(So you can skip ahead, if you want.)

00:00 Introduction and Overview
03:40 Evolution of Network Automation
05:59 From Automation to Orchestration
07:40 Breaking Down Team Silos
09:50 AI in Infrastructure: Hype vs Reality
14:33 Balancing Innovation and Reliability
16:08 Underestimating Infrastructure Complexity
18:32 Future of Infrastructure Operations
21:48 Itential Platform and Pragmatic Solutions

Neil Hughes • 00:01

If you spend your days keeping complex infrastructure alive, you already know the gap between conference lines and real operations is incredibly wide, frustrating, and often painful. And today’s conversation is firmly on the practical side of that divide because I’m joined by Peter Sprygada and someone who has spent more than a decade deep in the weeds of enterprise networking, automation and multi-cloud environments. Yep, he’s got a few war stories of his time out there in the field and lots of experience because he’s worked across those traditional networks, cloud platforms and now modern automation stacks. So, yeah, he has the scars and lessons that only come from running infrastructure at scale. So, today is not a discussion about shiny tools or overnight transformations. I wouldn’t do that to you. It’s more of a grounded look at how automation evolved from scripts to orchestration, and where AI genuinely helps today.

Neil Hughes • 01:06

Yeah, we are going to talk a little bit about AI, and where expectations are getting ahead of operational reality. And I’m sure you’ve got experience of that too. And we’ll also dig into the hard parts most teams underestimate. Yep, complexity, governance, and reliability, all that unglamorous work that actually keeps systems running. So, if you’re responsible for bridging legacy systems with newer platforms, or if you’re tired of companies promising miracles without acknowledging constraints, hopefully, this conversation should feel refreshingly familiar, but give you a few actionable takeaways and solutions too, and lots to think about. Now, before we begin today’s interview, and there’s some great insights in that, I just want to give a special mention to my friends at Denodo who are passionate about the future and logical data management and Agentic AI, because everywhere you look, Agentic AI is undoubtedly the next big shift. But here’s the truth: it can’t operate on messy, inconsistent, or siloed information.

Neil Hughes • 02:08

With Denodo, you can create a unified govern layer that connects data across your lake house warehouses, across your apps and clouds instantly and without duplication. This means stronger AI governance, faster lake house acceleration, and reusable data products that your teams can trust. So, if you want AI that doesn’t just automate but operates, start with logical data management@denodo.com . But enough from me. Let me officially introduce you to Peter now. So, a massive warm welcome to the show. Can you tell everyone listening a little about who you are and what you do?

Peter Sprygada • 02:46

Yeah, so 1st of all, thanks for having me. My name is Peter Spragata. I currently serve as the chief architect at Atential, which is Is a fun and fancy title. That means I do all of the work in the weeds in terms of really just kind of looking at the product and trying to hypothesize where the product needs to go over the next three, five, seven months.

Neil Hughes • 03:09

Wow. You wear a lot of hats there. And before you came on the podcast today, I was doing a little research on you. And I’ll quickly learn that you’ve worked across enterprise networks, cloud environments, and platform engineering from Red Hat to Pureport and obviously now in Intential. So when you look back, how has the conversation around network automation changed over the last decade? And in particular, the last couple of years, I would imagine. And what problems were organizations originally trying to solve?

Neil Hughes • 03:40

Has things changed that much in the last 10 years in your career?

Peter Sprygada • 03:44

Yeah, wow. Yeah, they’ve changed a ton. You know, I trace my automation roots back to certainly in the networking space to 2011, 2012. So, you know, I’ve been doing this a long time. And, you know, when we 1st got started in this, It was really more about, you know, just trying to find a more efficient way to do your job. You know, I always love to tell the story as a network engineer.

Peter Sprygada • 04:12

You know, you 1st get started in the networking industry and you get really excited for configuring your 1st switch or router. And you turn up an interface or a routing protocol, whatever it is that you end up doing. And you’re like, this is really fun. This is cool. I enjoy this. Once you’ve done that, you know, 643 million times, you’re like, okay, typing these CLI commands isn’t as much fun as it used to be. And it’s detracting from what I really enjoy about network engineering.

Peter Sprygada • 04:39

And that’s really where created kind of that foundation of automation. And it was really to try and solve some of that repetitiveness that existed. From that point forward, over the course of that next 10 to 15 years, it really evolved substantially from kind of being a way to optimize your job to really an industry all of its own to the point where, you know, even in the last couple of years, as you mentioned, it’s changed substantially just in the last two years, as we’ve really started to look at how organizations can leverage automation more as a strategic advantage versus just simply a way to optimize the infrastructure. And now with, and I’m sure we’ll get into the dreaded AI conversation at some point. And now with AI, it’s poised for an even more significant growth curve as we go forward.

