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Enterprises Are Ready to Leverage Network as a Service (NaaS)

Shamus McGillicuddy

Cloud computing transformed the IT industry by delivering software and infrastructure as a service, allowing customers to offload capital expenditures and operational overhead around software, software development platforms, security, compute, and storage. The cloudification of networking was slower in coming, but the concept of network as a service (NaaS) — which until now was a loosely defined term to describe a variety of networking solutions delivered via a cloud-like service model — earned more prominence in recent years.

Numerous vendors and service providers have recently embraced the NaaS concept, yet there is still no industry consensus on its definition or the types of networks it involves. Furthermore, providers have varied in how they define the NaaS service delivery model. I conducted research for a new report, Network as a Service: Understanding the Cloud Consumption Model in Networking, to refine the concept of NaaS and reduce buyer confusion over what it is and how it can offer value.

For this research survey, I defined NaaS for survey participants as the following: A network infrastructure solution that offers a cloud consumption model (pay as you go) in which the NaaS provider can manage all aspects of network engineering and operations, from design and build to monitoring and troubleshooting.

Some of the key findings from this report include:

■ Most respondents associated NaaS with cloud and WAN interconnectivity, SD-WAN and SASE, and WAN connectivity; only 28% associated NaaS with campus networking.

■ IT organizations believe a NaaS offering should include integrated managed security services, cloud-like consumption of services, comprehensive observability, and APIs and integrations with other IT systems.

■ 64% prefer a hybrid operating model for NaaS solutions, in which the provider and the internal network team share responsibility for day monitoring troubleshooting, and ongoing management.

This research found that most companies are interested in consuming NaaS solutions in all aspects of their network, from the campus to the cloud. But decision-makers do have concerns about NaaS.

First, they believe the shift from CapEx to OpEx could lead to higher total cost of ownership over time, much like the public cloud.

Second, they worry that they'll lose visibility into service quality.

Finally, as with any disruptive technology, many stakeholders worry about the security risk of consuming networks in this way.

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Cloud outages are usually described as technical failures. When a service goes down, a dependency breaks, or a region has issues, the focus immediately shifts to infrastructure. But if you look closely at how these incidents actually unfold, the root cause is rarely the technology itself. It is almost always tied to decisions made earlier, during design, implementation, or day-to-day operations. The system behaves the way it was built. The real question is how it was built ...

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In the ever-evolving digital landscape, enterprises are increasingly focused on enhancing their observability stacks to gain deeper insights into their IT environments. Observability has become a cornerstone of modern IT operations, enabling organizations to monitor, diagnose, and optimize their systems with unprecedented precision. However, a critical piece of the puzzle often goes unnoticed in this transformation: IBM i ...

We just surveyed 300 frontend and mobile engineers across 16 countries, and the finding that keeps sticking with me isn't the one about AI. It's this: 74% of engineering teams rate themselves in the "middle" of the observability maturity scale. Not reactive, not strategic. Stuck in the middle. They have dashboards, they have tracing, they have alerts. And yet when something goes wrong, they still can't tell you why ...

In MEAN TIME TO INSIGHT Episode 25, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses  AI's impact on the Wide Area Network (WAN) ... 

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The race to deploy AI is largely over. Most enterprises have entered it. The question now is not whether artificial intelligence is running inside the organization. The question is whether anyone is genuinely responsible for what it does. That is not a technical question. It is a leadership one. And most organizations are not yet structured to answer it honestly ...

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The enterprises that will define the next decade are not the ones that deployed the most technology. They are the ones who understood what their technology was actually doing. That distinction is not a philosophical point. It is the central operational challenge facing every organization that has spent the last five years modernizing at speed ...

AI is becoming the operating system of the enterprise. It acts as an invisible coordination layer that understands intent, connects systems, and executes work across complex SaaS environments. Previously, employees had to click through multiple systems — CRM, ERP, support tools, collaboration platforms — to complete a single task. Now, instead of navigating each application manually, they can simply state what they need to accomplish ...

Enterprises Are Ready to Leverage Network as a Service (NaaS)

Shamus McGillicuddy

Cloud computing transformed the IT industry by delivering software and infrastructure as a service, allowing customers to offload capital expenditures and operational overhead around software, software development platforms, security, compute, and storage. The cloudification of networking was slower in coming, but the concept of network as a service (NaaS) — which until now was a loosely defined term to describe a variety of networking solutions delivered via a cloud-like service model — earned more prominence in recent years.

