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Troubleshooting's Secret Weapon: Greater Visibility

Jason Baudreau

Today's network engineers have their work cut out for them. Bigger, more complex networks have created an environment where network engineers are forced to adapt and develop more effective ways to manage and troubleshoot their networks. This begins with better visibility, which has presented an issue traditionally as engineers struggle to create an accurate picture due to challenges with static maps.

87 percent of survey respondents primarily rely on manual techniques to create and update their network diagrams

Network engineers typically spend hours or even days at a time manually mapping out network diagrams. In fact, NetBrain's State of the Network Engineer study found that 87 percent of survey respondents primarily rely on manual techniques to create and update their network diagrams. However, by the time these diagrams are complete, they are already out-of-date and therefore useless.

This is where automation comes in. By automating the documentation process, any part of the network can be visualized in seconds with infinite detail. In addition, these maps will update automatically each time there is a change to the network, so engineers can be sure they are always seeing a thorough and accurate picture.

Manual documentation is wrought with inefficiencies. When it comes to a network outage or breach, network engineers are working against the clock to get back online. Manual methods and static documents only add to the frustration and time to repair.

Currently, most network engineers rely on a combination of manual techniques for troubleshooting, including traceroute and the command-line interface (CLI) to gain visibility into a network. However, these are tedious and time-consuming methods that force engineers to work through one device at a time to identify and address an issue. In fact, 43 percent of survey respondents stated that troubleshooting takes too much time using CLI. This can result in an overreliance on tribal knowledge and a slew of other tools to access critical information such as configuration details and performance data. This will hinder a network teams' ability to troubleshoot issues quickly by having to cycle back and forth between applications.

So, what's the alternative to network engineers suffering though hours of manual documentation to find the route of an outage? A Dynamic Map.

Dynamic Maps integrate with network teams' existing ticketing systems, monitoring tools, security and event management systems to create an all-encompassing tool. When an issue arises, a Dynamic Map can be created instantly to target the problem by simply identifying the source and destination IP addresses. Through automation, it can then be used to diagnose the connectivity, performance and configuration of each interface. The ability to immediately identify the source of an issue significantly reduces a network team's mean time to repair (MTTR), which can positively impact a company's bottom line. The longer the network is down, the longer the organization loses out on revenue.

With the abundance of new trends like AI/machine learning, SD-WAN and DevOps, it's unclear what exactly the networking industry will look like in the future. One thing we do know for certain — networks will only become more complex and difficult to manage. Automation will become the secret ingredient to network management, arming engineers with much-needed visibility as day-to-day workflows become nearly impossible to complete manually. Enterprises not prepared for these changes and who are without an accurate picture of their network will ultimately suffer.

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Troubleshooting's Secret Weapon: Greater Visibility

Jason Baudreau

Today's network engineers have their work cut out for them. Bigger, more complex networks have created an environment where network engineers are forced to adapt and develop more effective ways to manage and troubleshoot their networks. This begins with better visibility, which has presented an issue traditionally as engineers struggle to create an accurate picture due to challenges with static maps.

87 percent of survey respondents primarily rely on manual techniques to create and update their network diagrams

Network engineers typically spend hours or even days at a time manually mapping out network diagrams. In fact, NetBrain's State of the Network Engineer study found that 87 percent of survey respondents primarily rely on manual techniques to create and update their network diagrams. However, by the time these diagrams are complete, they are already out-of-date and therefore useless.

This is where automation comes in. By automating the documentation process, any part of the network can be visualized in seconds with infinite detail. In addition, these maps will update automatically each time there is a change to the network, so engineers can be sure they are always seeing a thorough and accurate picture.

Manual documentation is wrought with inefficiencies. When it comes to a network outage or breach, network engineers are working against the clock to get back online. Manual methods and static documents only add to the frustration and time to repair.

Currently, most network engineers rely on a combination of manual techniques for troubleshooting, including traceroute and the command-line interface (CLI) to gain visibility into a network. However, these are tedious and time-consuming methods that force engineers to work through one device at a time to identify and address an issue. In fact, 43 percent of survey respondents stated that troubleshooting takes too much time using CLI. This can result in an overreliance on tribal knowledge and a slew of other tools to access critical information such as configuration details and performance data. This will hinder a network teams' ability to troubleshoot issues quickly by having to cycle back and forth between applications.

So, what's the alternative to network engineers suffering though hours of manual documentation to find the route of an outage? A Dynamic Map.

Dynamic Maps integrate with network teams' existing ticketing systems, monitoring tools, security and event management systems to create an all-encompassing tool. When an issue arises, a Dynamic Map can be created instantly to target the problem by simply identifying the source and destination IP addresses. Through automation, it can then be used to diagnose the connectivity, performance and configuration of each interface. The ability to immediately identify the source of an issue significantly reduces a network team's mean time to repair (MTTR), which can positively impact a company's bottom line. The longer the network is down, the longer the organization loses out on revenue.

With the abundance of new trends like AI/machine learning, SD-WAN and DevOps, it's unclear what exactly the networking industry will look like in the future. One thing we do know for certain — networks will only become more complex and difficult to manage. Automation will become the secret ingredient to network management, arming engineers with much-needed visibility as day-to-day workflows become nearly impossible to complete manually. Enterprises not prepared for these changes and who are without an accurate picture of their network will ultimately suffer.

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 ...