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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

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Part 4 outlines the challenges enterprise face when adopting AI observability. The main challenge is that AI complexity compounds at every stage of maturity. LLM-based applications introduce new behavior, dependencies, and quality considerations, while Agentic AI adds further failure modes as systems make decisions and take actions ...

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AI, automation, and enterprise software give organizations an extraordinary amount of leverage. Work that once required hours can happen in minutes. Information buried across systems can be analyzed almost instantly. Complex workflows can be coordinated across teams with far less manual intervention. That leverage creates a temptation to start with the technology ...

Everyone wants to talk about models. Compute clusters. Benchmark scores that climb a fraction of a point and make headlines anyway. It's an easy conversation to have because it's measurable. But it's also increasingly beside the point ...

For more than a decade, the default infrastructure play has been simple. Move more workloads to the cloud, retire on-premises gear and treat the data center as a cost to shrink. That logic held while public cloud offered near-limitless capacity at predictable prices, and AI demand is now testing both halves of that assumption ...

Most enterprise IT leaders can tell you exactly how many applications are running across their organization. They can surface a dashboard showing telecom spend by region, pull a report on SaaS license utilization, or call up a real-time view of mobile device inventory. The data is there, and IT leaders have largely delivered on the promise of visibility. Yet, in most organizations, that visibility has not translated into business value ...

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

AI observability serves several roles across an organization. AI engineers use it to build, evaluate, and improve AI systems. SREs use it to operate those systems reliably and efficiently in production, including managing their cost. Leaders need it to connect AI behavior and operational performance to business outcomes. The common need is a clear understanding of whether AI systems are delivering the intended result ...

Part 4 outlines the challenges enterprise face when adopting AI observability. The main challenge is that AI complexity compounds at every stage of maturity. LLM-based applications introduce new behavior, dependencies, and quality considerations, while Agentic AI adds further failure modes as systems make decisions and take actions ...

Part 3 reports on the current state of AI observability. Most experts agree: enterprises are moving faster with AI than they are with the operational discipline needed to run it safely ...

When discussing AI Observability, one of the first questions that arises: Is this just an extension of traditional observability or is this a whole new type of tool? Part 2 compares traditional observability with AI observability ...

In this extensive 14-part series that will post over the next three weeks, experts across observability and AI will provide insight and opinions on the need for AI Observability, the challenges, the benefits, the current state, and predictions for the future ...

Amid rising complexity, organizations are moving quickly toward agent-driven operations: AgenticOps, according to The Impact of Agentic AI on Network Operations, a new report from Cisco ...

AI, automation, and enterprise software give organizations an extraordinary amount of leverage. Work that once required hours can happen in minutes. Information buried across systems can be analyzed almost instantly. Complex workflows can be coordinated across teams with far less manual intervention. That leverage creates a temptation to start with the technology ...

Everyone wants to talk about models. Compute clusters. Benchmark scores that climb a fraction of a point and make headlines anyway. It's an easy conversation to have because it's measurable. But it's also increasingly beside the point ...

For more than a decade, the default infrastructure play has been simple. Move more workloads to the cloud, retire on-premises gear and treat the data center as a cost to shrink. That logic held while public cloud offered near-limitless capacity at predictable prices, and AI demand is now testing both halves of that assumption ...

Most enterprise IT leaders can tell you exactly how many applications are running across their organization. They can surface a dashboard showing telecom spend by region, pull a report on SaaS license utilization, or call up a real-time view of mobile device inventory. The data is there, and IT leaders have largely delivered on the promise of visibility. Yet, in most organizations, that visibility has not translated into business value ...