Skip to main content

10 Questions to Ask When Evaluating Network Performance Management Solutions - Part 2

Jay Botelho

Successful insight into the performance of a company's networks starts with effective network performance management (NPM) tools. However, with the plethora of options it can be overwhelming for IT teams to choose the right one. This blog continues the 10 essential questions to ask before selecting an NPM tool.

Start with: 10 Questions to Ask When Evaluating Network Performance Management Solutions - Part 1

Question #6: Does the NPM solution support machine-learning, advanced anomaly detection and correlation?

Most solutions make broad claims in these areas, without much to show for it. Networks, and the demands on those networks, are highly unique between companies, so it's extremely difficult even with today's computing technologies to apply generalizations across network performance monitoring. But what is becoming more practical is the ability of NPM solutions to learn and apply knowledge based on machine learning of data trends over time, to create baselines and identify anomalous behavior without having to pre-configure limits or behavior characteristics.

Legacy systems require a great deal of a prior knowledge, and then significant configuration, for anomaly detection to work effectively. ML and AI are beginning to change that, but it's important to really validate the claims of any NPM solution.

Question #7: Is the solution utilizing advanced analytics and reporting?

To derive meaningful insights into complex issues, analytics platforms must provide reports and analyses on most, if not all, of a network's performance. This includes offering custom reporting for baselining and trend analysis and the ability to easily pivot reports to focus on key network performance intelligence.

Additionally, a modern NPM solution should correlate data across multiple network domains offering a cohesive, big-picture view of performance metrics and providing intelligent alerting, giving back valuable time to strapped IT teams.

Question #8: Does the solution assist with capacity planning?

Under-provisioning network resources can lead to congestion, bad user experience, and loss of productivity — overall, a negative business impact. Over-provisioning can lead to excess spending and a hit to the bottom line. Therefore, capacity planning is critical in helping to avoid performance problems and negative impacts.

When looking at an NPM solution, it is critical that it supports capacity planning through these features:

■ Service Level Agreement (SLA) management

■ Network and application analysis

■ Baselining and trending

■ Exception management

■ QoS management

Question #9: Does the solution facilitate root-cause analysis?

Most NPM solutions focus on visualization and reporting based on flow data (NetFlow, sFlow, IPFIX, etc.). These solutions, and the flow data that feed them, provide enough detail to troubleshoot many network and application issues. But at times flow data are simply not enough to get to the root cause of a problem. When more detailed data are needed, a recording of the network traffic itself, at the packet level, provides the detailed data needed for root-cause analysis. And when this packet data is analyzed with appropriate software, the software itself can identify many of these detailed network and application issues.

An NPM solution that can quickly pivot from flow data for visualization and reporting to packet data for analysis provides the most comprehensive solution and will significantly reduce the mean time to repair (MTTR).

Question #10: Can the solution provide scalable, enterprise support?

As the number of devices in many organizations continues to grow, it's important to implement tools that support this growth, particularly for large-scale organizations. A modern NPM platform must be able to analyze devices and environments at scale without latency and extend into additional environments such as multi-vendor WAN, public and private clouds and more. It also must support capacity planning and predict if a network can support an increase in business-critical traffic.

As organizations continue to grow and disperse, it is more evident than ever that ensuring optimal network performance is critical to business efficiency. When choosing a network performance monitoring solution, considering the questions above and implementing a unified platform will help organizations eliminate the cost and complexity of point solutions, reduce downtime, and successfully address the challenges of a modern network system.

Hot Topics

The Latest

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

10 Questions to Ask When Evaluating Network Performance Management Solutions - Part 2

Jay Botelho

Successful insight into the performance of a company's networks starts with effective network performance management (NPM) tools. However, with the plethora of options it can be overwhelming for IT teams to choose the right one. This blog continues the 10 essential questions to ask before selecting an NPM tool.

Start with: 10 Questions to Ask When Evaluating Network Performance Management Solutions - Part 1

Question #6: Does the NPM solution support machine-learning, advanced anomaly detection and correlation?

Most solutions make broad claims in these areas, without much to show for it. Networks, and the demands on those networks, are highly unique between companies, so it's extremely difficult even with today's computing technologies to apply generalizations across network performance monitoring. But what is becoming more practical is the ability of NPM solutions to learn and apply knowledge based on machine learning of data trends over time, to create baselines and identify anomalous behavior without having to pre-configure limits or behavior characteristics.

Legacy systems require a great deal of a prior knowledge, and then significant configuration, for anomaly detection to work effectively. ML and AI are beginning to change that, but it's important to really validate the claims of any NPM solution.

Question #7: Is the solution utilizing advanced analytics and reporting?

To derive meaningful insights into complex issues, analytics platforms must provide reports and analyses on most, if not all, of a network's performance. This includes offering custom reporting for baselining and trend analysis and the ability to easily pivot reports to focus on key network performance intelligence.

Additionally, a modern NPM solution should correlate data across multiple network domains offering a cohesive, big-picture view of performance metrics and providing intelligent alerting, giving back valuable time to strapped IT teams.

Question #8: Does the solution assist with capacity planning?

Under-provisioning network resources can lead to congestion, bad user experience, and loss of productivity — overall, a negative business impact. Over-provisioning can lead to excess spending and a hit to the bottom line. Therefore, capacity planning is critical in helping to avoid performance problems and negative impacts.

When looking at an NPM solution, it is critical that it supports capacity planning through these features:

■ Service Level Agreement (SLA) management

■ Network and application analysis

■ Baselining and trending

■ Exception management

■ QoS management

Question #9: Does the solution facilitate root-cause analysis?

Most NPM solutions focus on visualization and reporting based on flow data (NetFlow, sFlow, IPFIX, etc.). These solutions, and the flow data that feed them, provide enough detail to troubleshoot many network and application issues. But at times flow data are simply not enough to get to the root cause of a problem. When more detailed data are needed, a recording of the network traffic itself, at the packet level, provides the detailed data needed for root-cause analysis. And when this packet data is analyzed with appropriate software, the software itself can identify many of these detailed network and application issues.

An NPM solution that can quickly pivot from flow data for visualization and reporting to packet data for analysis provides the most comprehensive solution and will significantly reduce the mean time to repair (MTTR).

Question #10: Can the solution provide scalable, enterprise support?

As the number of devices in many organizations continues to grow, it's important to implement tools that support this growth, particularly for large-scale organizations. A modern NPM platform must be able to analyze devices and environments at scale without latency and extend into additional environments such as multi-vendor WAN, public and private clouds and more. It also must support capacity planning and predict if a network can support an increase in business-critical traffic.

As organizations continue to grow and disperse, it is more evident than ever that ensuring optimal network performance is critical to business efficiency. When choosing a network performance monitoring solution, considering the questions above and implementing a unified platform will help organizations eliminate the cost and complexity of point solutions, reduce downtime, and successfully address the challenges of a modern network system.

Hot Topics

The Latest

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...