AWS Financial Services Symposium 2026 | Peter Sprenger, Splunk, a Cisco Company

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Peter Sprenger

Field CTO

Splunk, a Cisco company

play_circle_outline Powering Reliable AI with Timely Data: How Splunk’s Flexible Platform Drives Security, Observability, Operations, and Customer Experience

play_circle_outline Risk-Informed Enterprise Security: Virtual Mission Control, Real-Time Dashboards, and Fusion Centers

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Peter Sprenger, Splunk, a Cisco Company

Peter Sprenger

Field CTO Splunk, a Cisco company

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Rebecca Knight

>> Welcome back everyone to The Cube's coverage of the AWS Financial Services Symposium here in New York City. I'm your host, Rebecca Knight. I would like to welcome to the show, Peter Sprenger. He is field CTO at Splunk. Thank you so much for coming on the show.

Peter Sprenger

>> Thanks, Rebecca.

Rebecca Knight

>> Splunk has been a fixture in financial services for a long time, but its role has changed. Why don't you start by just describing what is Splunk and what you're focused on right now?

Peter Sprenger

>> No, it's a great question. I think Splunk, whenever I'll talk to people and try and understand their baseline, where they're coming from, I found that sometimes it's whatever they first saw Splunk doing and that could've been whatever job they had. With Splunk, in its essence, it's really a data platform. And with that, just like you can use building blocks when kids go and play, they can build whatever they want out of things. That can be good because people can build a lot of really cool things as they're thinking through it, but it also makes it harder to explain it. And so Splunk, at its essence, is a data platform, and building on that, people can use it for security, they can use it for observability, understand a bank's operations and how things are running and the customer experience. There's a whole bunch of different things they can do. When we look at AI, you really can't have a good AI program without a good data program. You want AI understanding what's happening, and if it's going to make important decisions, reading the newspaper from today and not a month ago. And we find that Splunk can really help financial institutions either jumpstart their AI program and then make it sustainable and being able to understand how it's doing. And then when we look at data coming into that data platform, making sure that's happening efficiently. So Splunk can do all of those things and it's really exciting.

Rebecca Knight

>> You mentioned security and observability. Let's first talk about security because this is a good example of where things get really critical. How does Splunk change what is possible in terms of a security team for a financial institution?

Peter Sprenger

>> I've done a lot of security work in financial institutions and we think... And I spent a lot of time as an infantry officer in the military. And as we fight threat actors, when we think about defending it... I mean, banks are under attack, constant attack. And these are extremely sophisticated nation state actors in some instances. Splunk really helps people work from a common operating picture and stop talking past each other with all the different systems that financial institutions have and focusing on the threat. It's thinking about security end-to-end and being able to do that. So Splunk comes into a couple different areas. One, you can take almost any data you have as long as it has a timestamp and you send that in and Splunk can help make sense of that. But then when we look at Splunk and say enterprise security, now you actually have mission control, almost like a virtual war room to be able to think through things. And now leaders are making decisions based on what they're seeing, data, and in real time. There are dashboards that are across video walls and say a command center or a fusion center thinking through. And now people are thinking about the threat and trying to reduce risk instead of really thinking about the data and the nuts and bolts. We want Splunk to be really that utility that people just use to be able to do their best work together. But at the end of the day, we want to understand risk, and you can't understand risk without good data.

Rebecca Knight

>> Right. Observability. How do you help them realize value?

Peter Sprenger

>> Yeah. And observability, I think, is great. That's the other area where we'll see maybe a security team owns Splunk. They purchased it and they use it. But we also see in the financial institutions and a lot of the banks are using it for observability, and that could be everything from understanding are my switches online or my routers or whatever it may be, or it can enable the business and it can say, what is the customer experience? How long is it taking them to access our mobile application? Or in the case of AI, we think about AI as this monolithic amazing thing, but it's technology that relies on a bunch of other technologies. And what if something important for AI isn't working? I mean, we would want to know.

Rebecca Knight

>> You need to know. Y need that data. Exactly. Let's look at a customer engagement.

Peter Sprenger

>> Sure.

Rebecca Knight

>> Walk us through how you work with customers and the impact that Splunk can have.

