEx.

Then, after AmEx, I moved to California to take a job with Jabil who was launching a division focused on creating and selling big data appliances. They had very large clients. A lot of cloud vendors bought machines from this company, and I was brought in as a design and automation architect.

That was fun while it lasted. But no one bought big data appliances, so it ramped up quickly, but died quickly, as well. I spent about 19 months there before I saw the writing on the wall and realized I was in a sales division that wasn’t selling anything! So I started looking around. And by that point, I was in the blessed position to be able to choose from a few different positions.

And this is when you found Pepperdata, right?

That’s right. It became a high priority for me to find something that I thought would actually be useful, especially after that last experience of making a bunch of things that people didn’t buy. Pepperdata ticked off all the boxes in that regard.

At that point, I talked to Sean Suchter and Chad Carson (the co-founders), and I also did a bunch of reading, watching YouTube videos, and learning whatever I could find about Pepperdata.

And I realized that the big data performance monitoring technology was something I would have loved to have had in my previous roles, as I was managing these systems and trying to keep the lights on. That’s really what brought me in the door.

So you discovered Pepperdata, learned about it, and realized how useful it could have been in your previous work?

That’s right. And from then on, I was glad to be working with technology that I knew could help people. That’s sort of been the story from day one: I know this stuff. I know it helps people, and that we need to get it in front of people and convince them.

That’s really cool. What was your role at Pepperdata at the beginning?

Well, it’s been four, five years now since I began working at Pepperdata. Alex Pierce and I started as sales engineers, and we were the only ones in the department. At one point, Alex had his calendar booked out for the next 90 days, so I came in to help. My job, day one, was to learn how to host demos and perform the POC process as fast as I could. Our process starts with a demo; followed by the sessions where we help people understand what Pepperdata is, how to use it, what the value is; and then you ask them to become a user.

I shadowed Alex for a few calls, and when I had gotten about 40% up to speed, they went, “Alright, now you’re going to do a demo for the whole company. And the day after that, you’re going to do a demo for a customer because we need you to jump in.”

It was basically trial by fire, but I managed to develop my own approach. What I did was try to build some automation around the steps to install the software. How can I carry out these steps more efficiently? How can I get more comfortable with the problems that I might see on the way into these customer engagements? And how can I get to a point where I could confidently get on the phone with folks and install the software and prove the value? That sort of thing.

How does that differ from your day-to-day work now?

For me, there’s a core set of tasks that aren’t all that different, but we have changed. I mean, the product has evolved a lot: Before, we only had Pepperdata—when it was just one piece of software. Now we’ve got a range of products, from Application Spotlight to Capacity Optimizer, and all of these various use cases that we’re looking to tackle.

The day-to-day role has also morphed a bit. So, one of the things that I really like about Pepperdata that I hadn’t experienced before is that I get to talk to folks from different fields, like marketing and engineering. Often when you’re in a very large organization, you don’t get to talk to those people. You just get the product after it’s fully baked, and you just run it with what you’ve got.

But now, I interface with both the marketing team and the product management team. With marketing, we get to work on things like messaging: why we’re saying what we’re saying, and how we say it. For product management, I get to tell the team, “Hey, I talked to this customer, and he said it would be great if we had a button here that lets them do X.” And then I talk to Jeremy Hay, our lead guy on the UI side, we discuss it and, if it makes sense, we do it.

I get to be involved in the areas that I’m interested in, which is pretty much the whole thing as Pepperdata exists today. It’s great to have a hand in what the product is becoming at this stage.

What do you consider as the most unique aspect of the Pepperdata suite?

Pepperdata has always had what I consider to be the richest set of performance data of any cloud data monitoring product.

The use cases we’re servicing are mostly questions related to app performance data. And that sounds simple enough, but really, that begs a bunch of more questions that line up with our products. “Who are you? Are you a developer? Are you an IT Ops guy? Are you the CTO? Are you the capacity planner?”

When you look at who’s asking those questions, it starts to line up with the products we have: Application Spotlight for developers, Query Spotlight for database folks, Platform Spotlight for the platform folks, and Streaming Spotlight for the people who are in the big data pipeline, architecture, and data management space.

So our job as a product is to figure out how to answer their questions as quickly as possible. We know we have the performance data to do it, but most times if I sit someone in front of that data, they’re just going to be overwhelmed by it. Sometimes, we come across engineering people and teams that can jump right into the app performance data they have and answer those questions for themselves, but they’re the rare birds. The rest of the market, however, needs it explained. They want to turn Pepperdata on and get, “Hey, this application is messed up. Here’s how you fix it.”

They don’t care about the data as much as they care about the answer to the questions that they’re asking. We give them that answer and that satisfaction.

So Pepperdata succeeds by responding to the singular, granular needs of a given customer?

Precisely. This is sort of the problem when you have big data: How do you make sense of it?

A lot of this spurred from the whole data science movement of people starting to collect all data, right? They said, “Oh, you’ve got to collect everything.” Then you say, “Okay, great.”

So then you have a performance data swamp, or lake or warehouse, that receives and stores all that. And then the next big question is, “Now, what do I do with all this? Don’t shoot me a Google Sheet with 2000 lines and numbers and expect me to make a decision for my business unit based on that. I need to understand the insights.”

When you look at the space that we play in, there’s no shortage of folks who will say, “We can show you everything.” But here, at Pepperdata, we’re answering, “Can you show me what I’m looking for?” Pepperdata makes a big difference in making sure people get the insights they need from the mountain of data that they have.

Last question: The top two pain points that the market has, especially in the cloud, are complexity and unexpected costs. Do you think Pepperdata is uniquely positioned to help with those challenges?

Yes. Part of the thing that allows us to work well in that space is the underlying approach of collecting everything first. That allows us to be pretty flexible.

When we first started hearing from these large enterprises that the cloud was going to be something we need to address, we created cloud migration reports to help people move from on-prem to the cloud. That data science exercise of building those reports didn’t require us to go grab any more app performance data from these environments because we already had it.

So when we’re looking at how flexible we need to be relative to the cloud, we realized what’s happening wasn’t really cloud migration but cloud adoption. People aren’t migrating for the most part to the cloud; they’re adopting components of the cloud within their data architecture. That told us we’ve still got to stay good at the on-prem stuff, but that we also have to stitch it together with what’s happening in the cloud.

So a client might say, “I’m going to use Cloudera in my data center, but I’m going to use a little bit of Snowflake in the cloud. And I’m going to use a little bit of EMR here, a bit of Google Data proc there, and a little bit of Microsoft over here.”

Since we’re an independent third-party solution, we can say, “Alright, I can monitor and see the performance data for all of those elements and pull it all back so that your chargeback report is still comprehensive. You don’t need to get Amazon’s, or Microsoft’s, or Google’s chargeback report and try to make sense of that. We can do that for you.” That’s because we sit a level above all of those things. We are, for all intents and purposes, the umbrella cloud data monitoring solution.

Read more profiles on the people of Pepperdata.

The views expressed on this blog are those of the author and do not necessarily reflect the views of Pepperdata. Any solutions offered by the author are environment-specific and not part of the commercial solutions or support offered by Pepperdata.