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Seven Tips for Optimizing Network Performance - Part 2

Jay Botelho

Despite careful planning and monitoring, users still experience stuttering video calls, slow downloads, and dropped calls — all symptoms of common network problems. That's why proactive monitoring and optimization of the network is critical to keeping business operations running optimally. To help, let's look at some more network performance management tips that can keep your team ahead of the curve.

Start with Seven Tips for Optimizing Network Performance - Part 1

4. Update Software and Firmware

This is obviously critical for security, but when it comes to network performance, older software and firmware can also be a big problem. No one knows better than the manufacturer about the strengths, and weaknesses, of their products. Most products today, whether hardware or software, are essentially driven by the software and firmware that they run. Even though it may seem like the product you're using is stable, the "if it's not broken don't fix it" rule is not the optimal choice. Manufacturers know when there are underlying problems in their products that you may not see or may not be experiencing right now.

5. Establish a View of Network Topology

It's every network engineer's dream: a clear and concise dashboard that depicts the network topology from end to end. It sounds simple, but of course it's not. Network topologies take different forms, depending on the perspective of the user. But many agree that at least one depiction (that of each flow traversing the network, from client to server and back) is extremely useful for visualizing and troubleshooting network performance issues. The ability of solutions to provide this visualization is being taxed by many new technologies, including SD-WAN and cloud.

Make sure the network monitoring and visualization solution you choose can trace flows across and within all these different technologies. This is especially true for cloud since so much processing has already been pushed to the cloud, and the cloud infrastructure is very dynamic. It's imperative to track your network traffic not only to your cloud providers, but inside the cloud infrastructure whenever possible to retain the same level of troubleshooting you had when you hosted your applications in your own data center.

6. Implement Bandwidth-Friendly Policies

From the network engineering perspective these policies are bandwidth-friendly, but users may not see it the same way. Bandwidth is a commodity, and with most commodities users will use as much as they can if they see the commodity as free. And your corporate infrastructure users see bandwidth as being free and unlimited, even though we know that is far from the case. From a corporate perspective, bandwidth-friendly policies are those that allow business traffic to flow unimpeded on your network, but limit or perhaps even block traffic that is not essential.

Fortunately, there are ways to limit non-essential business traffic without blocking it entirely, keeping the user revolt at bay. This can be done through QoS settings, using traffic-shaping technologies, or taking advantage of SD-WAN features, assuming SD-WAN is already in use. The choice depends on the degree of control needed.

7. Use Automation When Possible

Automation is the holy grail in network performance management and includes finding a solution that monitors your network 24x7, detecting every problem before it happens, and adjusting the network to prevent the problem. But every network is different, and every situation is different, making true automation one of the most difficult areas to address in network management, never mind the blind trust required. But with the strides made in end-to-end network monitoring, along with the predictive capabilities of AI/ML solutions for detecting problems, the industry is moving forward. We can't expect automation in every area, and probably wouldn't trust automation in every area, so the best approach is to start small with technologies you can trust.

For example, relying on built-in automation between various solutions used in your network monitoring and management process. More specifically, integrating your network monitoring and trouble ticket systems such that critical alerts from network monitoring opens trouble tickets and begins feeding the system with key data so that network engineers can hit the ground running when they begin working on the issue.

Optimizing the network to ensure it meets the needs of users is becoming more and more complex. But the good news is that new tools and technologies are making it easier than ever to automate functionality, visualize performance and isolate problems before they become major issues for the business (not to mention providing tools for planning). Consider these tips when strategizing about your network monitoring and management to stay one step ahead of network problems.

The Latest

Rapid AI adoption and the unique ways AI workloads operate is redefining the scope and structure of what these teams must deliver. This shift is forcing organizations to rethink how they manage scale, automation, and control, according to The State of SRE and Platform Engineering 2026, a new report from Dynatrace ...

AI is usually talked about as a software tool, but it also depends heavily on the network behind it. Whether a company is using AI for chatbots, automation, monitoring, analytics, or employee support, all of that information has to move across the network in a reliable and secure way. That means AI is not just an application decision. It is also an infrastructure decision. Before organizations rush into AI, they should ask a simple question: Is our network ready to support it? ...

Enterprise AI often lacks governed access to where business processes actually execute. Without that access, AI agents may be able to reason, but they cannot operate reliably across enterprise workflows. For AI agents to effectively carry out workflows, they will require integration-layer context and controls. Organizations can implement these prerequisites by providing AI with managed access to the middleware layer ...

