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Beyond the Box: Rethinking Network Infrastructure in an Era of Supply Chain Volatility

Atif Khan
Alkira

Network hardware vendors are raising prices again — and enterprises are feeling it at renewal and refresh time. For example, multiple sources reported that Cisco implemented an average ~3.4% uplift on hardware effective September 13, 2025, followed by similar increases for technical services in early October.

At the same time, the "AI tax" is pushing costs up the stack — especially memory. Counterpoint has projected server-memory prices could double by the end of 2026 versus early 2025, driven by AI demand and supply constraints.

So, if you're an IT leader watching budgets swell while vendors point to "market conditions," you're not alone. Gartner forecasts worldwide IT spending will exceed $6 trillion in 2026, up 10.8% from 2025.

Here's the reality: the buy-rack-depreciate cycle is no longer the only way to build a world-class enterprise network — and this isn't a one-off. It's sustained upward pressure across the hardware stack.

The Old Model Is Breaking

For years, enterprise networking followed the same playbook: buy the hardware, rack it, and build around it. But today, the box-by-box approach creates a bottleneck that slows down an entire organization. Recent data shows that average delivery times for critical infrastructure components remain roughly 25% longer than pre-pandemic levels, stalling digital transformation projects across the globe.

A jump in semiconductor costs stems from growing AI needs, global political strains, and limits in production capacity. As generative AI infrastructure demands skyrocket, with data center systems spending now projected to grow nearly 37% in 2026, traditional enterprise networking is being crowded out of the supply chain.

On top of that, finding skilled engineers to handle complex hardware systems has become tougher. Recent reports suggest that over 60% of organizations now cite a lack of specialized skills as the primary barrier to modernization, surpassing even budget constraints.

The Shift Toward "Consumption-Based" Infrastructure

The shift we are seeing today mirrors the evolution of the data center. Just as we moved from owning physical servers to consuming elastic compute in the cloud, the network is finally decoupling from the physical hardware it runs on.

Nowadays, businesses prefer paying only for what they use when it comes to infrastructure. Instead of owning physical gear, access happens instantly — like turning on a tap — wherever needed across the planet. Software controls everything; human setup becomes unnecessary. What once required boxes and cables now runs quietly behind APIs.

The Strategic Benefits of a Hardware-Light Strategy

When an organization moves away from being its own network utility company and starts consuming networking as a scalable resource, the operational math changes:

  • Shifting focus from heavy upfront investments to flexible operations allows decision-makers to match expenses with real-time demand. Instead of locking funds into expensive equipment that loses value immediately, teams adjust resources as needed. This approach links financial choices directly to how services are used. Over time, reliance on rigid infrastructure gives way to responsiveness. Costs become more predictable when tied to activity levels rather than fixed purchases.
  • Freed from routine fixes, engineers find new roles in shaping secure systems. With less time spent on hardware glitches, attention shifts toward modernizing infrastructure. Instead of troubleshooting ports, they focus on strategic upgrades. Once manual checks fade, innovation gains space to grow. Tasks once demanding daily effort now leave room for deeper work.
  • In a software-defined, service-led model, the underlying technology is upgraded behind the scenes. The enterprise gains access to the latest speeds and security protocols without a disruptive migration project or a forklift upgrade.
  • In the traditional model, expanding into a new global region meant months of procurement and shipping. In the new model, connectivity is a configuration change, not a logistics project.

The Real Cost Conversation

When I talk with CIOs and network architects, the conversation has moved beyond the price of a router.

Instead, focus shifts toward broader expenses, like total cost of ownership. Power needs enter the picture, along with demands for cooling systems. Space constraints matter too. Above all else, the value of staff hours weighs heavily in these talks.

Given fluctuations in worldwide logistics, justifying ownership of an extensive brick-and-mortar infrastructure grows more difficult. Though scale once signaled strength, shifting dependencies now undermine that logic. Because disruptions occur without warning, large fixed networks lose their appeal. Even steady demand patterns fail to offset rising unpredictability. So, reliance on physical reach appears less strategic over time.

Navigating the Transition

Of course, switching to pay-per-use doesn't fix everything instantly. A deeper change in mindset and daily practice is needed. When fixed machines fade out, work flows shift toward APIs, with rules applied by software, not people. At the same time, finance leaders accustomed to steady costs over five years now face shifting monthly bills. For today's tech leads, success hinges less on picking tools and more on making old infrastructure talk smoothly with flexible, modern platforms.

