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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.

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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

AI observability serves several roles across an organization. AI engineers use it to build, evaluate, and improve AI systems. SREs use it to operate those systems reliably and efficiently in production, including managing their cost. Leaders need it to connect AI behavior and operational performance to business outcomes. The common need is a clear understanding of whether AI systems are delivering the intended result ...

Part 4 outlines the challenges enterprise face when adopting AI observability. The main challenge is that AI complexity compounds at every stage of maturity. LLM-based applications introduce new behavior, dependencies, and quality considerations, while Agentic AI adds further failure modes as systems make decisions and take actions ...

Part 3 reports on the current state of AI observability. Most experts agree: enterprises are moving faster with AI than they are with the operational discipline needed to run it safely ...

When discussing AI Observability, one of the first questions that arises: Is this just an extension of traditional observability or is this a whole new type of tool? Part 2 compares traditional observability with AI observability ...

In this extensive 14-part series that will post over the next three weeks, experts across observability and AI will provide insight and opinions on the need for AI Observability, the challenges, the benefits, the current state, and predictions for the future ...

Amid rising complexity, organizations are moving quickly toward agent-driven operations: AgenticOps, according to The Impact of Agentic AI on Network Operations, a new report from Cisco ...

AI, automation, and enterprise software give organizations an extraordinary amount of leverage. Work that once required hours can happen in minutes. Information buried across systems can be analyzed almost instantly. Complex workflows can be coordinated across teams with far less manual intervention. That leverage creates a temptation to start with the technology ...

Everyone wants to talk about models. Compute clusters. Benchmark scores that climb a fraction of a point and make headlines anyway. It's an easy conversation to have because it's measurable. But it's also increasingly beside the point ...

For more than a decade, the default infrastructure play has been simple. Move more workloads to the cloud, retire on-premises gear and treat the data center as a cost to shrink. That logic held while public cloud offered near-limitless capacity at predictable prices, and AI demand is now testing both halves of that assumption ...

Most enterprise IT leaders can tell you exactly how many applications are running across their organization. They can surface a dashboard showing telecom spend by region, pull a report on SaaS license utilization, or call up a real-time view of mobile device inventory. The data is there, and IT leaders have largely delivered on the promise of visibility. Yet, in most organizations, that visibility has not translated into business value ...