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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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A new wave of tariffs, some exceeding 100%, is sending shockwaves across the technology industry. Enterprises are grappling with sudden, dramatic cost increases that threaten to disrupt carefully planned budgets, sourcing strategies, and deployment plans. For CIOs and CTOs, this isn't just an economic setback; it's a wake-up call. The era of predictable cloud pricing and stable global supply chains is over ...

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Artificial intelligence (AI) is core to observability practices, with some 41% of respondents reporting AI adoption as a core driver of observability, according to the State of Observability for Financial Services and Insurance report from New Relic ...

Application performance monitoring (APM) is a game of catching up — building dashboards, setting thresholds, tuning alerts, and manually correlating metrics to root causes. In the early days, this straightforward model worked as applications were simpler, stacks more predictable, and telemetry was manageable. Today, the landscape has shifted, and more assertive tools are needed ...

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Private clouds are no longer playing catch-up, and public clouds are no longer the default as organizations recalibrate their cloud strategies, according to the Private Cloud Outlook 2025 report from Broadcom. More than half (53%) of survey respondents say private cloud is their top priority for deploying new workloads over the next three years, while 69% are considering workload repatriation from public to private cloud, with one-third having already done so ...

As organizations chase productivity gains from generative AI, teams are overwhelmingly focused on improving delivery speed (45%) over enhancing software quality (13%), according to the Quality Transformation Report from Tricentis ...

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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

A new study by the IBM Institute for Business Value reveals that enterprises are expected to significantly scale AI-enabled workflows, many driven by agentic AI, relying on them for improved decision making and automation. The AI Projects to Profits study revealed that respondents expect AI-enabled workflows to grow from 3% today to 25% by the end of 2025. With 70% of surveyed executives indicating that agentic AI is important to their organization's future, the research suggests that many organizations are actively encouraging experimentation ...

Respondents predict that agentic AI will play an increasingly prominent role in their interactions with technology vendors over the coming years and are positive about the benefits it will bring, according to The Race to an Agentic Future: How Agentic AI Will Transform Customer Experience, a report from Cisco ...

A new wave of tariffs, some exceeding 100%, is sending shockwaves across the technology industry. Enterprises are grappling with sudden, dramatic cost increases that threaten to disrupt carefully planned budgets, sourcing strategies, and deployment plans. For CIOs and CTOs, this isn't just an economic setback; it's a wake-up call. The era of predictable cloud pricing and stable global supply chains is over ...

As artificial intelligence (AI) adoption gains momentum, network readiness is emerging as a critical success factor. AI workloads generate unpredictable bursts of traffic, demanding high-speed connectivity that is low latency and lossless. AI adoption will require upgrades and optimizations in data center networks and wide-area networks (WANs). This is prompting enterprise IT teams to rethink, re-architect, and upgrade their data center and WANs to support AI-driven operations ...

Artificial intelligence (AI) is core to observability practices, with some 41% of respondents reporting AI adoption as a core driver of observability, according to the State of Observability for Financial Services and Insurance report from New Relic ...

Application performance monitoring (APM) is a game of catching up — building dashboards, setting thresholds, tuning alerts, and manually correlating metrics to root causes. In the early days, this straightforward model worked as applications were simpler, stacks more predictable, and telemetry was manageable. Today, the landscape has shifted, and more assertive tools are needed ...

Cloud adoption has accelerated, but backup strategies haven't always kept pace. Many organizations continue to rely on backup strategies that were either lifted directly from on-prem environments or use cloud-native tools in limited, DR-focused ways ... Eon uncovered a handful of critical gaps regarding how organizations approach cloud backup. To capture these prevailing winds, we gathered insights from 150+ IT and cloud leaders at the recent Google Cloud Next conference, which we've compiled into the 2025 State of Cloud Data Backup ...

Private clouds are no longer playing catch-up, and public clouds are no longer the default as organizations recalibrate their cloud strategies, according to the Private Cloud Outlook 2025 report from Broadcom. More than half (53%) of survey respondents say private cloud is their top priority for deploying new workloads over the next three years, while 69% are considering workload repatriation from public to private cloud, with one-third having already done so ...

As organizations chase productivity gains from generative AI, teams are overwhelmingly focused on improving delivery speed (45%) over enhancing software quality (13%), according to the Quality Transformation Report from Tricentis ...

Back in March of this year ... MongoDB's stock price took a serious tumble ... In my opinion, it reflects a deeper structural issue in enterprise software economics altogether — vendor lock-in ...