The traditional role of the network engineer is undergoing a fundamental and irreversible transformation, driven by the relentless expansion of network scale and the ever-increasing complexity of modern IT infrastructures. As manual, command-line-driven management becomes increasingly unsustainable in the face of these challenges, a new and powerful discipline known as NetDevOps is emerging from the intersection of network engineering and software development. This practice merges the deep domain knowledge of networking with the core principles of DevOps, such as continuous integration and continuous deployment, to treat the network as a fully programmable system. The ultimate goal is to manage the entire network lifecycle through code, a shift that requires not just new tools but a profound evolution in the skills, mindset, and operational models of existing network teams. This is not about replacing network engineers but empowering them to build, automate, and manage the resilient, agile networks of the future.
The Inevitable Push Towards Automation
The widespread shift to NetDevOps is not a matter of choice or a passing trend but a direct and necessary response to overwhelming operational pressures that have pushed traditional network management methods past their breaking point. Recent industry data reveals a critical state of affairs, with a vast majority of organizations—around 95%—suffering from significant visibility gaps across their networks, making proactive management nearly impossible. Furthermore, over a third of enterprises cite a lack of modern networking expertise as a major roadblock, while more than a quarter report that their initial automation efforts have completely stalled, failing to deliver on their initial promise. This situation is compounded by the fact that network teams are now expected to support incredibly demanding and complex initiatives, including artificial intelligence workloads and sophisticated multi-cloud architectures, often with stagnant or even shrinking headcounts. This widening gap between expectations and capabilities is forcing a fundamental reevaluation of how networks are designed, deployed, and maintained, making automation an essential survival strategy rather than a luxury.
This pressing need for a new operational model is perfectly illustrated by the real-world challenges faced at major technology enterprises, where the scale of network infrastructure has grown exponentially while the size of the engineering teams has remained flat or even decreased. In one notable example, a team of just twenty engineers was responsible for managing approximately 3,000 network devices a few years ago. By 2025, that ratio had dramatically shifted, with only thirteen engineers tasked with overseeing a sprawling network of 5,500 devices. Such an imbalance renders manual, device-by-device configuration through the command-line interface (CLI) completely untenable. Relying on outdated practices like manually copying and pasting configurations from a text file is not only incredibly inefficient but also introduces a significant risk of human error, leading to outages and security vulnerabilities. In this high-stakes environment, the clear and urgent mandate for modern network teams has become “automate or die,” as relying on manual processes is no longer a viable strategy for maintaining a robust, secure, and scalable network.
The Practical Journey to a Code-Driven Network
The adoption of NetDevOps is rarely a sudden, revolutionary overhaul; instead, it is typically an incremental and pragmatic journey that begins with small, achievable goals. Most organizations, nearly 70% according to industry research, start their automation efforts modestly by focusing on task-level scripting. This initial phase involves using accessible and powerful tools like Ansible or Python to automate the most repetitive, time-consuming, and low-level tasks that bog down network engineers in their daily work. Common starting points include standardizing the provisioning of new devices, executing routine configuration changes across multiple switches or routers, or performing simple data collection for compliance audits. This “low-hanging fruit” approach is highly effective because it provides immediate, tangible value by freeing up engineer time, reduces the chance of manual errors in common procedures, and, perhaps most importantly, builds the team’s confidence and skills in using automation tools, paving the way for more ambitious projects.
As teams gain experience and see the benefits of initial automation, they naturally progress toward more structured, reliable, and scalable practices borrowed directly from the world of software development. This second stage of maturity involves adopting a more disciplined approach to managing network configurations as code. A critical step is the implementation of a version control system like Git, which allows teams to meticulously track every change, review modifications before they are applied, and easily roll back to a previous state if an issue arises. Concurrently, teams begin to define and enforce “golden configurations,” which serve as standardized, validated templates for different device roles, ensuring consistency across the infrastructure. This phase also sees the introduction of basic validation checks, where automated scripts are run before and after deploying a change to verify that the network is in the expected state and that the modification did not cause any unintended side effects, bringing a new level of discipline and predictability to network operations.
Redefining the Foundation Data as the Source of Truth
A core tenet of a mature and successful NetDevOps practice involves a profound and fundamental shift in operational thinking: the network’s intended state must be defined by a centralized and authoritative data model, not by the live configurations running on individual devices. In this advanced paradigm, this data model becomes the single “source of truth,” serving as the foundation for all network operations and automation. The guiding principle is simple yet powerful: “Start with your data, and everything else follows.” Instead of an engineer logging into a router to make a change, the change is first made to the source of truth—perhaps a database or a set of structured data files. From there, automated pipelines read this updated information, generate the necessary device-specific configurations, and push those changes to the network. This approach completely inverts the traditional workflow, where documentation and inventory systems perpetually struggled to keep up with the actual state of the network, ensuring that the intended state and the deployed state are always in sync.
Despite its clear advantages, establishing this foundational source of truth is often the most significant and time-consuming hurdle in an organization’s NetDevOps journey. Many enterprises find that their critical network data is of poor quality, outdated, and scattered across numerous disparate and siloed systems, including spreadsheets, legacy inventory tools, and wiki pages. The process of discovering, consolidating, cleaning, and structuring this information into a cohesive and reliable data model that can be accessed via APIs is a critical prerequisite for any meaningful automation. This foundational work can easily take a year or more to complete but is an essential investment. Research confirms its importance, showing that organizations with a clearly defined and well-maintained source of truth are nearly three times more likely to achieve consistent and successful automation outcomes. A primary goal of this data-driven model is to proactively control “configuration drift”—the inevitable and often dangerous variance between the intended state defined in the source of truth and the actual running configuration on a device.
The New Skillset Building Talent from Within
The transition to NetDevOps had fundamentally altered the skill requirements for network professionals, blending traditional networking expertise with software development practices. Deep knowledge of routing protocols, failure-domain design, and security fundamentals remained indispensable, serving as the bedrock upon which all automation was built. However, this evolution enhanced rather than replaced that foundation. Success now hinged on developing fluency with Git-based workflows, understanding structured data formats like YAML and JSON, and mastering automation tools such as Ansible and Python. A working knowledge of APIs became essential for interacting with network devices and management systems programmatically. Furthermore, concepts that were once the exclusive domain of software engineering, such as automated testing, streaming telemetry for real-time visibility, and a broader sense of observability, became central to the modern network engineer’s toolkit. This blend of skills defined the future of the profession.
Looking back, the most successful enterprises discovered that the best strategy was to build this talent from within rather than attempting to hire pre-made NetDevOps experts. The most effective approach proved to be a hybrid one: investing heavily in training and upskilling experienced network engineers on automation concepts while selectively hiring individuals with strong DevOps or software backgrounds to architect robust tooling and instill best practices across the team. This evolution redefined the daily work of a network engineer. Instead of spending hours on manual device configurations, their focus shifted to higher-value activities like designing, reviewing, and validating network changes through code and automated pipelines. High-performing infrastructure teams were found to spend significantly more time on these proactive design and verification activities compared to their less-automated peers, who remained mired in reactive troubleshooting. This strategic upskilling ultimately transformed the network operations function from a cost center focused on maintenance to a strategic enabler of business agility and innovation.