Numerous vendors and service providers have recently embraced the NaaS concept, yet there is still no industry consensus on its definition or the types of networks it involves. Furthermore, providers have varied in how they define the NaaS service delivery model. I conducted research for a new report, Network as a Service: Understanding the Cloud Consumption Model in Networking, to refine the concept of NaaS and reduce buyer confusion over what it is and how it can offer value.

For this research survey, I defined NaaS for survey participants as the following: A network infrastructure solution that offers a cloud consumption model (pay as you go) in which the NaaS provider can manage all aspects of network engineering and operations, from design and build to monitoring and troubleshooting.

Some of the key findings from this report include:

■ Most respondents associated NaaS with cloud and WAN interconnectivity, SD-WAN and SASE, and WAN connectivity; only 28% associated NaaS with campus networking.

■ IT organizations believe a NaaS offering should include integrated managed security services, cloud-like consumption of services, comprehensive observability, and APIs and integrations with other IT systems.

■ 64% prefer a hybrid operating model for NaaS solutions, in which the provider and the internal network team share responsibility for day monitoring troubleshooting, and ongoing management.

This research found that most companies are interested in consuming NaaS solutions in all aspects of their network, from the campus to the cloud. But decision-makers do have concerns about NaaS.

First, they believe the shift from CapEx to OpEx could lead to higher total cost of ownership over time, much like the public cloud.

Second, they worry that they'll lose visibility into service quality.

Finally, as with any disruptive technology, many stakeholders worry about the security risk of consuming networks in this way.

Hot Topics

The Latest

Cloud outages are usually described as technical failures. When a service goes down, a dependency breaks, or a region has issues, the focus immediately shifts to infrastructure. But if you look closely at how these incidents actually unfold, the root cause is rarely the technology itself. It is almost always tied to decisions made earlier, during design, implementation, or day-to-day operations. The system behaves the way it was built. The real question is how it was built ...

77% of leaders say their teams need AI skills urgently. 64% say their organization plans to train current employees rather than hire new ones. So far, so reasonable. The part that surprised me is who's been put in charge: 34% of those leaders say IT and engineering own the AI skills mandate. Learning and Development or HR own it at 7% of organizations. That's roughly five-to-one in favor of the people who understand the tools, over the people whose actual job is teaching adults how to learn new ones ...

In the ever-evolving digital landscape, enterprises are increasingly focused on enhancing their observability stacks to gain deeper insights into their IT environments. Observability has become a cornerstone of modern IT operations, enabling organizations to monitor, diagnose, and optimize their systems with unprecedented precision. However, a critical piece of the puzzle often goes unnoticed in this transformation: IBM i ...

We just surveyed 300 frontend and mobile engineers across 16 countries, and the finding that keeps sticking with me isn't the one about AI. It's this: 74% of engineering teams rate themselves in the "middle" of the observability maturity scale. Not reactive, not strategic. Stuck in the middle. They have dashboards, they have tracing, they have alerts. And yet when something goes wrong, they still can't tell you why ...

In MEAN TIME TO INSIGHT Episode 25, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses  AI's impact on the Wide Area Network (WAN) ... 

Application performance monitoring (APM) dashboards are only as useful as what they are configured to measure. The default setup covers obvious failure modes such as downtime, error spikes, and latency breaches, but it does not cover everything. Some failures produce no alerts or anomalies. The dashboard stays green while users experience a broken product. Here are six signs that is happening ...

The race to deploy AI is largely over. Most enterprises have entered it. The question now is not whether artificial intelligence is running inside the organization. The question is whether anyone is genuinely responsible for what it does. That is not a technical question. It is a leadership one. And most organizations are not yet structured to answer it honestly ...

A new analysis of 250 real-world queries across common retail tasks, such as product pricing, availability, ratings, shipping and specifications, reveals systemic inefficiency at the heart of web-based AI agents. On average, 97.9% of the data retrieved by agents from live web pages is irrelevant to the query being answered. Specifically, the average page ingested ran nearly 9,000 characters, while the average answer was just 32 characters, resulting in a noise-to-signal ratio of 278:1. Price queries were the most extreme outlier, with noise rates approaching 99.5%. That's not a rounding error. That's a structural problem ...

The enterprises that will define the next decade are not the ones that deployed the most technology. They are the ones who understood what their technology was actually doing. That distinction is not a philosophical point. It is the central operational challenge facing every organization that has spent the last five years modernizing at speed ...

AI is becoming the operating system of the enterprise. It acts as an invisible coordination layer that understands intent, connects systems, and executes work across complex SaaS environments. Previously, employees had to click through multiple systems — CRM, ERP, support tools, collaboration platforms — to complete a single task. Now, instead of navigating each application manually, they can simply state what they need to accomplish ...