Neil Hughes • 05:32

Yeah, I’m sure we will get to AI. It’s a tech podcast. It’s almost against the law not to mention AI now. But of course, many teams started with scripts and then task automation, often with the best intentions. But at what point does automation stop being enough? And what signals tell an organization that, hey, it now needs orchestration rather than just even more isolated workflows?

Peter Sprygada • 05:59

Yeah, you know what? You just touched on the key word, even in the question, and that is isolated. You know, automation works in. You know, islands of expertise, right? The core networking team, the edge compute team, the security firewall team, whoever you are and however you do it, automation is really optimized to allow really smart people in a very specific domain optimize how they do things. What automation is not good at is it’s not good at fundamentally understanding end-to-end systems and flows that are attempting to align with the actual needs of the business, right? And that’s where that conversation, that’s that’s a signal that you kind of talked about saying this is when we need to start thinking about orchestration is how do I take and leverage all of the automation that’s happening in each of these isolated domains and now build something horizontally across all of that that I can align with my company’s initiatives, I can align with my business processes and ultimately streamline just functionally how the organization works.

Peter Sprygada • 07:08

And that’s really, I think, where what the big signal is.

Neil Hughes • 07:12

And I was recently reading that you often describe infrastructure as something that should support conversations between teams, tools, and systems, which is incredibly refreshing to hear. So, how does an orchestration layer change the way that a network, cloud, and application teams actually work together day to day and stop turning into one of those Spider-Man memes where they’re all pointing at each other and blaming each other for when something goes down?

Peter Sprygada • 07:40

Yeah. So, you know, it’s interesting, you know, having had that, you know, and kind of we talked about it at the intro, you know, having had the opportunity in my career to kind of work across many of these different domains, you know, in cloud, in network, even to a little smaller extent, even in compute and application. One of the things that has always fascinated me is that, you know, if I look at what the network team is doing and I look at what the cloud team is doing, and when it comes to, you know, how we interconnect these systems, in a lot of cases, they’re doing, if not the same thing, very similar things. What’s different is the vernacular they use, right? The way that they talk about things, the names they give to things, the tools that they use, but generally they’re all kind of doing the same thing. So, with the backdrop of that, we start to realize that an orchestration layer can start to become a way that these disseparate teams can really start to find a common way to communicate how they ultimately need to go about achieving whatever it is that they’re trying to achieve. And that’s really, I think, one of the big wins when we look at how the orchestration layer can ultimately help an organization.

Peter Sprygada • 09:01

Because it finally allows the line of business owner to conversate with the cloud team, to be conversant with the network team, and come to a common understanding about how the infrastructure ultimately needs to be provisioned, evolved, optimized, et cetera, to support the organization.

Neil Hughes • 09:23

And of course, we did mention AI a moment ago. And before you came on the podcast, I was going through some of your blogs. I know there numerous blogs out on AI and AI ops. So I know you’re reluctantly passionate about this too. So AI has now entered the infrastructure stack, often wrapped in big promises. From your perspective, where does AI genuinely help infrastructure operations today? And where do you see hype getting ahead of operational reality?

Neil Hughes • 09:50

There’s probably quite a few myths and misconceptions that you’ve seen out there, but what are you seeing?

Peter Sprygada • 09:56

There is. There is no question. You know, there’s a few points in here. First and foremost, I talk a lot about, you know, AI, you know, when we bring AI into this conversation, we always have to step back for just a moment. And, you know, as you said, right, the hype cycle is off the charts right now. And frightfully so. It’s revolutionary technology.

Peter Sprygada • 10:17

It’s transformative technology, the likes that most of us, myself included, have never seen before in our careers. But at the end of the day, if we can detach from the hype for just a moment and understand that AI is just a technology tool, and we have lots of technology tools. It’s a very powerful tool, but it is still a tool nonetheless. And we have to start by recognizing that, is that AI is a tool and we need to apply it as such and we need to apply rigor around it as such. AI is not something that is going to, you know, day one, fundamentally change everything we do. Now, it may ultimately get there, but it’s not, you know, we need to recognize it for what it is. The 2nd thing about AI that I really find fascinating in my own personal journey was that when AI 1st burst onto the scene, I, like many other, you know, old school engineers, looked at the technology and I said, uh-uh, no way.

