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Why UC Applications Still Cause Network Headaches (And How to Fix Them)

Chris Bloom

Unified Communications (UC) applications such as VoIP and Video streaming have been around in the enterprise setting now for almost two decades. It's rather remarkable, then, that for all of their business benefits and popularity, UC applications still post so many headaches for network engineers. With that in mind, are there steps that network engineers can and should be taking to make these applications more reliable, and deliver better quality of service to their users? I believe there are, so let's take a look at some tips.

Rather than being generated digitally, the origin of UC data is a fluid and continuous analog stream. For that reason, data from UC applications such as VoIP need to be managed in real time. Unfortunately, as digital files are transferred over any network, it's common for some of those packets to be dropped or to be delivered out of sync, resulting in poor sound quality, delays, static and sound gaps.

Email and document transfer applications generally cause far less obvious problems on the network thanks to TCP's built-in checks and acknowledgements, giving it the ability to resend and reorganize data into a perfect digital copy of the original. This isn't the case for UDP, which is a best-effort protocol often used by UC applications. Once a UDP packet has been sent, there is no mechanism to acknowledge or retransmit that packet if it gets delayed or corrupted due to latency, jitter or packet loss. VoIP technologies often employ tools such as DSP algorithms that compensate for up to 30 milliseconds of missing data, however anything above that threshold will be noticed by the listener.

This is where modern network analysis and diagnostic solutions come in. These tools give network engineers the ability to monitor and analyze all network traffic, including VoIP and other UC applications, for signs of network traffic issues. Armed with information about latency, throughput, and other network problems, IT teams have the power to resolve issues, maintain a QoS experience, mitigate poor performance caused by a competition for network bandwidth, and monitor compliance with established network policies and vendor SLAs.

It all starts with taking a proactive approach to UC application management. This involves being aware of the ways in which applications affect the network and other applications, but it also requires leveraging the full value of a network analysis solution to provide ongoing expert analysis of possible issues. Here are a few simple tips.

1. Understand your network's behavior

There are certain things an IT team needs to understand about the network's behavior, including its general health. The best way to assess this is to establish baselines of the existing infrastructure across the entire enterprise network. Knowing how the network behaves on a regular basis will prepare you to spot and deal with any issues that UC applications may have.

2. Beware of the three-headed beast: Jitter, Latency and Packet Loss

Jitter, latency, and packet loss are common, but they can cause havoc to UC applications on a converged network. This is where network visibility and analytics tools are invaluable as they alert the IT team to performance problems and enable proactive management of UC applications by adjusting configurations or adding extra capacity.

3. Monitor constantly

Monitoring UC applications includes a combination of metrics for general network performance and specific end-user quality of experience (QoE). Constant monitoring will validate QoS operations, reveal network traffic patterns that affect UC applications, and provide alerts whenever there's a drop in performance.

4. Zoom in on VoFi

VoFi is just another data type on your network, but using VoIP over wireless introduces the possibility of extra interference and other issues. Once the IT team has performed a scan of the 802.11 bands in use, 2.4GHz, 5GHz, etc., it's a good idea to isolate VoFi traffic for things like call quality, call volume (number of calls), and network utilization for VoFi versus all other data. If a more detailed analysis is needed, check the signaling for each call, including detail about any packet bounces.

You may also want to observe individual flows, since the packet paths between the caller and the callee can differ. Also check the quality of the voice transmission, including an analysis of latency, packet loss, jitter, and MOS and R-Factor voice quality metrics. If you're not sure how these metrics compare with “real world” quality, it helps to play back sections of a sample call to hear how it actually sounded.

5. Don't be afraid to tweak the network

Application traffic changes all the time. When you see issues crop up, don't be afraid to tweak the network to maintain levels of performance.

Although UC applications data is basically just another type of traffic on the network, ensuring that they work seamlessly can be a big challenge for IT teams. It's always best to start by testing the overall environment and the end user experience, and from there you can gradually drill down into specific problem areas to find a resolve the issues. Being proactive about network health will absolutely result in fewer problems down the line.

