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What is SDN?

Early Adopters Define Sofware-Defined Networking
Shamus McGillicuddy

Greg Ferro recently blogged about how attempts to define software-defined networking (SDN) are a waste of time. He wrote: "You can’t define 'Software Defined Network' because it's not a thing. It's not a single thing or even a few things. It's combination of many things including intangibles. Stop trying to define it. Just deploy it."

To a great extent I agree with him. It’s hard to define SDN as one thing, given that it is applied to so many different areas of networking: Data centers, enterprise campus, the WAN, radio access networks, etc. And each vendor that introduces an SDN product to the market is working from a definition that fits into its own strategy. Cisco’s is hardware-centric. VMware’s is software-centric, and so on.

So, yes. Just deploy it. But … what do those people who deploy SDN have to say?

EMA did offer a definition of SDN in its recently published research report Managing Tomorrow’s Networks: The Impacts of SDN and Network Virtualization on Network Management. The research is based on a survey of 150 enterprises that have deployed SDN in production or have plans to do so within 12 months. The report explores the benefits and challenges of SDN. Much of the research explores the readiness of incumbent network management tools to support SDN infrastructure and it identifies new functional requirements for these management tools.

(Side note: We also surveyed 76 communications service providers on the same topics, but I’m limiting this blog discussion to enterprise networking).

Since we were surveying people who were actually implementing SDN, we thought it would be valuable to get their take on what SDN actually is. We asked them the following question: When thinking about the definition of SDN, what characteristics of an SDN solution are important to you? Here are the top three defining characteristics of SDN for early enterprise adopters:

■ Centralized controller (39% of respondents)

■ Fluid network architecture (27%)

■ Low-cost hardware (25%)

A decoupled control plane and data plane (13%) was tied with intent-based networking as the least important defining aspect of SDN solutions.

These top three responses from early adopters of SDN present a pretty simple definition of the technology. And when you think about it, these terms align what we’re seeing in the market place. Nearly every SDN solution has a centralized controller, or at least a centrally accessible, distributed controller. This controller serves as a single point of control, access, programmability and data collection for the network. Most solutions also offer low-cost hardware, or — in the case of overlays — require no new hardware.

Fluid network architecture, I would argue, gets to the heart of what SDN is all about. It enables networks that are flexible and responsive to changes in infrastructure conditions and business requirements. This contrasts sharply with static, highly manual legacy networks, where any change to network connectivity in a data center or a remote site can require days, weeks or even months to implement. SDN’s promise is a network that can respond to change quickly and fluidly, thanks to increased programmability, for instance.

Therefore, I defer to the wisdom of early adopters when trying to come with up a definition. SDN is characterized by a fluid network architecture that is enabled by a centralized controller and low-cost hardware.

One final point on the subject of defining SDN. We asked early adopters of software-defined WAN (SD-WAN) a similar but distinct question on the defining characteristics of SD-WAN, which EMA considers sufficiently different from other varieties of SDN to warrant its own definition. In the case of SD-WAN, cloud-based network and security services were the number one defining aspect of such solutions. Centralized control was the number two priority, followed by hybrid WAN connectivity.

Shamus McGillicuddy is Senior Analyst, Network Management at Enterprise Management Associates (EMA).

Hot Topics

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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 ... 

Most production autonomous agents do not run in a vacuum. They run inside cloud infrastructure: virtual machines, containers, pods, managed clusters or private servers. That is where most operations teams start monitoring. Is the VM alive? Is the container running? Did the pod restart? Is memory stable? Is CPU too high? Did the health check pass? Those signals are useful. They tell you whether the shell around the agent is alive. They do not tell you whether the agent inside is actually operational ...

Enterprise IT environments have never been more observable ... Yet many organizations still grapple with outages, lengthy incident resolution cycles, and increasing complexity. Most teams do not suffer from a shortage of data. They struggle to determine what deserves attention and what action to take next ... Enterprise IT operations must move beyond monitoring and visibility. The next stage of maturity is decision operations, an approach that helps teams make faster, better-informed decisions ...

