Skip to main content

Network Automation Enables DevOps Programmability

Shamus McGillicuddy

Nearly 97% of DevOps teams are integrating their orchestration solutions with network automation tools, according to new research from Enterprise Management Associates (EMA).

EMA recently published The Future of Data Center Network Automation, a report based on a survey of 359 enterprises and services providers. The survey explored technology strategies and challenges for automating data center networks.

Integration between data center network automation tools and DevOps tools are nearly universal, but the depth of that integration varies. More than 50% of companies have or plan to have only loose integration between NetOps and DevOps automation, meaning that many NetOps teams are limiting the extent of network programmability that they offer to DevOps.

This conservative approach may mitigate risk, but it could be shortsighted. DevOps groups require agility to achieve their goals. When network engineers limit network programmability, they will inevitably have to respond to a larger number of change tickets from DevOps, leading to human latency in overall operations. Network engineers may maintain more control over how the network operates, but it comes at the expense of agility.

More than 46% of networks teams have or plan to implement tight integration between NetOps and DevOps automation, meaning that they are going to allow DevOps to program most or all aspects of their data center networks. This approach is most popular with best-in-class data center network automation strategies, suggesting that it is a best practice.

Network Automation Strategies are Cloud and DevOps Centric

The typical data center network automation strategy is multi-tool. More than 48% of network teams use two tools for network automation, and 45% use three or more. Quite often, DevOps tools are part of the picture, not just something to be integrated with. More than 42% of network teams use DevOps automation or infrastructure-as-code tools as one of their network automation solutions. DevOps tools are most popular as a network automation solution in companies that have many data centers (11 or more).

Beyond DevOps integration, EMA research found that most companies are thinking about how their data center network automation tools fit into their overall hybrid cloud architecture. Nearly 78% of companies require that their data center network automation tools be extensible to public cloud environments, thus allowing the orchestration of network automation across both data centers and clouds. This requirement is more common among best-in-class companies, against suggesting that it is a best practice.

"The push toward the cloud is one thing that is driving our [data center] network automation," a network automation engineer with a $3 billion retailer told EMA. "With day-to-day operations, we want to be able to provide our new cloud applications with access to resources that are sitting in a data center."

EMA's research is clear. As network engineering teams formulate a plan for data center network automation, DevOps and cloud will be a major factor. If you have a DevOps team, you must be prepared to integrate your network automation solutions with the DevOps toolset. You should also consider how your network automation strategy will be extensible to public cloud environments. And DevOps tools may offer solutions to some of your network automation requirements.

The Latest

64% of enterprise networking teams use internally developed software or scripts for network automation, but 61% of those teams spend six or more hours per week debugging and maintaining them, according to From Scripts to Platforms: Why Homegrown Tools Dominate Network Automation and How Vendors Can Help, my latest EMA report ...

Cloud computing has transformed how we build and scale software, but it has also quietly introduced one of the most persistent challenges in modern IT: cost visibility and control ... So why, after more than a decade of cloud adoption, are cloud costs still spiraling out of control? The answer lies not in tooling but in culture ...

CEOs are committed to advancing AI solutions across their organization even as they face challenges from accelerating technology adoption, according to the IBM CEO Study. The survey revealed that executive respondents expect the growth rate of AI investments to more than double in the next two years, and 61% confirm they are actively adopting AI agents today and preparing to implement them at scale ...

Image
IBM

 

A major architectural shift is underway across enterprise networks, according to a new global study from Cisco. As AI assistants, agents, and data-driven workloads reshape how work gets done, they're creating faster, more dynamic, more latency-sensitive, and more complex network traffic. Combined with the ubiquity of connected devices, 24/7 uptime demands, and intensifying security threats, these shifts are driving infrastructure to adapt and evolve ...

Image
Cisco

The development of banking apps was supposed to provide users with convenience, control and piece of mind. However, for thousands of Halifax customers recently, a major mobile outage caused the exact opposite, leaving customers unable to check balances, or pay bills, sparking widespread frustration. This wasn't an isolated incident ... So why are these failures still happening? ...

Cyber threats are growing more sophisticated every day, and at their forefront are zero-day vulnerabilities. These elusive security gaps are exploited before a fix becomes available, making them among the most dangerous threats in today's digital landscape ... This guide will explore what these vulnerabilities are, how they work, why they pose such a significant threat, and how modern organizations can stay protected ...

The prevention of data center outages continues to be a strategic priority for data center owners and operators. Infrastructure equipment has improved, but the complexity of modern architectures and evolving external threats presents new risks that operators must actively manage, according to the Data Center Outage Analysis 2025 from Uptime Institute ...

As observability engineers, we navigate a sea of telemetry daily. We instrument our applications, configure collectors, and build dashboards, all in pursuit of understanding our complex distributed systems. Yet, amidst this flood of data, a critical question often remains unspoken, or at best, answered by gut feeling: "Is our telemetry actually good?" ... We're inviting you to participate in shaping a foundational element for better observability: the Instrumentation Score ...

We're inching ever closer toward a long-held goal: technology infrastructure that is so automated that it can protect itself. But as IT leaders aggressively employ automation across our enterprises, we need to continuously reassess what AI is ready to manage autonomously and what can not yet be trusted to algorithms ...

Much like a traditional factory turns raw materials into finished products, the AI factory turns vast datasets into actionable business outcomes through advanced models, inferences, and automation. From the earliest data inputs to the final token output, this process must be reliable, repeatable, and scalable. That requires industrializing the way AI is developed, deployed, and managed ...