The Path Forward

The organizations that thrive in the coming years won't be the ones with the biggest hardware budgets. They'll be the ones that rethink how infrastructure is consumed altogether.

We don't build our own power plants, and we no longer manufacture our own servers for every application. Networking is the final frontier of this shift. The infrastructure you need is increasingly software-defined and ready to serve your business. The only question is whether you'll keep buying boxes or start consuming networking the way modern enterprises consume everything else.

Atif Khan is CTO and Co-Founder of Alkira

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Ask most IT leaders about their biggest concern with AI and you'll hear the same answer: hallucinations ... Today, however, the conversation has shifted ... As organizations move beyond chatbots and experiments, they are increasingly deploying AI agents that perform multi-step tasks. These systems retrieve documents, query databases, call APIs, generate reports, write code, and make recommendations. The issue is not whether the model can reason. The issue is whether the organization can see, verify, and govern the decisions being made along the way ...

While organizations want to take control of their telemetry, building telemetry pipelines from scratch can be a very daunting, complicated task, even when leveraging open-source standards like OpenTelemetry. It requires specialized knowledge across distributed systems, data engineering, and security. This fragmented approach across systems causes higher operational costs; it puts a strain on resources and reduces efficiency as teams have to work with different interfaces and processes ...

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...

The 2026 Global Data Center Survey from Uptime Institute reveals an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams ...

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Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...

Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...

Top-performing businesses prioritize data-driven decision making, enabling leaders to move from intuition and gut feel towards evidence-based judgment. But that judgment is only sound when the data underpinning decisions is accurate. With incident management, data accuracy is particularly important. Long-term revenue, customer trust, and operational stability depend on high-quality data that enables teams to quickly identify and address the root cause of major incidents. Against this backdrop, governance becomes a critical endeavor to ensure the right data drives the right action ...

In MEAN TIME TO INSIGHT Episode 26, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network compliance ... 

Beyond the Box: Rethinking Network Infrastructure in an Era of Supply Chain Volatility

Atif Khan
Alkira

Network hardware vendors are raising prices again — and enterprises are feeling it at renewal and refresh time. For example, multiple sources reported that Cisco implemented an average ~3.4% uplift on hardware effective September 13, 2025, followed by similar increases for technical services in early October.

At the same time, the "AI tax" is pushing costs up the stack — especially memory. Counterpoint has projected server-memory prices could double by the end of 2026 versus early 2025, driven by AI demand and supply constraints.

So, if you're an IT leader watching budgets swell while vendors point to "market conditions," you're not alone. Gartner forecasts worldwide IT spending will exceed $6 trillion in 2026, up 10.8% from 2025.

Here's the reality: the buy-rack-depreciate cycle is no longer the only way to build a world-class enterprise network — and this isn't a one-off. It's sustained upward pressure across the hardware stack.

The Old Model Is Breaking

For years, enterprise networking followed the same playbook: buy the hardware, rack it, and build around it. But today, the box-by-box approach creates a bottleneck that slows down an entire organization. Recent data shows that average delivery times for critical infrastructure components remain roughly 25% longer than pre-pandemic levels, stalling digital transformation projects across the globe.

A jump in semiconductor costs stems from growing AI needs, global political strains, and limits in production capacity. As generative AI infrastructure demands skyrocket, with data center systems spending now projected to grow nearly 37% in 2026, traditional enterprise networking is being crowded out of the supply chain.

On top of that, finding skilled engineers to handle complex hardware systems has become tougher. Recent reports suggest that over 60% of organizations now cite a lack of specialized skills as the primary barrier to modernization, surpassing even budget constraints.

The Shift Toward "Consumption-Based" Infrastructure

The shift we are seeing today mirrors the evolution of the data center. Just as we moved from owning physical servers to consuming elastic compute in the cloud, the network is finally decoupling from the physical hardware it runs on.

Nowadays, businesses prefer paying only for what they use when it comes to infrastructure. Instead of owning physical gear, access happens instantly — like turning on a tap — wherever needed across the planet. Software controls everything; human setup becomes unnecessary. What once required boxes and cables now runs quietly behind APIs.