What is SDN?

Early Adopters Define Sofware-Defined Networking
Shamus McGillicuddy

Greg Ferro recently blogged about how attempts to define software-defined networking (SDN) are a waste of time. He wrote: "You can’t define 'Software Defined Network' because it's not a thing. It's not a single thing or even a few things. It's combination of many things including intangibles. Stop trying to define it. Just deploy it."

To a great extent I agree with him. It’s hard to define SDN as one thing, given that it is applied to so many different areas of networking: Data centers, enterprise campus, the WAN, radio access networks, etc. And each vendor that introduces an SDN product to the market is working from a definition that fits into its own strategy. Cisco’s is hardware-centric. VMware’s is software-centric, and so on.

So, yes. Just deploy it. But … what do those people who deploy SDN have to say?

EMA did offer a definition of SDN in its recently published research report Managing Tomorrow’s Networks: The Impacts of SDN and Network Virtualization on Network Management. The research is based on a survey of 150 enterprises that have deployed SDN in production or have plans to do so within 12 months. The report explores the benefits and challenges of SDN. Much of the research explores the readiness of incumbent network management tools to support SDN infrastructure and it identifies new functional requirements for these management tools.

(Side note: We also surveyed 76 communications service providers on the same topics, but I’m limiting this blog discussion to enterprise networking).

Since we were surveying people who were actually implementing SDN, we thought it would be valuable to get their take on what SDN actually is. We asked them the following question: When thinking about the definition of SDN, what characteristics of an SDN solution are important to you? Here are the top three defining characteristics of SDN for early enterprise adopters:

■ Centralized controller (39% of respondents)

■ Fluid network architecture (27%)

■ Low-cost hardware (25%)

A decoupled control plane and data plane (13%) was tied with intent-based networking as the least important defining aspect of SDN solutions.

These top three responses from early adopters of SDN present a pretty simple definition of the technology. And when you think about it, these terms align what we’re seeing in the market place. Nearly every SDN solution has a centralized controller, or at least a centrally accessible, distributed controller. This controller serves as a single point of control, access, programmability and data collection for the network. Most solutions also offer low-cost hardware, or — in the case of overlays — require no new hardware.

Fluid network architecture, I would argue, gets to the heart of what SDN is all about. It enables networks that are flexible and responsive to changes in infrastructure conditions and business requirements. This contrasts sharply with static, highly manual legacy networks, where any change to network connectivity in a data center or a remote site can require days, weeks or even months to implement. SDN’s promise is a network that can respond to change quickly and fluidly, thanks to increased programmability, for instance.

Therefore, I defer to the wisdom of early adopters when trying to come with up a definition. SDN is characterized by a fluid network architecture that is enabled by a centralized controller and low-cost hardware.

One final point on the subject of defining SDN. We asked early adopters of software-defined WAN (SD-WAN) a similar but distinct question on the defining characteristics of SD-WAN, which EMA considers sufficiently different from other varieties of SDN to warrant its own definition. In the case of SD-WAN, cloud-based network and security services were the number one defining aspect of such solutions. Centralized control was the number two priority, followed by hybrid WAN connectivity.

Shamus McGillicuddy is Senior Analyst, Network Management at Enterprise Management Associates (EMA).

Hot Topics

The Latest

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 ... 

Most production autonomous agents do not run in a vacuum. They run inside cloud infrastructure: virtual machines, containers, pods, managed clusters or private servers. That is where most operations teams start monitoring. Is the VM alive? Is the container running? Did the pod restart? Is memory stable? Is CPU too high? Did the health check pass? Those signals are useful. They tell you whether the shell around the agent is alive. They do not tell you whether the agent inside is actually operational ...

Enterprise IT environments have never been more observable ... Yet many organizations still grapple with outages, lengthy incident resolution cycles, and increasing complexity. Most teams do not suffer from a shortage of data. They struggle to determine what deserves attention and what action to take next ... Enterprise IT operations must move beyond monitoring and visibility. The next stage of maturity is decision operations, an approach that helps teams make faster, better-informed decisions ...