NetDevOps Faces Cultural Hurdles Amidst Maturing Tools

As organizations navigate the intricacies of network automation, they face a looming challenge that's less about technology and more about human dynamics. While tools like Python and Ansible have stabilized their roles in network management, the human component remains a critical bottleneck. A recent survey highlights that nearly half of network professionals cite people-related issues as the primary obstacle to effective NetDevOps, revealing a stark contrast to the common assumption that technical implementations are the main hindrance.

The 44% Problem: Unpacking the Data

The findings from the 2025 State of Network Automation Survey are particularly telling. Out of 681 network professionals across 58 countries, a mere 10% pinpointed technical challenges as barriers to automation. In contrast, a hefty 44% highlighted issues stemming from people—whether due to skills gaps, organizational dysfunctions, or cultural resistance. This stark reality underscores the notion that the tech is ready; it's the organizational readiness that remains elusive.

The survey further emphasizes that almost half of organizations lack formal metrics to evaluate automation success. This absence cripples their ability to justify funding and initiatives, as proof-positive results cannot be showcased. The crux of the matter? Progressing in NetDevOps is less about mastering Python or other scripts and more about reshaping organizational culture and workflows.

The Myth of the Unicorn: Evolution, Not Perfection

There's a pervasive myth in the industry suggesting the need for "unicorn" hires—individuals possessing expertise in both networking and software development. However, this expectation may lead companies down a futile path. Instead, the more fruitful strategy lies in nurturing existing talent who can grow into their roles. Research from theCUBE suggests that prioritizing internal upskilling significantly outperforms reliance on new hires.

The survey indicates that 92% of automation development is executed by network engineers who specifically enhance their automation skills. This data is a crucial reminder: the necessary talent is already within reach and only needs the right environment to flourish. It’s not about reinventing the wheel but facilitating gradual evolution through hands-on experience.

Creating a Culture of Continuous Learning

Embracing a mindset shift is essential for organizations aiming to implement effective NetDevOps practices. Here are actionable insights to foster an environment that encourages continual learning and adaptation:

• Encourage on-the-job training: Automation skills blossom when real-world problems are tackled using novel tools. Organizations must be prepared for initial projects to consume more time than traditional methods, but this investment leads to long-term gains.
• Foster collaborative learning: Teams should facilitate partnerships rather than isolating individuals with advanced skills. By pairing seasoned experts with less-experienced engineers on projects, organizations can cultivate skill transfer within a collaborative framework.
• Recognize small victories: Celebrating incremental successes, such as the completion of a first automation script, bolsters motivation. Acknowledgment of these milestones contributes to momentum and engagement in further learning.

The Fundamental Shift: Data as the Foundation

Transitioning toward a NetDevOps model requires a fundamental rethinking of how data is treated within the network operations ecosystem. Traditionally, operational documentation has been seen as an afterthought, something to update post-changes. This outdated approach must yield to a proactive stance where adjustments are made in the data before propagating changes to the network via automation. Intel's Greg Botts succinctly encapsulates this mindset: "Start with your data, and everything falls out of that.”

However, establishing a "source of truth" can be a lengthy endeavor, often taking one to two years to solidify. Yet, this foundational work is non-negotiable—it consolidates fragmented information, cleanses years of drift, and sets the stage for future automation initiatives. Organizations with a clearly defined source of truth report nearly threefold improvement in achieving consistent automation outcomes. Yet, alarmingly, over half of surveyed professionals still lack this vital component, which critically undermines their attempts at adopting NetDevOps principles.

Documentation as Operation: A New Approach

Underpinning a successful NetDevOps initiative is the shift from a passive approach to one that considers data operationally. When data reflects operational intent rather than mere documentation, it redefines how network tasks are executed. As organizations embrace intent-driven methodologies, documentation no longer becomes an administrative chore but rather an integral part of network operations. Changes to the network originate from updates made to the source of truth, thus intertwining documentation directly with operational efficacy.

AI: Leveraging Technology When Ready

As we stand on the brink of broader AI adoption in network operations, it’s essential to stress that technology is only as effective as the infrastructure it operates within. AI promises transformative capabilities—such as natural language processing for data queries and generating automation code—but its deployment hinges on a solid operational foundation. Currently, the majority of network professionals have yet to embrace AI as a tool, with 45% lacking plans for integration, and only 3% having made any practical application.

Engineers' hesitation, rooted in caution cultivated from previous experiences of hasty rollouts, indicates a widespread demand for structured approaches to AI. Such frameworks, like the NIST AI Risk Management Framework, are emerging but have yet to be widely adopted, leaving many unprepared to fully harness AI's potential.

The Future of Work in Network Operations

The potential for NetDevOps is real and burgeoning. Early adopters are already witnessing enhanced operational efficiency, rapid response times, and cultivated workplace satisfaction. However, acknowledging the genuine challenges of this transformation is critical. The success of NetDevOps hinges not on mythical hires or perfect technologies but on evolving incumbent teams, refining data practices, and doing the essential groundwork that often remains unspoken.

As we move toward 2026, the focus will be on the individuals driving these changes—most of whom are already part of your teams, waiting for the opportunity to advance. The challenge will lie not only in technological adaptation but in reshaping organizational culture to create an environment ripe for evolution.