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Assuring Exceptional Experiences with Applications Requires Assuring Network Performance - Part 2

Nadeem Zahid
cPacket Networks

This is Part 2 of a blog series on how to find root cause of the most common application experience issues.

Start with: Assuring Exceptional Experiences with Applications Requires Assuring Network Performance - Part 1

Responsiveness Issues

This type of issue is often reported as "the application is too slow." A likely root cause of unacceptable responsiveness resulting from network issues is an overloaded network (e.g., the capacity of the network is insufficient to handle the current traffic). If a network is overloaded, it is possible that its DNS server is also overloaded and either responds very slowly or not at all. Observing traffic bursts, especially microbursts, with detailed metrics is another indicator of an overloaded network and a cause of irregular latencies. If any of these are the root cause, then traffic must be shaped accordingly and/or capacity must be added.

When resolving these issues, IT teams analyze network, application and protocol latency using observed metrics such as DNS and HTTP latency, one-way latency, round-trip time, and Zero-Window activity. Additional observed behaviors and metrics will reveal which specific problem is the culprit. These metrics include throughput measured as gigabits per second (Gbps), the number of connections per second, and the number of concurrent connections. Network packet and flow data provides the insights and context to identify the root cause. Packet data captured with high fidelity using high-performance monitoring will detect and characterize traffic bursts and the number of connections per second. Flow data reveals top talkers and the number of packets transmitted per second.

Streaming Issues

Communications and streaming applications that use Voice over IP (VoIP), videoconferencing, and other streaming services are increasingly in use for entertainment, education and collaboration, especially in the COVID-19 era. Experiences with these applications are directly impacted by network performance.

Choppy and freezing video, unsynchronized audio and video, audio dropout, and other noticeable types of distortion are the typical issues that result in unsatisfactory experiences. These annoying issues are the result of streaming errors and packet loss that are readily noticed, complained about, and reported to IT and customer support help desks.

To diagnose the root causes and assure exceptional streaming experiences, IT needs to monitor and observe jitter, sequence errors, retransmissions, and Maximum Transmission Unit (MTU) fragmentation. Excessive jitter and sequence errors result from various streaming errors, while retransmissions and fragmentation indicate the packet loss as the culprit. It is necessary to dig further to determine whether these problems are caused by routing problems or MTU fragmentation. High MTU values mean that larger packets are transmitted that take relatively longer to process and retransmit and hence inhibit a smooth flow of digitized voice and video streams.

Other Performance Issues

The applications that rely on streaming services such as high frequency trading and high-performance computing, are increasingly relying on higher throughput that is driving the use of 100Gbps connectivity. Timing tolerances, latencies and all other performance metrics become finer as data rates increase. This necessitates higher fidelity monitoring to provide the necessary visibility and observability to ensure the best possible SLEs and MTTR. As an example, detecting gaps in high frequency trading streams requires observing microbursts and latencies with sub-millisecond resolution. Therefore, it is essential to have a clearly defined SLE, especially for high-performance applications and underlying infrastructure, then match to it the metrics to observe and the tools and resolution needed to do so.

Experiences impact organizations in many ways, which is why delivering exceptional experiences is a critical success factor. Experiences with applications depend on network performance. As a result, effectively and efficiently assuring experiences requires visibility and observability into both network and application behaviors and metrics. Network Performance Management and Diagnostics driven by monitoring is therefore a necessary complement to Application Performance Management in all environments.

Nadeem Zahid is VP of Product Management & Marketing at cPacket Networks

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Assuring Exceptional Experiences with Applications Requires Assuring Network Performance - Part 2

Nadeem Zahid
cPacket Networks

This is Part 2 of a blog series on how to find root cause of the most common application experience issues.

Start with: Assuring Exceptional Experiences with Applications Requires Assuring Network Performance - Part 1

Responsiveness Issues

This type of issue is often reported as "the application is too slow." A likely root cause of unacceptable responsiveness resulting from network issues is an overloaded network (e.g., the capacity of the network is insufficient to handle the current traffic). If a network is overloaded, it is possible that its DNS server is also overloaded and either responds very slowly or not at all. Observing traffic bursts, especially microbursts, with detailed metrics is another indicator of an overloaded network and a cause of irregular latencies. If any of these are the root cause, then traffic must be shaped accordingly and/or capacity must be added.

When resolving these issues, IT teams analyze network, application and protocol latency using observed metrics such as DNS and HTTP latency, one-way latency, round-trip time, and Zero-Window activity. Additional observed behaviors and metrics will reveal which specific problem is the culprit. These metrics include throughput measured as gigabits per second (Gbps), the number of connections per second, and the number of concurrent connections. Network packet and flow data provides the insights and context to identify the root cause. Packet data captured with high fidelity using high-performance monitoring will detect and characterize traffic bursts and the number of connections per second. Flow data reveals top talkers and the number of packets transmitted per second.

Streaming Issues

Communications and streaming applications that use Voice over IP (VoIP), videoconferencing, and other streaming services are increasingly in use for entertainment, education and collaboration, especially in the COVID-19 era. Experiences with these applications are directly impacted by network performance.

Choppy and freezing video, unsynchronized audio and video, audio dropout, and other noticeable types of distortion are the typical issues that result in unsatisfactory experiences. These annoying issues are the result of streaming errors and packet loss that are readily noticed, complained about, and reported to IT and customer support help desks.

To diagnose the root causes and assure exceptional streaming experiences, IT needs to monitor and observe jitter, sequence errors, retransmissions, and Maximum Transmission Unit (MTU) fragmentation. Excessive jitter and sequence errors result from various streaming errors, while retransmissions and fragmentation indicate the packet loss as the culprit. It is necessary to dig further to determine whether these problems are caused by routing problems or MTU fragmentation. High MTU values mean that larger packets are transmitted that take relatively longer to process and retransmit and hence inhibit a smooth flow of digitized voice and video streams.

Other Performance Issues

The applications that rely on streaming services such as high frequency trading and high-performance computing, are increasingly relying on higher throughput that is driving the use of 100Gbps connectivity. Timing tolerances, latencies and all other performance metrics become finer as data rates increase. This necessitates higher fidelity monitoring to provide the necessary visibility and observability to ensure the best possible SLEs and MTTR. As an example, detecting gaps in high frequency trading streams requires observing microbursts and latencies with sub-millisecond resolution. Therefore, it is essential to have a clearly defined SLE, especially for high-performance applications and underlying infrastructure, then match to it the metrics to observe and the tools and resolution needed to do so.

Experiences impact organizations in many ways, which is why delivering exceptional experiences is a critical success factor. Experiences with applications depend on network performance. As a result, effectively and efficiently assuring experiences requires visibility and observability into both network and application behaviors and metrics. Network Performance Management and Diagnostics driven by monitoring is therefore a necessary complement to Application Performance Management in all environments.

Nadeem Zahid is VP of Product Management & Marketing at cPacket Networks

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 ...