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

Nadeem Zahid
cPacket Networks

Network Performance Management and Diagnostics is an important aspect of Application Performance Management because application performance and experiences are intertwined with network performance. Networks connect end-users with applications; they also connect application components such as application servers and database servers, microservices, and IoT devices.

Experiences with enterprise and web-based (SaaS) applications by internal and external end-users directly impact an organization's success. These experiences may be formally specified with measurable metrics (for example, payment transaction response times) in a Service Level Experience (SLE). Externally, experiences impact customer satisfaction, retention and lifetime value. Within the organization, experiences affect employee satisfaction and productivity, including IT efficiency. Experiences also matter to automated processes, especially when specific timing tolerances are critical. Therefore, assuring exceptional experiences for all stakeholders and use cases is a critical success factor.


Frustration sets in for end-users who experience issues that are not proactively addressed. Customers may choose a competing service and internal customers will be less productive, resulting in a negative impact to the organization's top and bottom lines. IT personnel also get frustrated while troubleshooting and resolving issues under pressure. Proactively assuring performance using predictive and prescriptive analytics driven by data from monitoring is the ideal way to assure experiences because it averts poor experiences as well as time-consuming, costly and frustrating troubleshooting and problem solving.

Experiences with applications that are directly impacted by network performance can be grouped into the following three high-level categories:

Connectivity determines whether end-users and other processes including automation can access an application.

Responsiveness is either a quantitative or subjective measure of acceptability of the interactions with an application. For example, a target of receiving a response within one second is acceptable for many use cases.

Quality is another quantitative or subjective measure of acceptability. For example, a videoconference session that has delays, dropouts and other noticeable issues would be rated as poor quality.

Assuring Exceptional Experiences are Driving Performance Upgrades

High performance is often the way to assure responsiveness and quality. High performance often means increased processing speed that is reliant on data transmission speed, especially for processing intensive applications and streaming applications. Network throughput rates increase in steps. Currently the typical data rates are 10Gbps, 40Gbps, and 100Gbps. The need for performance and hence speed is driving upgrades of data center network data rates and corresponding monitoring to operate at 100Gbps.

High fidelity visibility and observability of the IT system's performance metrics are needed to manage and maximize user experiences. As data center networks continue migrating to 100Gbps data rates, monitoring resolution must keep pace.

Finding the Root Cause of Experience Issues

Customer support and IT help desks receive trouble tickets when performance issues occur. Tickets initiate an effort to resolve issues and start a timer that measures the mean time to resolution (MTTR) - a common metric used to gauge IT performance. Maintaining a low MTTR is a direct indicator of IT effectiveness and efficiency and an indirect indicator of customer satisfaction. The typical next steps include escalating the issue to specific roles and personnel within the IT team to isolate the root cause by first determining whether the problem is with the network or the application.

Investigating requires analyzing specific observable network and application behaviors and metrics. There are several entities and links between an end-user and an application that could cause connectivity issues if they malfunction. These include: the end-user's device, one or more networks (i.e., WAN, LAN, WLAN, DCN), the servers and other IT infrastructure hosting the application, and the application itself including underlying microservices and other software components.

Connectivity Issues

Let's look at a situation where network connectivity is inhibiting an employee's ability to access a custom application running within an organization's data center. The inability to access the application could be caused by a malfunction of the following connectivity stages:

■ Identity and Access Management

■ DHCP

■ DNS

■ Connectivity with the application server(s)

In such cases, investigator(s) should look at observable health and performance metrics in hopes of quickly isolating the problem. Using event logs, Ping, and Internet Control Message Protocol are quick ways to discover the root cause of connectivity issues. If no problems are found, the investigator(s) can dig deeper by analyzing network packet data to examine observed traffic and SYN/SYN ACK errors to determine if exchanges including TCP/IP handshakes at each of the connectivity stages listed above are working properly.

Go to: Assuring Exceptional Experiences with Applications Requires Assuring Network Performance - Part 2.