The Strategic Benefits of a Hardware-Light Strategy

When an organization moves away from being its own network utility company and starts consuming networking as a scalable resource, the operational math changes:

  • Shifting focus from heavy upfront investments to flexible operations allows decision-makers to match expenses with real-time demand. Instead of locking funds into expensive equipment that loses value immediately, teams adjust resources as needed. This approach links financial choices directly to how services are used. Over time, reliance on rigid infrastructure gives way to responsiveness. Costs become more predictable when tied to activity levels rather than fixed purchases.
  • Freed from routine fixes, engineers find new roles in shaping secure systems. With less time spent on hardware glitches, attention shifts toward modernizing infrastructure. Instead of troubleshooting ports, they focus on strategic upgrades. Once manual checks fade, innovation gains space to grow. Tasks once demanding daily effort now leave room for deeper work.
  • In a software-defined, service-led model, the underlying technology is upgraded behind the scenes. The enterprise gains access to the latest speeds and security protocols without a disruptive migration project or a forklift upgrade.
  • In the traditional model, expanding into a new global region meant months of procurement and shipping. In the new model, connectivity is a configuration change, not a logistics project.

The Real Cost Conversation

When I talk with CIOs and network architects, the conversation has moved beyond the price of a router.

Instead, focus shifts toward broader expenses, like total cost of ownership. Power needs enter the picture, along with demands for cooling systems. Space constraints matter too. Above all else, the value of staff hours weighs heavily in these talks.

Given fluctuations in worldwide logistics, justifying ownership of an extensive brick-and-mortar infrastructure grows more difficult. Though scale once signaled strength, shifting dependencies now undermine that logic. Because disruptions occur without warning, large fixed networks lose their appeal. Even steady demand patterns fail to offset rising unpredictability. So, reliance on physical reach appears less strategic over time.

Navigating the Transition

Of course, switching to pay-per-use doesn't fix everything instantly. A deeper change in mindset and daily practice is needed. When fixed machines fade out, work flows shift toward APIs, with rules applied by software, not people. At the same time, finance leaders accustomed to steady costs over five years now face shifting monthly bills. For today's tech leads, success hinges less on picking tools and more on making old infrastructure talk smoothly with flexible, modern platforms.

The Path Forward

The organizations that thrive in the coming years won't be the ones with the biggest hardware budgets. They'll be the ones that rethink how infrastructure is consumed altogether.

We don't build our own power plants, and we no longer manufacture our own servers for every application. Networking is the final frontier of this shift. The infrastructure you need is increasingly software-defined and ready to serve your business. The only question is whether you'll keep buying boxes or start consuming networking the way modern enterprises consume everything else.

Atif Khan is CTO and Co-Founder of Alkira

Hot Topics

The Latest

Ask most IT leaders about their biggest concern with AI and you'll hear the same answer: hallucinations ... Today, however, the conversation has shifted ... As organizations move beyond chatbots and experiments, they are increasingly deploying AI agents that perform multi-step tasks. These systems retrieve documents, query databases, call APIs, generate reports, write code, and make recommendations. The issue is not whether the model can reason. The issue is whether the organization can see, verify, and govern the decisions being made along the way ...

While organizations want to take control of their telemetry, building telemetry pipelines from scratch can be a very daunting, complicated task, even when leveraging open-source standards like OpenTelemetry. It requires specialized knowledge across distributed systems, data engineering, and security. This fragmented approach across systems causes higher operational costs; it puts a strain on resources and reduces efficiency as teams have to work with different interfaces and processes ...

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...

The 2026 Global Data Center Survey from Uptime Institute reveals an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams ...

The next observability gap may not be in the code. It may be under the rack. That sounds strange until you think about how AI incidents actually feel in the middle of an investigation ... The application dashboard may be accurate. It may also be stopping at the wrong boundary. AI systems depend on software, but they also depend on a dense physical stack: racks, power paths, thermal margin, maintenance activity and, in many environments, liquid cooling. Those physical dependencies can change slowly before they look like a software incident ...

Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...

Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...

Top-performing businesses prioritize data-driven decision making, enabling leaders to move from intuition and gut feel towards evidence-based judgment. But that judgment is only sound when the data underpinning decisions is accurate. With incident management, data accuracy is particularly important. Long-term revenue, customer trust, and operational stability depend on high-quality data that enables teams to quickly identify and address the root cause of major incidents. Against this backdrop, governance becomes a critical endeavor to ensure the right data drives the right action ...

In MEAN TIME TO INSIGHT Episode 26, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network compliance ...