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5 Misconceptions About Network Automation Platforms (and why they should be re-thought)

Song Pang
NetBrain Technologies

As enterprise networks get more complex, encompassing on-prem, cloud and hybrid systems and applications, network automation is no longer optional. It's critical for uptime, security and scale. Yet persistent misconceptions about increasingly capable network automation platforms among the very NetOps professionals who would benefit the most from using them are holding back adoption. Here are 5 of the most common of those misconceptions, and why NetOps teams might want to re-think them.

Misconception 1: DIY scripting gives me more control than a platform

Network engineers love their own scripts and tools. According to recent research by the analyst firm EMA, 64% of enterprises still rely on homegrown scripts or open source tools. Many NetOps professionals believe that their time-worn DIY approach provides greater flexibility and customization than any platform can offer.

But the downside of relying on scripts is that it also creates silos, introduces gatekeeper effects and increases fragility. It's also a lot of work. According to EMA, more than 60% of teams spend more than 6 hours per week maintaining and debugging scripts and tools. The hodgepodge of scripts and tools creates complexity, often lacks documentation and can introduce security risks.

The reality is that modern network automation platforms don't take away control, they operationalize it by centralizing, securing, and making automation reusable across teams. Platforms are now designed to onboard existing scripts, extend them, and make them shareable. That provides control at scale.

Misconception 2: Automation is a risk to my job

Automation platforms, especially in the AI era, can sometimes be perceived as a threat to the livelihood of network professionals.

But rather than reduce their value, network operations platforms free NetOps teams from low-level toil and firefighting (think config pushes and compliance scans). That leaves them with more time to focus on higher priority tasks and projects like network design, security posture, and cross-team initiatives. And with their low code/no code capabilities, network automation platforms can broaden access beyond scripting gatekeepers and create a career path for other professionals.

In an environment where many NetOps teams are being asked to do more with less, automation expands NetOps influence, future-proofs careers, and reduces burnout.

Misconception 3: An automation platform won't save me time because it's not reliable

In addition to their concerns about control, many NetOps teams rely on scripts and open source tools because they simply don't trust network automation platforms. They believe them to be fragile, error-prone, and more hassle than help.

But, as noted above, teams can spend anywhere from 6-10 hours per week debugging scripts, according to EMA. So, those unsupported scripts and code-heavy tools are not themselves inherently reliable.

Network automation platforms, by contrast, provide testing, dashboards, CI/CD principles, and role-based access. reducing error risk and improving consistency. For common tasks like automating config changes, onboarding, compliance scans, and firmware updates, network automation platforms are faster and more accurate than a human-driven scripting process.

Misconception 4: Network automation platforms are too costly and the ROI isn't clear

The cost of a network automation platform can seem high when judged against free homemade scripts or open source tools. But NetOps teams often struggle to quantify the hidden costs of DIY solutions. Whether it's time lost to debugging, finding and fixing security risks, the opportunity cost of having highly skilled professionals performing routine tasks, or, in the worst case scenario, network downtime, the DIY approach is anything but free.

Network automation platforms deliver real and quantifiable ROI. Platforms provide 24x7 automation that no human can match. They offer dashboards that can accurately track time saved and enhance cross-team visibility. And, most importantly, they ultimately justify their cost by reducing downtime.

The ROI of network automation platforms over DIY solutions becomes much clearer when measured in operational risk reduction, uptime, and freeing talent for strategic projects.

Misconception 5: It's just another hard-to-learn tool I'll have to manage

Tool sprawl is a real issue for NetOps teams. So it's understandable that they'd be reluctant to learn and manage yet another application.

But when you dig deeper, it turns out that what most (64% according to EMA) network professionals value are tools that are easy to use, with low code/no code capabilities that flatten the learning curve for both deeply experienced and less experienced engineers. And that's what modern network automation platforms offer. Layer on features like auto-discovery, pre-built network assessments, drag-and-drop workflows, and script onboarding and the time to value from a network automation platform for NetOps teams is fairly short. Modern platforms also integrate with IT service management (ITSM), IPAM and Git rather than replacing them, so NetOps teams can continue to use the workflows they've built.

In short, network automation platforms don't make things harder and more complex for NetOps teams. They simplify environments by consolidating fragmented DIY efforts into one system that both coders and non-coders can use.

It's time to re-think DIY

Network operations teams can be understandably reluctant to switch from the scripts and tools they've built on their own to a network automation platform. After all, ensuring the reliability and integrity of their organization's network is a business critical responsibility. Yet it only takes a bit of digging before the inefficiencies and risks of the DIY approach become apparent, especially at enterprise scale. Network automation platforms have become much more capable in recent years, providing a degree of flexibility and control that might surprise NetOps teams. NetOps leaders who might be hesitant to take the plunge can start with a hybrid approach, onboarding existing scripts into platforms before scaling with low-code/no code workflows. The benefits — in terms of reduced toil, improved reliability, better visibility and better utilization of talent and resources — are well worth the effort. 

Song Pang is CTO at NetBrain Technologies

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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 ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...