Peter Sprenger

>> Splunk's a part of Cisco now. It acquired a bit ago there. Now there are things where, say, if you have a piece of Cisco hardware, you can just install an application and it'll come right away. And then you have dashboards right away where you're getting great metrics coming out, largely very fast to set up. But we see customers and they bring Splunk data in and once that data's in... And that data can live in different places and you can even search it in different places. There are a lot of cool capabilities we have that have rolled out. But with that, they set up alerts. There's AI that can process things. You can even use agents to go and help you sift through that, really in that haystack finding the needle. Then you can use Splunk to go out and do something about it. It can orchestrate actions. There are different areas where you don't need a ton of coding skills. You can use AI to help build queries to help make sense of it. You can have dashboards that are showing things. That's really the journey I think, is first getting the data in, and there are things that you can download from an app store to do that very quickly. And then figuring out what's important, what do you want to help alert on and then what to do about those alerts. And it changes it from people thinking about what's going on to, what are we going to do about or where should we be investing? And those are the decisions that are really impactful and that just weren't available to people with technology we had just a few years ago even.

Rebecca Knight

>> One of the things that really stands out from what you're telling me here is that the emphasis is not just on getting more data but on having the right data in the right format. How do you help a firm get there and describe what that journey looks like from the initial deployment to having Splunk really be embedded.

Peter Sprenger

>> Yeah. That's where I think just looking at a couple of our customers that have great Splunk implementations, banks that have done a really good job in maxim, just really realizing the full value of their investment. They'll leverage the Splunk integrations that are prebuilt. They go put those in and the data comes in. It's in a format that makes sense. They're able to immediately start realizing value from that. Working with customers, what we've seen is there's a lot of value. When you look at the total cost of ownership and what they're getting, there's a lot of value in not having to recreate the wheel and rebuild those things. So they connect those. They then go and build dashboards to be able to monitor things, alerts, to be able to very quickly move forward and then understand what are their risk tolerances. What's the level of risk they want to accept or how quickly do they need to work through that? What we're seeing now in that journey is now customers are layering on AI. They're using Splunk agents to figure out, how can we move this faster? How can we do this more efficiently? And it's a really fun journey and we're nowhere near the end.

Rebecca Knight

>> Exciting times.

Peter Sprenger

>> It's just transformative. It's just fun.

Rebecca Knight

>> Peter, thank you so much for coming on The Cube.

Peter Sprenger

>> Thank you very much.

Rebecca Knight

>> I'm Rebecca Knight. Stay tuned for more of the Cube's coverage of the AWS Financial Services Symposium.

Peter Sprenger, Splunk, a Cisco Company

search

Rebecca Knight

>> Welcome back everyone to The Cube's coverage of the AWS Financial Services Symposium here in New York City. I'm your host, Rebecca Knight. I would like to welcome to the show, Peter Sprenger. He is field CTO at Splunk. Thank you so much for coming on the show.

Peter Sprenger

>> Thanks, Rebecca.

Rebecca Knight

>> Splunk has been a fixture in financial services for a long time, but its role has changed. Why don't you start by just describing what is Splunk and what you're focused on right now?

Peter Sprenger

>> No, it's a great question. I think Splunk, whenever I'll talk to people and try and understand their baseline, where they're coming from, I found that sometimes it's whatever they first saw Splunk doing and that could've been whatever job they had. With Splunk, in its essence, it's really a data platform. And with that, just like you can use building blocks when kids go and play, they can build whatever they want out of things. That can be good because people can build a lot of really cool things as they're thinking through it, but it also makes it harder to explain it. And so Splunk, at its essence, is a data platform, and building on that, people can use it for security, they can use it for observability, understand a bank's operations and how things are running and the customer experience. There's a whole bunch of different things they can do. When we look at AI, you really can't have a good AI program without a good data program. You want AI understanding what's happening, and if it's going to make important decisions, reading the newspaper from today and not a month ago. And we find that Splunk can really help financial institutions either jumpstart their AI program and then make it sustainable and being able to understand how it's doing. And then when we look at data coming into that data platform, making sure that's happening efficiently. So Splunk can do all of those things and it's really exciting.

Rebecca Knight

>> You mentioned security and observability. Let's first talk about security because this is a good example of where things get really critical. How does Splunk change what is possible in terms of a security team for a financial institution?