Peter Sprygada • 11:15

AI is not coming into this domain. I’m not leveraging AI. I understand this. I know how to do this. I do not need AI. And once I kind of got over some of those initial hurdles, some of those initial fears, and really started to think about AI as a tool and what it could do for my infrastructure, that’s when it really started to open the floodgates for me personally. And kind of going to the comment around leveraging it for infrastructure operations today, what I see evolving is very similar to what we saw in the automation space, going all the way back to the beginning of this conversation.

Peter Sprygada • 11:51

When automation 1st started in the industry, We heard a lot of the same talking points being parroted by networking engineers and even infrastructure and operations teams as well. It’s like, look, automation is here to take my job. It can’t do things better. It doesn’t understand things. And the list just went on and on and on. And over time, as we got more comfortable with the technology and we got over a lot of those fear biases, we understood that, hey, it’s a tool.

Peter Sprygada • 12:20

It’s a tool I can leverage. It’s a tool that can actually help me in my day-to-day operations if I leverage it in that way. And I think that AI is going to take a very similar path. The trajectory is going to be very different, right? It’s going to happen much faster, but it’s going to take a very similar trajectory, meaning that we will initially leverage AI for a lot of operational stuff, but over time it will evolve to take on other things like configuration, management, you know, of the infrastructure.

Neil Hughes • 12:49

I just want to give a big thank you to my sponsor who is supporting every show, every episode across the Tech Talks network this month. And this month, I’m proud to be partnering with Alcor. And anyone who’s tried to scale an engineering team across borders, they will know 1st hand how messy it can get. Because they deal with endless providers, then there’s confusing rules to deal with in each and every region, and fees that always seem to surface at the last minute. Now, Alcor, they solve that by acting as a partner rather than just an intermediary. And they focus on tech teams that expand in Eastern Europe and Latin America, and they bring employer of record services together with recruiting. So, essentially, they help you pick the right country, source the right engineers, and assess them properly, and then get them active for you and your company within days.

Neil Hughes • 13:43

And one of the things that stands out for me is the financial transparency. Around 85% of what you pay goes directly to your engineers. Their fee goes down as your team grows. And if you ever wanted to bring your team in-house, you do so with no exit costs. And you can find out more by simply going to alcor.com/slash podcast or follow the link in the show notes below. And inside any IT department, I think that constant battle with reliability and innovation are always framed as almost opposing forces, especially in infrastructure decisions. So, based on what you’ve seen in the field, how can organizations better modernize their operational stack, do some of that cool stuff that they’ve been wanting to do without introducing that unnecessary risk or disruption?

Neil Hughes • 14:33

I mean, you mentioned a few moments ago when you 1st heard about AI, I’m not having this in here. So, what are you seeing here?

Peter Sprygada • 14:41

I think, yeah, I think that’s right. And it kind of goes back, you know, goes to that concept of treating AI, you know, with the respect it needs and also understanding that it is just a tool. You know, we wouldn’t take, or at least we shouldn’t take, right, a script that a junior engineer just wrote and put it into the critical path of how we operate the infrastructure, you know, without vetting it, without. Putting some type of governance around it without making sure it’s got logging, without making sure that it’s secure, right? These are all things that we do today almost as 2nd nature, at least we should be doing almost as 2nd nature today as it relates to automation. And I think AI is very, very similar, right? We need to recognize that all the boring stuff, if you like, we always internally at attention, we like to talk about this as the boring stuff, right?

Peter Sprygada • 15:28

But the boring stuff is the critical stuff that allows you to go to sleep at night. It’s the fact that it’s, I know it’s secure. I know it’s got guardrails. I know that I’ve got governance wrapped around it. I know that I’ve got logging so that when things go off the rail, and they will, we all have been doing this long enough to know I don’t care what the technology is, it will go off the rails at some point for some set of use cases. We’ve got the right things in place that allow us to understand what happened, remediate it, get back to a normalized operational model, and then move forward by making changes so that it doesn’t happen again. And I think that’s really kind of the key to how we ultimately operationalize this type of technology.

Neil Hughes • 16:08

And if we look at the full operational stack here from intent to execution to assurance, what do you think most IT leaders are guilty of still underestimating about running modern infrastructure at scale? Again, you must see a lot of mistakes being made here, but what are the big things that people are still underestimating?

