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The Role of Automation in Network Operations Isn't What You Think

Song Pang
NetBrain Technologies

Nearly all CIOs have seen IT automation projects get derailed, often because they try to do too much. But the IT skills gaps, layoffs or flat budgets and the increasing complexity of networks, automation is often the only way to scale up network management processes. Changes in technology have made network automation much more accessible to the point that there are low-code and no-code options available.

Any repetitive network management tasks can, and arguably should, be automated. Here are four examples of tasks that can be automated successfully with today's technology.

Task 1: Making network documentation more accurate and comprehensive

Network documentation is essential for a variety of reasons, but large enterprise networks change so quickly that documentation goes out of date almost as soon as it's completed. And more troubling, documentation that simply identifies device connectivity is simply not enough in an era of multi-vendor and multi-cloud digital infrastructures.

Documentation must have the ability to guide network engineers more intelligently as they solve service problems, which requires a clear understanding of all the device operating conditions (physical and virtual), the connection topology of devices, how traffic flows bi-directionally and the desired behaviors that results. And this all must be available at the touch of a button. Network automation is the perfect platform to enable this, since it can work in the background constantly maintaining this multi-facet model of any network in near real-time.

Task 2: Proactively looking for anomalous conditions such as outdated configurations or insecure passwords

Every network has a set of architectures that have been defined to support the business and its mission critical applications. By using no-code approaches to allow any engineer to translate the parameters of these architectures into validation logic, automation can be leveraged to execute verifications at scale.

By doing so, most network problems can be detected and corrected before they materially affect production services. These problem types range from available capacity and service delivery performance to security management and resilience. Device passwords must always be verified to be secure; failover links must be tested to assure they are available during times of stress; and device configurations must be tested to make sure required operating parameters are in effect. These and a hundred other scenarios can be crafted through automation to establish and maintain confidence in the operating baseline.

Task 3: The workflows associated with network troubleshooting

In every enterprise and MSP, there is a constant stream of operational service tasks, or tickets, that must be handled. The resolution of each of these tickets typically requires a set of repetitive steps that must be executed each time manually. And to make matters worse, the same service task being handled by different network engineers may be using completely different sets of steps based on their level of expertise and experience. The result is vastly inconsistent remedies.

Automation can capture the best practices for the majority of problem types and then make those available to engineers across the planet. And since those steps are repetitive, what may have taken hours to execute by hand may take minutes to execute by machine. Network engineers can leverage automation to run this golden set of diagnostics quickly, allowing them to focus on the harder networking issues which may be infrequent or deeply complex. This use of automation for troubleshooting results in lower MTTR, fewer tickets, faster MTTI, and improved resource management.

Task 4: Creating a more secure Change Management environment

Change is one of the most critical aspects of keeping every digital infrastructure up and running and in direct support of the business. And while there have been countless change management solutions over the years from more than a hundred vendors, they all lack the ability to understand the service delivery aspects of change, and they lack the ability to automatically verify that the change was not only completed successfully, but the results were as expected. Simply put, traditional change management solutions may successfully enable device changes to be made, but without an automated way to verify business service impacts, the business itself may suffer unforeseen dependencies.

A strong understanding of the network using a comprehensive digital twin coupled with an automation engine that can provide the means to verify the business services that traverse each and every device, both before and after change is made, is an entirely new way of thinking about change management- in the context of business service delivery, rather than device health.

Ensuring critical applications and IT services perform well is key to the operation and success of any business. No-code network automation enables fundamental change to long-established yet manual workflows, and in doing so, provides a level of consistency and operational performance never previously imagined. Network automation eliminates the tedium found in current processes and reduces the reliance on labor intensive tasks which are repetitive in nature. Network engineers can now rely on automation to handle the first two-thirds of the remedial work that they would otherwise manually do, allowing them to focus on more strategic and forward-looking work.

In broad strokes, automating NetOps enables outage prevention (which preserves the company's livelihood), troubleshooting scale (which saves time and money), application services to be delivered as needed (which increases revenue), network security to be continuously verified (which protects the business), and protected change (which eliminates the unintended consequences typically associated with change). Network automation can elevate network operations from tactical to strategic and bring simplicity and efficiency to NetOps teams.

Song Pang is CTO at NetBrain Technologies

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The Role of Automation in Network Operations Isn't What You Think

Song Pang
NetBrain Technologies

Nearly all CIOs have seen IT automation projects get derailed, often because they try to do too much. But the IT skills gaps, layoffs or flat budgets and the increasing complexity of networks, automation is often the only way to scale up network management processes. Changes in technology have made network automation much more accessible to the point that there are low-code and no-code options available.