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Why UC Applications Still Cause Network Headaches (And How to Fix Them)

Chris Bloom

Unified Communications (UC) applications such as VoIP and Video streaming have been around in the enterprise setting now for almost two decades. It's rather remarkable, then, that for all of their business benefits and popularity, UC applications still post so many headaches for network engineers. With that in mind, are there steps that network engineers can and should be taking to make these applications more reliable, and deliver better quality of service to their users? I believe there are, so let's take a look at some tips.

Rather than being generated digitally, the origin of UC data is a fluid and continuous analog stream. For that reason, data from UC applications such as VoIP need to be managed in real time. Unfortunately, as digital files are transferred over any network, it's common for some of those packets to be dropped or to be delivered out of sync, resulting in poor sound quality, delays, static and sound gaps.

Email and document transfer applications generally cause far less obvious problems on the network thanks to TCP's built-in checks and acknowledgements, giving it the ability to resend and reorganize data into a perfect digital copy of the original. This isn't the case for UDP, which is a best-effort protocol often used by UC applications. Once a UDP packet has been sent, there is no mechanism to acknowledge or retransmit that packet if it gets delayed or corrupted due to latency, jitter or packet loss. VoIP technologies often employ tools such as DSP algorithms that compensate for up to 30 milliseconds of missing data, however anything above that threshold will be noticed by the listener.

This is where modern network analysis and diagnostic solutions come in. These tools give network engineers the ability to monitor and analyze all network traffic, including VoIP and other UC applications, for signs of network traffic issues. Armed with information about latency, throughput, and other network problems, IT teams have the power to resolve issues, maintain a QoS experience, mitigate poor performance caused by a competition for network bandwidth, and monitor compliance with established network policies and vendor SLAs.

It all starts with taking a proactive approach to UC application management. This involves being aware of the ways in which applications affect the network and other applications, but it also requires leveraging the full value of a network analysis solution to provide ongoing expert analysis of possible issues. Here are a few simple tips.

1. Understand your network's behavior

There are certain things an IT team needs to understand about the network's behavior, including its general health. The best way to assess this is to establish baselines of the existing infrastructure across the entire enterprise network. Knowing how the network behaves on a regular basis will prepare you to spot and deal with any issues that UC applications may have.

2. Beware of the three-headed beast: Jitter, Latency and Packet Loss

Jitter, latency, and packet loss are common, but they can cause havoc to UC applications on a converged network. This is where network visibility and analytics tools are invaluable as they alert the IT team to performance problems and enable proactive management of UC applications by adjusting configurations or adding extra capacity.

3. Monitor constantly

Monitoring UC applications includes a combination of metrics for general network performance and specific end-user quality of experience (QoE). Constant monitoring will validate QoS operations, reveal network traffic patterns that affect UC applications, and provide alerts whenever there's a drop in performance.

4. Zoom in on VoFi

VoFi is just another data type on your network, but using VoIP over wireless introduces the possibility of extra interference and other issues. Once the IT team has performed a scan of the 802.11 bands in use, 2.4GHz, 5GHz, etc., it's a good idea to isolate VoFi traffic for things like call quality, call volume (number of calls), and network utilization for VoFi versus all other data. If a more detailed analysis is needed, check the signaling for each call, including detail about any packet bounces.

You may also want to observe individual flows, since the packet paths between the caller and the callee can differ. Also check the quality of the voice transmission, including an analysis of latency, packet loss, jitter, and MOS and R-Factor voice quality metrics. If you're not sure how these metrics compare with “real world” quality, it helps to play back sections of a sample call to hear how it actually sounded.

5. Don't be afraid to tweak the network

Application traffic changes all the time. When you see issues crop up, don't be afraid to tweak the network to maintain levels of performance.

Although UC applications data is basically just another type of traffic on the network, ensuring that they work seamlessly can be a big challenge for IT teams. It's always best to start by testing the overall environment and the end user experience, and from there you can gradually drill down into specific problem areas to find a resolve the issues. Being proactive about network health will absolutely result in fewer problems down the line.

Hot Topics

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

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.