5 Misconceptions About Network Automation Platforms (and why they should be re-thought)

Song Pang
NetBrain Technologies

As enterprise networks get more complex, encompassing on-prem, cloud and hybrid systems and applications, network automation is no longer optional. It's critical for uptime, security and scale. Yet persistent misconceptions about increasingly capable network automation platforms among the very NetOps professionals who would benefit the most from using them are holding back adoption. Here are 5 of the most common of those misconceptions, and why NetOps teams might want to re-think them.

Misconception 1: DIY scripting gives me more control than a platform

Network engineers love their own scripts and tools. According to recent research by the analyst firm EMA, 64% of enterprises still rely on homegrown scripts or open source tools. Many NetOps professionals believe that their time-worn DIY approach provides greater flexibility and customization than any platform can offer.

But the downside of relying on scripts is that it also creates silos, introduces gatekeeper effects and increases fragility. It's also a lot of work. According to EMA, more than 60% of teams spend more than 6 hours per week maintaining and debugging scripts and tools. The hodgepodge of scripts and tools creates complexity, often lacks documentation and can introduce security risks.

The reality is that modern network automation platforms don't take away control, they operationalize it by centralizing, securing, and making automation reusable across teams. Platforms are now designed to onboard existing scripts, extend them, and make them shareable. That provides control at scale.

Misconception 2: Automation is a risk to my job

Automation platforms, especially in the AI era, can sometimes be perceived as a threat to the livelihood of network professionals.

But rather than reduce their value, network operations platforms free NetOps teams from low-level toil and firefighting (think config pushes and compliance scans). That leaves them with more time to focus on higher priority tasks and projects like network design, security posture, and cross-team initiatives. And with their low code/no code capabilities, network automation platforms can broaden access beyond scripting gatekeepers and create a career path for other professionals.

In an environment where many NetOps teams are being asked to do more with less, automation expands NetOps influence, future-proofs careers, and reduces burnout.

Misconception 3: An automation platform won't save me time because it's not reliable

In addition to their concerns about control, many NetOps teams rely on scripts and open source tools because they simply don't trust network automation platforms. They believe them to be fragile, error-prone, and more hassle than help.

But, as noted above, teams can spend anywhere from 6-10 hours per week debugging scripts, according to EMA. So, those unsupported scripts and code-heavy tools are not themselves inherently reliable.

Network automation platforms, by contrast, provide testing, dashboards, CI/CD principles, and role-based access. reducing error risk and improving consistency. For common tasks like automating config changes, onboarding, compliance scans, and firmware updates, network automation platforms are faster and more accurate than a human-driven scripting process.

Misconception 4: Network automation platforms are too costly and the ROI isn't clear

The cost of a network automation platform can seem high when judged against free homemade scripts or open source tools. But NetOps teams often struggle to quantify the hidden costs of DIY solutions. Whether it's time lost to debugging, finding and fixing security risks, the opportunity cost of having highly skilled professionals performing routine tasks, or, in the worst case scenario, network downtime, the DIY approach is anything but free.

Network automation platforms deliver real and quantifiable ROI. Platforms provide 24x7 automation that no human can match. They offer dashboards that can accurately track time saved and enhance cross-team visibility. And, most importantly, they ultimately justify their cost by reducing downtime.

The ROI of network automation platforms over DIY solutions becomes much clearer when measured in operational risk reduction, uptime, and freeing talent for strategic projects.

Misconception 5: It's just another hard-to-learn tool I'll have to manage

Tool sprawl is a real issue for NetOps teams. So it's understandable that they'd be reluctant to learn and manage yet another application.

But when you dig deeper, it turns out that what most (64% according to EMA) network professionals value are tools that are easy to use, with low code/no code capabilities that flatten the learning curve for both deeply experienced and less experienced engineers. And that's what modern network automation platforms offer. Layer on features like auto-discovery, pre-built network assessments, drag-and-drop workflows, and script onboarding and the time to value from a network automation platform for NetOps teams is fairly short. Modern platforms also integrate with IT service management (ITSM), IPAM and Git rather than replacing them, so NetOps teams can continue to use the workflows they've built.

In short, network automation platforms don't make things harder and more complex for NetOps teams. They simplify environments by consolidating fragmented DIY efforts into one system that both coders and non-coders can use.

It's time to re-think DIY

Network operations teams can be understandably reluctant to switch from the scripts and tools they've built on their own to a network automation platform. After all, ensuring the reliability and integrity of their organization's network is a business critical responsibility. Yet it only takes a bit of digging before the inefficiencies and risks of the DIY approach become apparent, especially at enterprise scale. Network automation platforms have become much more capable in recent years, providing a degree of flexibility and control that might surprise NetOps teams. NetOps leaders who might be hesitant to take the plunge can start with a hybrid approach, onboarding existing scripts into platforms before scaling with low-code/no code workflows. The benefits — in terms of reduced toil, improved reliability, better visibility and better utilization of talent and resources — are well worth the effort. 

Song Pang is CTO at NetBrain Technologies

Hot Topics

The Latest

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 ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...