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Software Defined Networking: A New Approach to Delivering Business Agility

Software defined networking (SDN) is creating a lot of excitement in data centers, but current technology is still relatively immature.

In the new research note Ending The Confusion Around Software Defined Networking (SDN): A Taxonomy, Joe Skorupa, VP and distinguished analyst at Gartner, explains that SDN is not only limited to data center and service provider networks.

Skorupa answered some questions around the current state of SDN and how it will evolve:

Q: What is Software Defined Networking?

A: SDN is a new approach to designing, building and operating networks that supports business agility. SDN brings a similar degree of agility to networks that abstraction, virtualization and orchestration have brought to server infrastructure.

In the SDN architecture, the control and data planes are decoupled, network intelligence and state are logically centralized, and the underlying network infrastructure is abstracted from network applications and features. In addition, programmability enables external control and automation that allow for highly scalable, flexible networks that readily adapt to changing business needs.

While a great deal of attention has been directed toward SDN in data center networks and service provider networks, it can also be applied to campus networks and, enterprise WANs. The applicability and benefits will vary by use case.

Q: What Models Exist for SDN Deployment?

A: Three deployment approaches are possible - switched-based, overlay and hybrid. For greenfield deployments, particularly when the cost of physical infrastructure and multi-vendor options are important, a switch-based model will be common. The biggest limitation to this approach is that is currently does not leverage existing L2/3 network equipment.

When rapid deployment over an existing IP network, or when responsibility for the SDN environment is assigned to the server virtualization team, a tunnel-based overlay approach may be appropriate. With this approach the SDN endpoints are virtual devices that are part of the hypervisor environment. The greatest limitations of this approach are that it does not address the overhead of managing the underlying infrastructure, de-bugging problems in an overlay can be complex and it does not support bare metal hosts.

The third approach combines the first two into a hybrid deployment. This allows a non-disruptive migration with a path toward an eventual switch-based design. Gateways link devices that do not natively support overlay tunnels, such as bare metal servers.

Q: Where might SDN be Leveraged?

A: In a data center context, SDN is a component of the Policy Driven Data Center. It provides the programmable connectivity required to link the network to other components within the data center delivering a more integrated, functional system. For example, a provisioning application could specify that an instance of the CRM application must have certain services delivered in a specific sequence and would ensure that the traffic flows through the appropriate devices in the correct sequence.

In a service provider context SDN might be leveraged to provide a common control plane across multiple vendors equipment including SGSN/GGSN, PE router, session border controller, core router, optical transport/WDM nodes to build an agile, multi-tenant network that is a platform for value added services. Possible service offering could include flexible bandwidth on demand, patch protection/restoration and multi-casting. SDN promises easier integration with OSS/BSS to increase service agility while reducing CapEx and OpEx.

How Can I Decide if SDN is Right for My Organization?

- Begin to explore the potential benefits and risks that SDN will bring to your organization, but beware of SDN-washing which simply re-labels legacy approaches with the latest buzzwords.

- Be aware that SDN has significant potential impacts on security. Your security strategy must evolve with the SDN strategy to incorporate new needs and opportunities brought on by SDN.

- If you focus on the data center network first, be sure to involve server, virtualization, security and storage teams in the discussion to ensure a single approach is adopted.

- The adoption of SDN requires a new way of thinking that may threaten existing network engineers. Identify members of your team with the skills and vision to lead the evaluation process

Related Links:

Download a complimentary copy of the Gartner report: Ending The Confusion Around Software Defined Networking (SND): A Taxonomy

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Software Defined Networking: A New Approach to Delivering Business Agility

Software defined networking (SDN) is creating a lot of excitement in data centers, but current technology is still relatively immature.

In the new research note Ending The Confusion Around Software Defined Networking (SDN): A Taxonomy, Joe Skorupa, VP and distinguished analyst at Gartner, explains that SDN is not only limited to data center and service provider networks.

Skorupa answered some questions around the current state of SDN and how it will evolve:

Q: What is Software Defined Networking?

A: SDN is a new approach to designing, building and operating networks that supports business agility. SDN brings a similar degree of agility to networks that abstraction, virtualization and orchestration have brought to server infrastructure.

In the SDN architecture, the control and data planes are decoupled, network intelligence and state are logically centralized, and the underlying network infrastructure is abstracted from network applications and features. In addition, programmability enables external control and automation that allow for highly scalable, flexible networks that readily adapt to changing business needs.

While a great deal of attention has been directed toward SDN in data center networks and service provider networks, it can also be applied to campus networks and, enterprise WANs. The applicability and benefits will vary by use case.

Q: What Models Exist for SDN Deployment?

A: Three deployment approaches are possible - switched-based, overlay and hybrid. For greenfield deployments, particularly when the cost of physical infrastructure and multi-vendor options are important, a switch-based model will be common. The biggest limitation to this approach is that is currently does not leverage existing L2/3 network equipment.

When rapid deployment over an existing IP network, or when responsibility for the SDN environment is assigned to the server virtualization team, a tunnel-based overlay approach may be appropriate. With this approach the SDN endpoints are virtual devices that are part of the hypervisor environment. The greatest limitations of this approach are that it does not address the overhead of managing the underlying infrastructure, de-bugging problems in an overlay can be complex and it does not support bare metal hosts.

The third approach combines the first two into a hybrid deployment. This allows a non-disruptive migration with a path toward an eventual switch-based design. Gateways link devices that do not natively support overlay tunnels, such as bare metal servers.

Q: Where might SDN be Leveraged?

A: In a data center context, SDN is a component of the Policy Driven Data Center. It provides the programmable connectivity required to link the network to other components within the data center delivering a more integrated, functional system. For example, a provisioning application could specify that an instance of the CRM application must have certain services delivered in a specific sequence and would ensure that the traffic flows through the appropriate devices in the correct sequence.

In a service provider context SDN might be leveraged to provide a common control plane across multiple vendors equipment including SGSN/GGSN, PE router, session border controller, core router, optical transport/WDM nodes to build an agile, multi-tenant network that is a platform for value added services. Possible service offering could include flexible bandwidth on demand, patch protection/restoration and multi-casting. SDN promises easier integration with OSS/BSS to increase service agility while reducing CapEx and OpEx.

How Can I Decide if SDN is Right for My Organization?

- Begin to explore the potential benefits and risks that SDN will bring to your organization, but beware of SDN-washing which simply re-labels legacy approaches with the latest buzzwords.

- Be aware that SDN has significant potential impacts on security. Your security strategy must evolve with the SDN strategy to incorporate new needs and opportunities brought on by SDN.

- If you focus on the data center network first, be sure to involve server, virtualization, security and storage teams in the discussion to ensure a single approach is adopted.

- The adoption of SDN requires a new way of thinking that may threaten existing network engineers. Identify members of your team with the skills and vision to lead the evaluation process

Related Links:

Download a complimentary copy of the Gartner report: Ending The Confusion Around Software Defined Networking (SND): A Taxonomy

Hot Topics

The Latest

If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

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 ...