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Metrics That Matter: 10 Key Insights Worth Monitoring for Remote Networks

Mandana Javaheri

The network is the unsung hero of any business; transporting information — actually, business value — to and from every resource, application, and employee, functioning quietly and invisibly in the background. Until there is a problem, that is. Then the resource everyone takes for granted is a major problem, a topic of great interest. Avoiding becoming the subject of that kind of discussion is one reason why IT professionals spend so much effort ensuring their network is stable, high performing, and secure.

The central network used to be the IT professional's primary concern. Now, remote and edge networks are a vital part of every organization. Savvy businesses monitor network performance and security all the way to the edge, giving them key insights on how to optimize business and improve operations. But, what type of analytics help drive this intelligence? Let's look at 10 key insights worth monitoring from remote networks.

Network Performance Metrics

The reliability of networks has increased over the last decade even as they have become more complex. Balanced against this increased reliability is the staggering expense of any network downtime or performance degradation. At the end of the day, an organization with fewer – but more costly – issues will find visibility into key network performance metrics is even more critical than it has ever been.

There are four metrics that determine acceptable performance of a distributed network and its activities:

1. Network Bandwidth: Approaching maximum network capacity is a vital indicator of an impending problem. Identifying which users, applications, or protocols are using the most bandwidth enables organizations to manage their network resources wisely and act on bandwidth issues quickly

2. Packet Loss: A well-performing network has little or no packet loss, so even if retransmits mean that no data is lost, substantial packet loss is a useful indicator of network congestion, link failure, or hardware/software issues on network devices. It isn't enough to know that packet loss occurred; seeing the issue as it happens and understanding the root cause means the right action can be taken quickly and effectively.

3. Latency: Latency issues impact productivity and decrease user dissatisfaction. The severity of the effect and user expectation vary from one use case to another. For example, sensitivity to latency for applications like financial trading is much higher than traditional web applications and VoIP. Once you know the accepted latency for your network and applications, then when it goes beyond the threshold you know to pay attention.

4. Errors Rate: Ideally, all packets would arrive to their destinations intact, but, a small fraction do not. The error rate is the percentage of bits or packets that are lost or damaged during delivery. Measure error rates when traffic levels are high in order to have a good understanding of error rate risks. The impact of even small error rates can be large since it can produce a major impact in throughput for applications.

Application Availability Metrics

Networks and applications are inseparable. Network congestion and application latency increase as the data has further to travel between locations. For distributed networks with remote locations, this distance can be a particularly challenging hurdle for application performance and availability. Bandwidth bottlenecks can cause critical applications like VoIP, WEB, ERP and CRM to slow down. Insight into applications at their operational location will speed up application incident analysis and resolution.

IT professionals require application awareness combined with overall network visibility; otherwise they risk being confronted with the signs and symptoms of an issue without the ability to identify and address the root cause.

For edge networks, the following application metrics are needed:

5. Application Performance: Poor application performance impacts user experience, productivity, business transactions, and most importantly, revenue. Real-time insight into application performance metrics such as throughput and response time allows organizations to know the status of each one of their applications wherever they are being used.

6. Application Responsiveness: Every application has an "accepted" response time. Significant deviations from this baseline directly reduce application usability. Measure response time per application to optimize quality of service, manage resources, and ensure application usability.

7. Application Distribution: How can you know if there is an application issue without first learning which applications are in your network? Are social media activities slowing down your entire network? Who is using which application on a daily basis? Visibility into application locations allows insightful business decisions and ensures compliance with policies and SLAs.

Security Metrics

Enterprises, under constant threat of attack, have implemented systems for prevention and detection of security threats. This isn't enough. Security incidents can and will occur, and when they do, the investigation into the breach must be timely and comprehensive in order to rapidly understand, contain, and eliminate the attack.

Network-level information critical for speedy breach forensics and productive investigations includes:

8. Network Packets: Investigations without access to the original network packets that carried the intrusion are invariably less effective. Logs and binaries on drives and memory can be altered or deleted, but packets contain critical information about the attacks, attackers, and information transmitted even before the attack initiates. It is a saying among security investigators: "packets don't lie."

9. Long-term Packet Availability: The challenge all enterprises face is that more often than not attacks remain undetected for weeks or even months. With this much time without discovery, attackers are able to inflict higher levels of damage and disguise themselves. Long-term packet-level information is required for effective security investigations of these most damaging breaches.

10. Decryption: For obvious reasons, today, most of the network traffic is encrypted and the percentage is increasing as security becomes a serious concern for most organizations. Without visibility into packets and their content, investigating a breach is not feasible. Having visibility into encrypted traffic eliminates blind spots and enables effective incident investigation.

The ability to actively monitor and act on performance, application and security data is critical for IT professionals today. For organizations with remote locations, the performance and security of their entire network is largely reliant on visibility into these ten metrics.

Mandana Javaheri is CTO of Savvius.

