A (3:33)

Thank you, I appreciate that highlighting that risk. And you talked about MSPs having this fragmented tooling which I've seen as well. They're dozens of tools to report lots of dashboards but just a not not enough context which again comes with a higher risk. And I liked how you mentioned AI governance. You know I've been involved in a lot of that, chair IT governance myself. But it seems like technology always leapfrogs, right? It's the hardware doesn't keep up with the software and vice versa. Same thing with AI. We're seeing a lot of just the proliferation of AI and there's really no governance or AI governance anyway for the technology that's being rolled out. So I appreciate you highlighting that. And Dan Avic manages over a million network devices and millions of SaaS applications across 100,000 networks. What technical or architectural decisions are essential to delivering reliability and simplicity at that scale?

B (4:32)

Yeah, at that scale the architectural decisions made early on really matter. We went into the MSP channel and true multi tenancy is key to the operational efficiency and scalability. A lot of companies try to move into the MSP space and build multi tenancy on later. That never really works out who ends up clunky. So building your system with multi tenancy upfront actually matters a lot. Beyond that, observability is incredibly important. Being cloud native and being able to scale your services to handle traffic spikes and adoption matter. And then I like to keep it take things back to we want to keep things simple for our users. We want to make sure our technology decisions and keep our technology simple until we need to make it more complex. Beyond that, automated discovery and device consolidation, we need those as a first principle. Manual configuration doesn't really scale. The system needs to continuously relearn the environment. If you were to manually do that, it's outdated the second you deploy it. So continuous automated discovery and mapping ensure that Our platform always reflects reality because networks do change constantly. And lastly, you want automation of like configuration backups and documentations to remove operational drag for msps.

A (6:02)

Thank you, I appreciate that. Just to highlight a few things, you talked about really the key to scale, that architectural design has to be foundational from the get go. We talked about observability, being cloud native, being able to scale quickly, but automated discovery and mapping, device consolidation, those are key to really managing these large environments. So I appreciate that.

B (6:25)

Absolutely.

A (6:26)

Dan, automation is a core promise of modern IT operations. Where does automation deliver the most immediate value for IT teams? And where do you still see friction or overhype?

B (6:37)

So there's really like two areas where I see immediate value for IT teams. The first one is when it comes to those boring, repetitive, mundane operational tasks. So if you think like firmware updates, routine patching workflows, triaging alerts, policy enforcement across distributed sites and documentation, I think automation can really, really help streamline those. And they're not strategic activities, but they're absolutely necessary and they need to be done. So automation helps reduce the burnout and frees IT techs to focus their time on more high impact work. And the second one, I think automation could really start to help with root cause isolation across hybrid environments. Especially when you have data from multiple sources. You could tie together and try to start to root cause. Like I keep having zoom drop. Is that a network issue? Okay, where's the device having the problem? So I think there's a ton of value there. And then to the second part of your question, where is it overhyped? You hear a lot of like, AI is going to replace all of your engineers. That's probably unrealistic. AI is great and it offers a bunch of really fantastic like productivity enhancements if you use it properly. But in reality it's probably not going to replace everything your engineers are doing. I think it's also risky to have AI without governance. You could run into hallucinations where you might automate something and it might do the wrong thing. So I think you have to be very careful with AI and automation and make sure you have deterministic checkpoints in place as you roll that out.

A (8:22)

Thank you. I appreciate that. AI does come with a lot of hype and can be invaluable for automated tasks and obviously scanning a lot of data points, endpoints, that sort of thing. But it does come with risk. And as we talked about earlier, you know, AI governance is key in this area if we're going to leverage the, the, the AI technology But talking about the value for IT teams, you talked about those mundane tasks, updates, policy enforcements, et cetera. Automation is definitely key to streamlining and definitely automate key for root cause isolation as you mentioned. So I appreciate your insights there. And Dan, last question of the day. As we look ahead, how do you see the future of network management and IT operations changing over the next five years? And what skills will IT leaders and engineers need to stay ahead?

B (9:11)

I think a big one for network management. It's the rise of the IT generalist and AI driven outcomes. We're moving into an era where companies have leaner teams managing broader environments and I think the IT generalist becomes much more normal than having a bunch of certified specialists. Leaders must build platforms that increase the leverage of those generalists rather than requiring deep specialization to operate the platform. And I think we'll see a shift from AI everywhere, random tools layered on top of workflows to AI centered around actual outcomes with measurable metrics. So that means you'll see AI deployed in areas where you want to see measurable improvements in uptime ticket resolution, time, risk detection, end user experience, not just AI for AI's sake. Beyond that, like continuing what we were just talking about, AI governance is going to become core infrastructure. The conversation has to shift from which AI tools are we using to how do we govern AI safety at scale. I think Shadow AI detection, SaaS visibility and then anomaly monitoring are going to become foundational. And then I think governance won't be a compliant side project. It's going to have to be embedded into network and it oper. So and the end of the day, the next five years won't reward the teams with the most tools, they'll reward the teams that create the visibility and approach governance proactively.

A (10:44)

Thank you, appreciate that. Yes, definitely see a lot of changes here in the near future, especially as the newer technology comes out with AI people leveraging AI. But we'll definitely need some more automation. As you mentioned, IT journalists will be more prominent obviously as we implement more automation and AI workflows with measurable outputs and reporting, which is really key. And Dan, it was such a pleasure having you on today and I look forward to speaking with you real soon.

B (11:14)

Pleasure to be here.

A (11:16)

Bye for now.