Peter Sprenger

>> I've done a lot of security work in financial institutions and we think... And I spent a lot of time as an infantry officer in the military. And as we fight threat actors, when we think about defending it... I mean, banks are under attack, constant attack. And these are extremely sophisticated nation state actors in some instances. Splunk really helps people work from a common operating picture and stop talking past each other with all the different systems that financial institutions have and focusing on the threat. It's thinking about security end-to-end and being able to do that. So Splunk comes into a couple different areas. One, you can take almost any data you have as long as it has a timestamp and you send that in and Splunk can help make sense of that. But then when we look at Splunk and say enterprise security, now you actually have mission control, almost like a virtual war room to be able to think through things. And now leaders are making decisions based on what they're seeing, data, and in real time. There are dashboards that are across video walls and say a command center or a fusion center thinking through. And now people are thinking about the threat and trying to reduce risk instead of really thinking about the data and the nuts and bolts. We want Splunk to be really that utility that people just use to be able to do their best work together. But at the end of the day, we want to understand risk, and you can't understand risk without good data.

Rebecca Knight

>> Right. Observability. How do you help them realize value?

Peter Sprenger

>> Yeah. And observability, I think, is great. That's the other area where we'll see maybe a security team owns Splunk. They purchased it and they use it. But we also see in the financial institutions and a lot of the banks are using it for observability, and that could be everything from understanding are my switches online or my routers or whatever it may be, or it can enable the business and it can say, what is the customer experience? How long is it taking them to access our mobile application? Or in the case of AI, we think about AI as this monolithic amazing thing, but it's technology that relies on a bunch of other technologies. And what if something important for AI isn't working? I mean, we would want to know.

Rebecca Knight

>> You need to know. Y need that data. Exactly. Let's look at a customer engagement.

Peter Sprenger

>> Sure.

Rebecca Knight

>> Walk us through how you work with customers and the impact that Splunk can have.

Peter Sprenger

>> Splunk's a part of Cisco now. It acquired a bit ago there. Now there are things where, say, if you have a piece of Cisco hardware, you can just install an application and it'll come right away. And then you have dashboards right away where you're getting great metrics coming out, largely very fast to set up. But we see customers and they bring Splunk data in and once that data's in... And that data can live in different places and you can even search it in different places. There are a lot of cool capabilities we have that have rolled out. But with that, they set up alerts. There's AI that can process things. You can even use agents to go and help you sift through that, really in that haystack finding the needle. Then you can use Splunk to go out and do something about it. It can orchestrate actions. There are different areas where you don't need a ton of coding skills. You can use AI to help build queries to help make sense of it. You can have dashboards that are showing things. That's really the journey I think, is first getting the data in, and there are things that you can download from an app store to do that very quickly. And then figuring out what's important, what do you want to help alert on and then what to do about those alerts. And it changes it from people thinking about what's going on to, what are we going to do about or where should we be investing? And those are the decisions that are really impactful and that just weren't available to people with technology we had just a few years ago even.

Rebecca Knight

>> One of the things that really stands out from what you're telling me here is that the emphasis is not just on getting more data but on having the right data in the right format. How do you help a firm get there and describe what that journey looks like from the initial deployment to having Splunk really be embedded.

Peter Sprenger

>> Yeah. That's where I think just looking at a couple of our customers that have great Splunk implementations, banks that have done a really good job in maxim, just really realizing the full value of their investment. They'll leverage the Splunk integrations that are prebuilt. They go put those in and the data comes in. It's in a format that makes sense. They're able to immediately start realizing value from that. Working with customers, what we've seen is there's a lot of value. When you look at the total cost of ownership and what they're getting, there's a lot of value in not having to recreate the wheel and rebuild those things. So they connect those. They then go and build dashboards to be able to monitor things, alerts, to be able to very quickly move forward and then understand what are their risk tolerances. What's the level of risk they want to accept or how quickly do they need to work through that? What we're seeing now in that journey is now customers are layering on AI. They're using Splunk agents to figure out, how can we move this faster? How can we do this more efficiently? And it's a really fun journey and we're nowhere near the end.

Rebecca Knight

>> Exciting times.

Peter Sprenger

>> It's just transformative. It's just fun.

Rebecca Knight

>> Peter, thank you so much for coming on The Cube.

Peter Sprenger

>> Thank you very much.

Rebecca Knight

>> I'm Rebecca Knight. Stay tuned for more of the Cube's coverage of the AWS Financial Services Symposium.