Peter Sprygada • 16:27

I think, you know, if I could distill this down to one point, I mean, I could come up with many, many points about it, but if I were to distill it down to one point, is I think that IT leaders still underestimate the level of complexity that is dealt with on a day-to-day basis by engineering teams. The reality is that when you look at full, to your point, the full operational stack, right? Everything from network to cloud to infrastructure to platforms to applications to databases to security to firewalls to low-bands, and on and on and on we go. The complexity continues to rise almost on a daily basis, if not on an hourly basis. And that is probably the biggest area that so many people underestimate, because we tend to get into conversations where we talk about things in very microscopic views, right? We talk about a particular application or a particular deployment or a particular cloud infrastructure. And when we put those guardrails, again, there’s that term guardrails, right?

Peter Sprygada • 17:31

We put those guardrails in place, it’s very easy to look at and say through that lens and say, okay, I know how to operationalize this stack so that it is performant, it is optimized, it is secure, it runs in my infrastructure the way I need it to. Now, when I take that and I push that into the larger The larger picture of the entire organization. Now we’ve introduced tons of complexity because there were a lot of very domain-specific decisions made that maybe don’t align with the full operational stack. And that’s where I think we make some of the, that’s where we underestimate significantly in terms of what it takes to run infrastructure today.

Neil Hughes • 18:11

And as we do look ahead, what does the future infrastructure operation stack actually look like to you? And what kind of mindset shift do leaders listening need to make right now if they want their platforms to stay relevant over the next five to 10 years? And I realized just saying that out loud, five to 10 years away is just impossible to predict, but let’s say in the next few years.

Peter Sprygada • 18:32

Yeah. You know, so we’ve already kind of touched on AI, and I won’t pound the AI drum, but I certainly think embracing AI as a technology and more importantly, as a tool for sure, no question about it. But beyond just simply AI, I think there’s two things that really IT leaders need to really think through to make sure that their platforms continue to stay relevant. One, 1st and foremost, is invest in the platform, right? That boring stuff I just talked about. And recognize that that boring stuff is what actually allows you to go to sleep at night. So continue to make investments in that boring stuff, that security and logging and governance and whatnot in that platform so that we take a platform level approach to how we build and run infrastructure.

Peter Sprygada • 19:21

I think the other thing that is that IT leaders really need to start to realize with the advent of, and this is a byproduct of AI, is that for a very long time, we’ve had a lot of rigidity in the operational stack. Meaning, if I thought about any particular operational deployment, I almost immediately, with 10, 15, 20, 25 years of experience, knew all the pieces and parts I needed. I needed some monitoring. I needed some logging. I needed some automation. I needed some DNS. I needed some DHCP.

Peter Sprygada • 19:52

I needed some, et cetera, right? The list goes on and on. And we understood that for each one of those categories, there was some subset of… products, technologies, and tools that I would turn to to help me build that operational stack. And we had very distinct lines between them. My service assurance platform is very different than my automation platform, which is very different than my orchestration platform, et cetera. We need to recognize, I think, especially as we continue to think about the complexity of modern infrastructure, that those lines are probably going to blur faster than they ever have.

Peter Sprygada • 20:27

If we look back 12 months from now, 18 months from now, what I think we’re going to start to see is that those lines are going to blur to the point of almost disappearing. The orchestration stack can do some automation. The automation stack can do some observability. The observability can act as a source of truth database. And the list goes on and on. So recognizing that, embracing that, and doing our best to manage our way through it is, I think, is how we can best set ourselves up for the future.

Neil Hughes • 20:55

And for people listening and hearing about Intential for the very 1st time, it is described as the infrastructure and network orchestration platform for the AI era that we all find ourselves. And most interestingly, I think, especially for techies, is you do this through agentic orchestration via MCP and intelligent workflows. And in doing so, you also connect IT systems, CI/CD pipelines, AI agents, and hybrid infrastructure. Now, we are living in an age where techies get triggered by high-level promises that don’t offer as much value as business leaders who see solutions at tech conferences might think. But your description there seems clearly aimed at the techies. So, for those techies listening, that we may have just sparked their curiosity, tell them a little bit more about the company, how you’re helping. Don’t be afraid to get your geek on here and the kind of help that you guys offer.

Peter Sprygada • 21:48

So, yeah, you know, Itential is in an interesting place as an organization is in an interesting place in that, you know, we’ve been doing infrastructure and network automation now for 11 plus years. So, we’ve got a deep-rooted understanding of that particular domain. And we’ve spent a fair bit of time, again, building out the boring stuff and doing some cool stuff on top of it. But, you know, one of the things that has always been important to me, and this actually extends beyond my time at Attention. This extends even back to my roots in the open source domain, back when I was at Red Hat and even prior to that, the way I got into Red Hat was through Ansible. And, you know, when we work in those types of communities, you start to recognize that, you know, you’re absolutely right. I mean, you can’t throw a stone without hitting 15 AI products or vendors or companies that are promising big, transformative changes.