Any repetitive network management tasks can, and arguably should, be automated. Here are four examples of tasks that can be automated successfully with today's technology.

Task 1: Making network documentation more accurate and comprehensive

Network documentation is essential for a variety of reasons, but large enterprise networks change so quickly that documentation goes out of date almost as soon as it's completed. And more troubling, documentation that simply identifies device connectivity is simply not enough in an era of multi-vendor and multi-cloud digital infrastructures.

Documentation must have the ability to guide network engineers more intelligently as they solve service problems, which requires a clear understanding of all the device operating conditions (physical and virtual), the connection topology of devices, how traffic flows bi-directionally and the desired behaviors that results. And this all must be available at the touch of a button. Network automation is the perfect platform to enable this, since it can work in the background constantly maintaining this multi-facet model of any network in near real-time.

Task 2: Proactively looking for anomalous conditions such as outdated configurations or insecure passwords

Every network has a set of architectures that have been defined to support the business and its mission critical applications. By using no-code approaches to allow any engineer to translate the parameters of these architectures into validation logic, automation can be leveraged to execute verifications at scale.

By doing so, most network problems can be detected and corrected before they materially affect production services. These problem types range from available capacity and service delivery performance to security management and resilience. Device passwords must always be verified to be secure; failover links must be tested to assure they are available during times of stress; and device configurations must be tested to make sure required operating parameters are in effect. These and a hundred other scenarios can be crafted through automation to establish and maintain confidence in the operating baseline.

Task 3: The workflows associated with network troubleshooting

In every enterprise and MSP, there is a constant stream of operational service tasks, or tickets, that must be handled. The resolution of each of these tickets typically requires a set of repetitive steps that must be executed each time manually. And to make matters worse, the same service task being handled by different network engineers may be using completely different sets of steps based on their level of expertise and experience. The result is vastly inconsistent remedies.

Automation can capture the best practices for the majority of problem types and then make those available to engineers across the planet. And since those steps are repetitive, what may have taken hours to execute by hand may take minutes to execute by machine. Network engineers can leverage automation to run this golden set of diagnostics quickly, allowing them to focus on the harder networking issues which may be infrequent or deeply complex. This use of automation for troubleshooting results in lower MTTR, fewer tickets, faster MTTI, and improved resource management.

Task 4: Creating a more secure Change Management environment

Change is one of the most critical aspects of keeping every digital infrastructure up and running and in direct support of the business. And while there have been countless change management solutions over the years from more than a hundred vendors, they all lack the ability to understand the service delivery aspects of change, and they lack the ability to automatically verify that the change was not only completed successfully, but the results were as expected. Simply put, traditional change management solutions may successfully enable device changes to be made, but without an automated way to verify business service impacts, the business itself may suffer unforeseen dependencies.

A strong understanding of the network using a comprehensive digital twin coupled with an automation engine that can provide the means to verify the business services that traverse each and every device, both before and after change is made, is an entirely new way of thinking about change management- in the context of business service delivery, rather than device health.

Ensuring critical applications and IT services perform well is key to the operation and success of any business. No-code network automation enables fundamental change to long-established yet manual workflows, and in doing so, provides a level of consistency and operational performance never previously imagined. Network automation eliminates the tedium found in current processes and reduces the reliance on labor intensive tasks which are repetitive in nature. Network engineers can now rely on automation to handle the first two-thirds of the remedial work that they would otherwise manually do, allowing them to focus on more strategic and forward-looking work.

In broad strokes, automating NetOps enables outage prevention (which preserves the company's livelihood), troubleshooting scale (which saves time and money), application services to be delivered as needed (which increases revenue), network security to be continuously verified (which protects the business), and protected change (which eliminates the unintended consequences typically associated with change). Network automation can elevate network operations from tactical to strategic and bring simplicity and efficiency to NetOps teams.

Song Pang is CTO at NetBrain Technologies

Hot Topics

The Latest

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 ...

Seamless shopping is a basic demand of today's boundaryless consumer — one with little patience for friction, limited tolerance for disconnected experiences and minimal hesitation in switching brands. Customers expect intuitive, highly personalized experiences and the ability to move effortlessly across physical and digital channels within the same journey. Failure to deliver can cost dearly ...

If your best engineers spend their days sorting tickets and resetting access, you are wasting talent. New global data shows that employees in the IT sector rank among the least motivated across industries. They're under a lot of pressure from many angles. Pressure to upskill and uncertainty around what agentic AI means for job security is creating anxiety. Meanwhile, these roles often function like an on-call job and require many repetitive tasks ...