Enterprise networks rarely behave the same way for very long. A routing adjustment in one region may unexpectedly alter application performance in another. A cloud migration may introduce hidden dependencies that go unnoticed until an outage occurs. All the while, the network is managed by several different teams, each of whom use different tool sets — and as a result, have different views of the network ... There’s usually an engineer who remembers why traffic fails over a certain way between sites, or which transparent firewall was added where. The problem is that human memory cannot scale alongside enterprise-scale networks ...

Ask an infrastructure team how confident they are in their ability to govern AI, and most will tell you they've got it handled. A recent survey of 406 IT decision-makers and platform engineering leaders found 86% expressing exactly that confidence. Ask the same group whether they have a formal written AI governance policy, and the number drops to 30%, according to Spacelift's Infrastructure Automation Report ...

In MEAN TIME TO INSIGHT Episode 27, Shamus McGillicuddy, EMA VP of Research, Network Infrastructure and Operations, and Parker Hathcock, EMA Research Director covering IT Service/Operations (ServiceOps), discuss observability unification in modern IT operations ... 

Virtual Private Networks became a cornerstone of enterprise security at a time when corporate infrastructure looked very different from today ... For years, this model worked well. But the architecture behind VPNs assumed a centralized corporate environment—one where the network itself was the hub of activity. In a cloud — first world, that assumption no longer holds ...

Website outages get resolved just as fast in August as they do in November. I went looking for the opposite: the summer slowdown everyone assumes is there once the people who fix things are away. It isn't in the data we collected, covering 1.8 million confirmed outages across tens of thousands of websites ...

This year, many of the cloud infrastructure contracts signed in the early days of the AI boom will come up for renewal. As the year goes on, I anticipate we'll see a significant amount of cloud vendor swapouts and multi-cloud adoption, and the reason isn't just GPU depreciation. It's because they're tired of their current cloud providers ...

There's a moment the many observability teams have experienced days into bringing a new service into production: you realize that the vendor's claims of "intelligent" behavior included a large serving of hype. Their dashboards look nice until they don't, the failure modes are a black box, and no one on the team can confidently explain why the system did what it did at 2 am. Agentic AI is about to force every Ops team to relive that moment at web-scale until they start treating these systems as the dependencies they actually are ...

Seven Tips for Optimizing Network Performance - Part 2

Jay Botelho

Despite careful planning and monitoring, users still experience stuttering video calls, slow downloads, and dropped calls — all symptoms of common network problems. That's why proactive monitoring and optimization of the network is critical to keeping business operations running optimally. To help, let's look at some more network performance management tips that can keep your team ahead of the curve.

Start with Seven Tips for Optimizing Network Performance - Part 1

4. Update Software and Firmware

This is obviously critical for security, but when it comes to network performance, older software and firmware can also be a big problem. No one knows better than the manufacturer about the strengths, and weaknesses, of their products. Most products today, whether hardware or software, are essentially driven by the software and firmware that they run. Even though it may seem like the product you're using is stable, the "if it's not broken don't fix it" rule is not the optimal choice. Manufacturers know when there are underlying problems in their products that you may not see or may not be experiencing right now.

5. Establish a View of Network Topology

It's every network engineer's dream: a clear and concise dashboard that depicts the network topology from end to end. It sounds simple, but of course it's not. Network topologies take different forms, depending on the perspective of the user. But many agree that at least one depiction (that of each flow traversing the network, from client to server and back) is extremely useful for visualizing and troubleshooting network performance issues. The ability of solutions to provide this visualization is being taxed by many new technologies, including SD-WAN and cloud.

Make sure the network monitoring and visualization solution you choose can trace flows across and within all these different technologies. This is especially true for cloud since so much processing has already been pushed to the cloud, and the cloud infrastructure is very dynamic. It's imperative to track your network traffic not only to your cloud providers, but inside the cloud infrastructure whenever possible to retain the same level of troubleshooting you had when you hosted your applications in your own data center.

6. Implement Bandwidth-Friendly Policies

From the network engineering perspective these policies are bandwidth-friendly, but users may not see it the same way. Bandwidth is a commodity, and with most commodities users will use as much as they can if they see the commodity as free. And your corporate infrastructure users see bandwidth as being free and unlimited, even though we know that is far from the case. From a corporate perspective, bandwidth-friendly policies are those that allow business traffic to flow unimpeded on your network, but limit or perhaps even block traffic that is not essential.

