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Stepping Into the New Network Architecture

Destiny Bertucci
Auvik

When the COVID-19 pandemic hit, employees that were once loyal to the Monday-Friday office life were given their first taste of what remote-work can be like. And while most thought it would be a temporary solution during unprecedented times, many discovered ways in which remote-work changed their working life for the better. According to a survey done by Owl Labs, after the COVID-19 pandemic 92% of the 10,000 surveyed stated that they expect to work from home at least one day per week, with 80% expecting to work from home at least three days a week. Over the past few years, employers and employees alike have discovered many benefits of allowing individuals to work in environments where they thrive.

It does not, however, come without its challenges. While most thought that distraction and motivation would be the main contributors to low productivity in a work-from-home environment, many organizations discovered that it was gaps in their IT systems that created some of the most significant challenges. During the pandemic, demand for broadband communications skyrocketed, with some operators seeing as much as a 60% increase in internet traffic. Where IT teams had previously had the ability to either physically work on devices with connectivity issues or work directly on the company network, employees working from home or at a coffee shop suddenly posed an entirely new challenge.

In order to combat network and productivity issues, IT teams have turned to SaaS and cloud services to help with employee productivity, making it easier for IT teams to provide the right services for employees no matter where they're working from. Today, SaaS and cloud service have become so prominent that we're predicted to see 25.4 billion active IoT devices by 2030.

While SaaS and cloud services have been a great solution for the shortage of network hardware (due to the ongoing semiconductor chip shortage and supply chain challenges) the sudden growth of cloud computing has changed the needs of the network, and its architecture is sure to need a makeover soon.

All Signs Point to the Economy

Believe it or not, the economy plays a big role in the need for a new network architecture. Prior to the pandemic, businesses were not looking to their IT teams for revenue growth or data on business continuity. If there was a problem with the network, common practice was to simply buy more bandwidth. Then came the supply chain issues and inflation, and businesses found themselves unable to get their hands on the devices they needed to add more bandwidth. Instead, they turned to SaaS and cloud services.

With this software, businesses suddenly had access to data they'd never considered before — Where is their traffic? Where is there congestion? What is the output? Where are employees losing productivity due to our processes? And most importantly — why is any of this occurring? SaaS and cloud services quickly made themselves central to business continuity and efficiency. Even when supply chain issues cleared up and hardware devices were less expensive and easier to find, business leaders had discovered a big business value in SaaS and we're not going to turn back.

So How Does this Change Network Architecture?

Network architecture must lean into the push for software-led devices. Right now, we're just seeing the beginning of the plug-and-play era and the traditional network that would backhaul traffic through data centers, and physical network devices won't suffice as SaaS and cloud services continue to take over. Instead, businesses need a network architecture that can steer traffic directly over the internet, eliminating traffic stops along the way while still providing the network security needed to keep their data safe.

SD-WAN is a hot topic at the moment. Unlike the traditional network architecture, it's designed for cloud computing, eliminating the need for traffic stops that the traditional network needed to connect devices that are in different locations but using the same cloud software. Instead, because SD-WAN is designed for cloud computing, it can route traffic directly over the internet while maintaining a secure connection. However, it is still rather new and poses risks for businesses whose IT teams aren't prepared and trained to work with a different type of network.

Right now, IT professionals and network admins are facing a divide between those who are trained and knowledgeable on how to run a cloud based network vs those who could run and maintain a traditional one. The lack of education on SD-WAN and the broader need for a new network architecture, pose threats to businesses who move forward with SaaS and cloud-based networks without properly trained professionals to manage and maintain it. As we move forward and see a broader adoption of SD-WAN and cloud-based networks, education and training will become more prominent in the industry and help push us forward into the new network architecture.

Destiny Bertucci is Product Strategist at Auvik

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

Stepping Into the New Network Architecture

Destiny Bertucci
Auvik

When the COVID-19 pandemic hit, employees that were once loyal to the Monday-Friday office life were given their first taste of what remote-work can be like. And while most thought it would be a temporary solution during unprecedented times, many discovered ways in which remote-work changed their working life for the better. According to a survey done by Owl Labs, after the COVID-19 pandemic 92% of the 10,000 surveyed stated that they expect to work from home at least one day per week, with 80% expecting to work from home at least three days a week. Over the past few years, employers and employees alike have discovered many benefits of allowing individuals to work in environments where they thrive.

It does not, however, come without its challenges. While most thought that distraction and motivation would be the main contributors to low productivity in a work-from-home environment, many organizations discovered that it was gaps in their IT systems that created some of the most significant challenges. During the pandemic, demand for broadband communications skyrocketed, with some operators seeing as much as a 60% increase in internet traffic. Where IT teams had previously had the ability to either physically work on devices with connectivity issues or work directly on the company network, employees working from home or at a coffee shop suddenly posed an entirely new challenge.

In order to combat network and productivity issues, IT teams have turned to SaaS and cloud services to help with employee productivity, making it easier for IT teams to provide the right services for employees no matter where they're working from. Today, SaaS and cloud service have become so prominent that we're predicted to see 25.4 billion active IoT devices by 2030.

While SaaS and cloud services have been a great solution for the shortage of network hardware (due to the ongoing semiconductor chip shortage and supply chain challenges) the sudden growth of cloud computing has changed the needs of the network, and its architecture is sure to need a makeover soon.

All Signs Point to the Economy

Believe it or not, the economy plays a big role in the need for a new network architecture. Prior to the pandemic, businesses were not looking to their IT teams for revenue growth or data on business continuity. If there was a problem with the network, common practice was to simply buy more bandwidth. Then came the supply chain issues and inflation, and businesses found themselves unable to get their hands on the devices they needed to add more bandwidth. Instead, they turned to SaaS and cloud services.

With this software, businesses suddenly had access to data they'd never considered before — Where is their traffic? Where is there congestion? What is the output? Where are employees losing productivity due to our processes? And most importantly — why is any of this occurring? SaaS and cloud services quickly made themselves central to business continuity and efficiency. Even when supply chain issues cleared up and hardware devices were less expensive and easier to find, business leaders had discovered a big business value in SaaS and we're not going to turn back.

So How Does this Change Network Architecture?

Network architecture must lean into the push for software-led devices. Right now, we're just seeing the beginning of the plug-and-play era and the traditional network that would backhaul traffic through data centers, and physical network devices won't suffice as SaaS and cloud services continue to take over. Instead, businesses need a network architecture that can steer traffic directly over the internet, eliminating traffic stops along the way while still providing the network security needed to keep their data safe.

SD-WAN is a hot topic at the moment. Unlike the traditional network architecture, it's designed for cloud computing, eliminating the need for traffic stops that the traditional network needed to connect devices that are in different locations but using the same cloud software. Instead, because SD-WAN is designed for cloud computing, it can route traffic directly over the internet while maintaining a secure connection. However, it is still rather new and poses risks for businesses whose IT teams aren't prepared and trained to work with a different type of network.

Right now, IT professionals and network admins are facing a divide between those who are trained and knowledgeable on how to run a cloud based network vs those who could run and maintain a traditional one. The lack of education on SD-WAN and the broader need for a new network architecture, pose threats to businesses who move forward with SaaS and cloud-based networks without properly trained professionals to manage and maintain it. As we move forward and see a broader adoption of SD-WAN and cloud-based networks, education and training will become more prominent in the industry and help push us forward into the new network architecture.

Destiny Bertucci is Product Strategist at Auvik

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.