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 1

Nadeem Zahid
cPacket Networks

Network Performance Management and Diagnostics is an important aspect of Application Performance Management because application performance and experiences are intertwined with network performance. Networks connect end-users with applications; they also connect application components such as application servers and database servers, microservices, and IoT devices.

Experiences with enterprise and web-based (SaaS) applications by internal and external end-users directly impact an organization's success. These experiences may be formally specified with measurable metrics (for example, payment transaction response times) in a Service Level Experience (SLE). Externally, experiences impact customer satisfaction, retention and lifetime value. Within the organization, experiences affect employee satisfaction and productivity, including IT efficiency. Experiences also matter to automated processes, especially when specific timing tolerances are critical. Therefore, assuring exceptional experiences for all stakeholders and use cases is a critical success factor.


Frustration sets in for end-users who experience issues that are not proactively addressed. Customers may choose a competing service and internal customers will be less productive, resulting in a negative impact to the organization's top and bottom lines. IT personnel also get frustrated while troubleshooting and resolving issues under pressure. Proactively assuring performance using predictive and prescriptive analytics driven by data from monitoring is the ideal way to assure experiences because it averts poor experiences as well as time-consuming, costly and frustrating troubleshooting and problem solving.

Experiences with applications that are directly impacted by network performance can be grouped into the following three high-level categories:

Connectivity determines whether end-users and other processes including automation can access an application.

Responsiveness is either a quantitative or subjective measure of acceptability of the interactions with an application. For example, a target of receiving a response within one second is acceptable for many use cases.

Quality is another quantitative or subjective measure of acceptability. For example, a videoconference session that has delays, dropouts and other noticeable issues would be rated as poor quality.

Assuring Exceptional Experiences are Driving Performance Upgrades

High performance is often the way to assure responsiveness and quality. High performance often means increased processing speed that is reliant on data transmission speed, especially for processing intensive applications and streaming applications. Network throughput rates increase in steps. Currently the typical data rates are 10Gbps, 40Gbps, and 100Gbps. The need for performance and hence speed is driving upgrades of data center network data rates and corresponding monitoring to operate at 100Gbps.

High fidelity visibility and observability of the IT system's performance metrics are needed to manage and maximize user experiences. As data center networks continue migrating to 100Gbps data rates, monitoring resolution must keep pace.

Finding the Root Cause of Experience Issues

Customer support and IT help desks receive trouble tickets when performance issues occur. Tickets initiate an effort to resolve issues and start a timer that measures the mean time to resolution (MTTR) - a common metric used to gauge IT performance. Maintaining a low MTTR is a direct indicator of IT effectiveness and efficiency and an indirect indicator of customer satisfaction. The typical next steps include escalating the issue to specific roles and personnel within the IT team to isolate the root cause by first determining whether the problem is with the network or the application.

Investigating requires analyzing specific observable network and application behaviors and metrics. There are several entities and links between an end-user and an application that could cause connectivity issues if they malfunction. These include: the end-user's device, one or more networks (i.e., WAN, LAN, WLAN, DCN), the servers and other IT infrastructure hosting the application, and the application itself including underlying microservices and other software components.

Connectivity Issues

Let's look at a situation where network connectivity is inhibiting an employee's ability to access a custom application running within an organization's data center. The inability to access the application could be caused by a malfunction of the following connectivity stages:

■ Identity and Access Management

■ DHCP

■ DNS

■ Connectivity with the application server(s)

In such cases, investigator(s) should look at observable health and performance metrics in hopes of quickly isolating the problem. Using event logs, Ping, and Internet Control Message Protocol are quick ways to discover the root cause of connectivity issues. If no problems are found, the investigator(s) can dig deeper by analyzing network packet data to examine observed traffic and SYN/SYN ACK errors to determine if exchanges including TCP/IP handshakes at each of the connectivity stages listed above are working properly.

Go to: Assuring Exceptional Experiences with Applications Requires Assuring Network Performance - Part 2.

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 ...