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Metrics That Matter: 10 Key Insights Worth Monitoring for Remote Networks

Mandana Javaheri

The network is the unsung hero of any business; transporting information — actually, business value — to and from every resource, application, and employee, functioning quietly and invisibly in the background. Until there is a problem, that is. Then the resource everyone takes for granted is a major problem, a topic of great interest. Avoiding becoming the subject of that kind of discussion is one reason why IT professionals spend so much effort ensuring their network is stable, high performing, and secure.

The central network used to be the IT professional's primary concern. Now, remote and edge networks are a vital part of every organization. Savvy businesses monitor network performance and security all the way to the edge, giving them key insights on how to optimize business and improve operations. But, what type of analytics help drive this intelligence? Let's look at 10 key insights worth monitoring from remote networks.

Network Performance Metrics

The reliability of networks has increased over the last decade even as they have become more complex. Balanced against this increased reliability is the staggering expense of any network downtime or performance degradation. At the end of the day, an organization with fewer – but more costly – issues will find visibility into key network performance metrics is even more critical than it has ever been.

There are four metrics that determine acceptable performance of a distributed network and its activities:

1. Network Bandwidth: Approaching maximum network capacity is a vital indicator of an impending problem. Identifying which users, applications, or protocols are using the most bandwidth enables organizations to manage their network resources wisely and act on bandwidth issues quickly

2. Packet Loss: A well-performing network has little or no packet loss, so even if retransmits mean that no data is lost, substantial packet loss is a useful indicator of network congestion, link failure, or hardware/software issues on network devices. It isn't enough to know that packet loss occurred; seeing the issue as it happens and understanding the root cause means the right action can be taken quickly and effectively.

3. Latency: Latency issues impact productivity and decrease user dissatisfaction. The severity of the effect and user expectation vary from one use case to another. For example, sensitivity to latency for applications like financial trading is much higher than traditional web applications and VoIP. Once you know the accepted latency for your network and applications, then when it goes beyond the threshold you know to pay attention.

4. Errors Rate: Ideally, all packets would arrive to their destinations intact, but, a small fraction do not. The error rate is the percentage of bits or packets that are lost or damaged during delivery. Measure error rates when traffic levels are high in order to have a good understanding of error rate risks. The impact of even small error rates can be large since it can produce a major impact in throughput for applications.

Application Availability Metrics

Networks and applications are inseparable. Network congestion and application latency increase as the data has further to travel between locations. For distributed networks with remote locations, this distance can be a particularly challenging hurdle for application performance and availability. Bandwidth bottlenecks can cause critical applications like VoIP, WEB, ERP and CRM to slow down. Insight into applications at their operational location will speed up application incident analysis and resolution.

IT professionals require application awareness combined with overall network visibility; otherwise they risk being confronted with the signs and symptoms of an issue without the ability to identify and address the root cause.

For edge networks, the following application metrics are needed:

5. Application Performance: Poor application performance impacts user experience, productivity, business transactions, and most importantly, revenue. Real-time insight into application performance metrics such as throughput and response time allows organizations to know the status of each one of their applications wherever they are being used.

6. Application Responsiveness: Every application has an "accepted" response time. Significant deviations from this baseline directly reduce application usability. Measure response time per application to optimize quality of service, manage resources, and ensure application usability.

7. Application Distribution: How can you know if there is an application issue without first learning which applications are in your network? Are social media activities slowing down your entire network? Who is using which application on a daily basis? Visibility into application locations allows insightful business decisions and ensures compliance with policies and SLAs.

Security Metrics

Enterprises, under constant threat of attack, have implemented systems for prevention and detection of security threats. This isn't enough. Security incidents can and will occur, and when they do, the investigation into the breach must be timely and comprehensive in order to rapidly understand, contain, and eliminate the attack.

Network-level information critical for speedy breach forensics and productive investigations includes:

8. Network Packets: Investigations without access to the original network packets that carried the intrusion are invariably less effective. Logs and binaries on drives and memory can be altered or deleted, but packets contain critical information about the attacks, attackers, and information transmitted even before the attack initiates. It is a saying among security investigators: "packets don't lie."

9. Long-term Packet Availability: The challenge all enterprises face is that more often than not attacks remain undetected for weeks or even months. With this much time without discovery, attackers are able to inflict higher levels of damage and disguise themselves. Long-term packet-level information is required for effective security investigations of these most damaging breaches.

10. Decryption: For obvious reasons, today, most of the network traffic is encrypted and the percentage is increasing as security becomes a serious concern for most organizations. Without visibility into packets and their content, investigating a breach is not feasible. Having visibility into encrypted traffic eliminates blind spots and enables effective incident investigation.

The ability to actively monitor and act on performance, application and security data is critical for IT professionals today. For organizations with remote locations, the performance and security of their entire network is largely reliant on visibility into these ten metrics.

Mandana Javaheri is CTO of Savvius.

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 ...