Network Automation Enables DevOps Programmability

Shamus McGillicuddy

Nearly 97% of DevOps teams are integrating their orchestration solutions with network automation tools, according to new research from Enterprise Management Associates (EMA).

EMA recently published The Future of Data Center Network Automation, a report based on a survey of 359 enterprises and services providers. The survey explored technology strategies and challenges for automating data center networks.

Integration between data center network automation tools and DevOps tools are nearly universal, but the depth of that integration varies. More than 50% of companies have or plan to have only loose integration between NetOps and DevOps automation, meaning that many NetOps teams are limiting the extent of network programmability that they offer to DevOps.

This conservative approach may mitigate risk, but it could be shortsighted. DevOps groups require agility to achieve their goals. When network engineers limit network programmability, they will inevitably have to respond to a larger number of change tickets from DevOps, leading to human latency in overall operations. Network engineers may maintain more control over how the network operates, but it comes at the expense of agility.

More than 46% of networks teams have or plan to implement tight integration between NetOps and DevOps automation, meaning that they are going to allow DevOps to program most or all aspects of their data center networks. This approach is most popular with best-in-class data center network automation strategies, suggesting that it is a best practice.

Network Automation Strategies are Cloud and DevOps Centric

The typical data center network automation strategy is multi-tool. More than 48% of network teams use two tools for network automation, and 45% use three or more. Quite often, DevOps tools are part of the picture, not just something to be integrated with. More than 42% of network teams use DevOps automation or infrastructure-as-code tools as one of their network automation solutions. DevOps tools are most popular as a network automation solution in companies that have many data centers (11 or more).

Beyond DevOps integration, EMA research found that most companies are thinking about how their data center network automation tools fit into their overall hybrid cloud architecture. Nearly 78% of companies require that their data center network automation tools be extensible to public cloud environments, thus allowing the orchestration of network automation across both data centers and clouds. This requirement is more common among best-in-class companies, against suggesting that it is a best practice.

"The push toward the cloud is one thing that is driving our [data center] network automation," a network automation engineer with a $3 billion retailer told EMA. "With day-to-day operations, we want to be able to provide our new cloud applications with access to resources that are sitting in a data center."

EMA's research is clear. As network engineering teams formulate a plan for data center network automation, DevOps and cloud will be a major factor. If you have a DevOps team, you must be prepared to integrate your network automation solutions with the DevOps toolset. You should also consider how your network automation strategy will be extensible to public cloud environments. And DevOps tools may offer solutions to some of your network automation requirements.

The Latest

64% of enterprise networking teams use internally developed software or scripts for network automation, but 61% of those teams spend six or more hours per week debugging and maintaining them, according to From Scripts to Platforms: Why Homegrown Tools Dominate Network Automation and How Vendors Can Help, my latest EMA report ...

Cloud computing has transformed how we build and scale software, but it has also quietly introduced one of the most persistent challenges in modern IT: cost visibility and control ... So why, after more than a decade of cloud adoption, are cloud costs still spiraling out of control? The answer lies not in tooling but in culture ...

CEOs are committed to advancing AI solutions across their organization even as they face challenges from accelerating technology adoption, according to the IBM CEO Study. The survey revealed that executive respondents expect the growth rate of AI investments to more than double in the next two years, and 61% confirm they are actively adopting AI agents today and preparing to implement them at scale ...

Image
IBM

 

A major architectural shift is underway across enterprise networks, according to a new global study from Cisco. As AI assistants, agents, and data-driven workloads reshape how work gets done, they're creating faster, more dynamic, more latency-sensitive, and more complex network traffic. Combined with the ubiquity of connected devices, 24/7 uptime demands, and intensifying security threats, these shifts are driving infrastructure to adapt and evolve ...

Image
Cisco

The development of banking apps was supposed to provide users with convenience, control and piece of mind. However, for thousands of Halifax customers recently, a major mobile outage caused the exact opposite, leaving customers unable to check balances, or pay bills, sparking widespread frustration. This wasn't an isolated incident ... So why are these failures still happening? ...

Cyber threats are growing more sophisticated every day, and at their forefront are zero-day vulnerabilities. These elusive security gaps are exploited before a fix becomes available, making them among the most dangerous threats in today's digital landscape ... This guide will explore what these vulnerabilities are, how they work, why they pose such a significant threat, and how modern organizations can stay protected ...

The prevention of data center outages continues to be a strategic priority for data center owners and operators. Infrastructure equipment has improved, but the complexity of modern architectures and evolving external threats presents new risks that operators must actively manage, according to the Data Center Outage Analysis 2025 from Uptime Institute ...

As observability engineers, we navigate a sea of telemetry daily. We instrument our applications, configure collectors, and build dashboards, all in pursuit of understanding our complex distributed systems. Yet, amidst this flood of data, a critical question often remains unspoken, or at best, answered by gut feeling: "Is our telemetry actually good?" ... We're inviting you to participate in shaping a foundational element for better observability: the Instrumentation Score ...

We're inching ever closer toward a long-held goal: technology infrastructure that is so automated that it can protect itself. But as IT leaders aggressively employ automation across our enterprises, we need to continuously reassess what AI is ready to manage autonomously and what can not yet be trusted to algorithms ...

Much like a traditional factory turns raw materials into finished products, the AI factory turns vast datasets into actionable business outcomes through advanced models, inferences, and automation. From the earliest data inputs to the final token output, this process must be reliable, repeatable, and scalable. That requires industrializing the way AI is developed, deployed, and managed ...