Fortunately, there are ways to limit non-essential business traffic without blocking it entirely, keeping the user revolt at bay. This can be done through QoS settings, using traffic-shaping technologies, or taking advantage of SD-WAN features, assuming SD-WAN is already in use. The choice depends on the degree of control needed.

7. Use Automation When Possible

Automation is the holy grail in network performance management and includes finding a solution that monitors your network 24x7, detecting every problem before it happens, and adjusting the network to prevent the problem. But every network is different, and every situation is different, making true automation one of the most difficult areas to address in network management, never mind the blind trust required. But with the strides made in end-to-end network monitoring, along with the predictive capabilities of AI/ML solutions for detecting problems, the industry is moving forward. We can't expect automation in every area, and probably wouldn't trust automation in every area, so the best approach is to start small with technologies you can trust.

For example, relying on built-in automation between various solutions used in your network monitoring and management process. More specifically, integrating your network monitoring and trouble ticket systems such that critical alerts from network monitoring opens trouble tickets and begins feeding the system with key data so that network engineers can hit the ground running when they begin working on the issue.

Optimizing the network to ensure it meets the needs of users is becoming more and more complex. But the good news is that new tools and technologies are making it easier than ever to automate functionality, visualize performance and isolate problems before they become major issues for the business (not to mention providing tools for planning). Consider these tips when strategizing about your network monitoring and management to stay one step ahead of network problems.

The Latest

Rapid AI adoption and the unique ways AI workloads operate is redefining the scope and structure of what these teams must deliver. This shift is forcing organizations to rethink how they manage scale, automation, and control, according to The State of SRE and Platform Engineering 2026, a new report from Dynatrace ...

AI is usually talked about as a software tool, but it also depends heavily on the network behind it. Whether a company is using AI for chatbots, automation, monitoring, analytics, or employee support, all of that information has to move across the network in a reliable and secure way. That means AI is not just an application decision. It is also an infrastructure decision. Before organizations rush into AI, they should ask a simple question: Is our network ready to support it? ...

Enterprise AI often lacks governed access to where business processes actually execute. Without that access, AI agents may be able to reason, but they cannot operate reliably across enterprise workflows. For AI agents to effectively carry out workflows, they will require integration-layer context and controls. Organizations can implement these prerequisites by providing AI with managed access to the middleware layer ...

Enterprise networks rarely behave the same way for very long. A routing adjustment in one region may unexpectedly alter application performance in another. A cloud migration may introduce hidden dependencies that go unnoticed until an outage occurs. All the while, the network is managed by several different teams, each of whom use different tool sets — and as a result, have different views of the network ... There’s usually an engineer who remembers why traffic fails over a certain way between sites, or which transparent firewall was added where. The problem is that human memory cannot scale alongside enterprise-scale networks ...

Ask an infrastructure team how confident they are in their ability to govern AI, and most will tell you they've got it handled. A recent survey of 406 IT decision-makers and platform engineering leaders found 86% expressing exactly that confidence. Ask the same group whether they have a formal written AI governance policy, and the number drops to 30%, according to Spacelift's Infrastructure Automation Report ...

In MEAN TIME TO INSIGHT Episode 27, Shamus McGillicuddy, EMA VP of Research, Network Infrastructure and Operations, and Parker Hathcock, EMA Research Director covering IT Service/Operations (ServiceOps), discuss observability unification in modern IT operations ... 

Virtual Private Networks became a cornerstone of enterprise security at a time when corporate infrastructure looked very different from today ... For years, this model worked well. But the architecture behind VPNs assumed a centralized corporate environment—one where the network itself was the hub of activity. In a cloud — first world, that assumption no longer holds ...

Website outages get resolved just as fast in August as they do in November. I went looking for the opposite: the summer slowdown everyone assumes is there once the people who fix things are away. It isn't in the data we collected, covering 1.8 million confirmed outages across tens of thousands of websites ...

This year, many of the cloud infrastructure contracts signed in the early days of the AI boom will come up for renewal. As the year goes on, I anticipate we'll see a significant amount of cloud vendor swapouts and multi-cloud adoption, and the reason isn't just GPU depreciation. It's because they're tired of their current cloud providers ...

There's a moment the many observability teams have experienced days into bringing a new service into production: you realize that the vendor's claims of "intelligent" behavior included a large serving of hype. Their dashboards look nice until they don't, the failure modes are a black box, and no one on the team can confidently explain why the system did what it did at 2 am. Agentic AI is about to force every Ops team to relive that moment at web-scale until they start treating these systems as the dependencies they actually are ...