Peter Sprygada • 22:43

I get it. But when you’re working in, Tight-knit technical communities, you stay much more focused on pragmatic solutions that address real problems. And I think that that’s one thing we’ve tried to strike a real balance of, you know, as we continue to roll our stuff, our technology forward is that, yeah, of course, we’re going to make big, bold claims. Of course, we are. But when you start to dig into our technology, You start to realize that our technology has been designed really to focus on solving very specific problems and really layer things together so that we can evolve it over time as organizations need to evolve.

Peter Sprygada • 23:24

And that’s really what it’s all about, you know, for me. It’s staying focused on what is the problem I’m trying to solve today. And let’s have real conversations about pragmatic solutions and not talk about overarching big promises. The reality is, and I believe this to my very, very core, no organization is going to upend their operational environment to bring in the latest and greatest platform that’s going to solve everything from infrastructure operations to world hunger. That’s just not living in reality. Everything has its place, and we have to make sure that we’re designing interfaces, touch points, user experiences, API interactions in ways that allow us to stitch tooling together so that organizations can ultimately bring people, process, and tools all together to solve real problems. And that’s really been our philosophy and what continues to be our philosophy moving forward.

Neil Hughes • 24:22

You had me at solving real problems there. And for everybody listening that would like to find out more information about you, your work, keep up to speed with some of those great blogs you’re writing as well. Where would you like to point everyone listening?

Peter Sprygada • 24:35

Yeah, absolutely. So all of my blogs are always published@itential.com . That’s I-T-E-N-T-I-A-L.com. You can certainly find my writings there. I also cross-post significantly to linkedin.com. And by all means, if you want to talk more, you know, I always tell folks, you know, I love getting into conversations about technology. I love to hear what we’re doing right.

Peter Sprygada • 24:58

But more importantly, I love to hear what we’re doing wrong. What are we missing? What are we not doing right? Because that’s how we grow. That’s how we grow as an organization. That’s how we grow as a community. That’s how we grow as an industry.

Peter Sprygada • 25:07

So you can always find me in the various ethers of the internet, x.com and mastodon at private IP is my handle there. Spragata on linkedin.com. And reach out and let’s have the conversation because that’s where it all starts.

Neil Hughes • 25:23

Love it. Well, I will add links to everything that you mentioned there. So anyone listening, have a look in the show notes. You’ll be able to get hold of you nice and easy. Keep up to speed with anything. I just cannot thank you enough for bringing your pragmatic insights today into bridging legacy systems with emerging tech and just offering real world value to listeners and focusing on solving real world problems while managing complex infrastructure. Sounds very easy on a podcast.

Neil Hughes • 25:50

It’s much more difficult than that. So kudos to everyone listening in this world. And thank you for starting the conversation today.

Peter Sprygada • 25:57

Absolutely. I appreciate the time. It’s been a fantastic conversation. And this is what it’s all about, right? This is where it all starts in these conversations.

Neil Hughes • 26:06

One of the many things I appreciated about Peter’s perspective today is that he never loses sight of the day two problem. Infrastructure does not fail because teams lack ambition. Typically, it fails when complexity outpaces visibility. Yeah, when tools don’t talk to each other, when new technology is introduced without the guardrails needed to help it run safely. And I think Peter’s experience across automation, orchestration, and now AI brings that reality into much-needed sharp focus. And for engineers and architects listening, there is a clear takeaway here. Modern infrastructure is not about replacing everything you have with new shiny tech.

Neil Hughes • 26:49

It’s about creating systems that allow teams to communicate, evolve, and recover when things go wrong. And yeah, that means investing in the boring parts, the governance, the logging, security, and platforms that can adapt over time. So if this episode resonated with you today, it probably reflects challenges that you’re already dealing with inside your own environment. And that alone raises a simple but important question to leave you with. As your infrastructure grows more complex, are your tools and processes helping teams work together? Or are they quietly making the job harder than it needs to be? Please go over to Tech TalksNetwork.com.

Neil Hughes • 27:33

You’ll find a blog post and information on how to connect with my guests. There, there’s 4,000 interviews, nine different podcasts, ways you can work with me, contact me, send me an audio message. The list is endless. I won’t bore you with it. Just go over to Tech TalksNetwork.com and let me know your thoughts on anything we talked about today. But that is it for now. So, time for me to go.

Neil Hughes • 27:55

But I’ll be back again real soon with another story for you. And hopefully, I’ll speak with you all then. Bye for now.