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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

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...