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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.

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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.

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Seeing is believing, or in this case, seeing is understanding, according to New Relic's 2025 Observability Forecast for Retail and eCommerce report. Retailers who want to provide exceptional customer experiences while improving IT operations efficiency are leaning on observability ... Here are five key takeaways from the report ...

Technology leaders across the federal landscape are facing, and will continue to face, an uphill battle when it comes to fortifying their digital environments against hostile and persistent threat actors. On one hand, they are being asked to push digital transformation ... On the other hand, they are facing the fiscal uncertainty of continuing resolutions (CR) and government shutdowns looming near and far. In the face of these challenges, CIOs, CTOs, and CISOs must figure out how to modernize legacy systems and infrastructure while doing more with less and still defending against external and internal threats ...

Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...

If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

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 ...