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End-User Monitoring is Displacing SNMP

Panos Vouzis

The cloud revolution has affected all facets of the IT realm, including network and application monitoring. SNMP monitoring gives us the status of our devices, but doesn’t capture the end-user experience. We need to know what users experience regardless of what device, network and ISP connects them to cloud applications.

On-premise hardware is being eliminated one router and one switch at a time. Since 2015, we have been seeing security-sensitive sectors migrating infrastructure from private to public cloud providers. The less hardware under management, the less important SNMP monitoring is.

In the not so distant future, the only hardware that will exist on-premise will be an edge device managed over the cloud. This will reduce the amount of hardware remaining under IT’s management. Overall complexity won’t go away, though, due to the number and gamut of devices connected to the network.

The IoT transformation within our connected world enables everything from personal devices to modern appliances to talk with us, and with each other refrigerators and door locks to talk to us and to each other. Each of these devices might also have its own Internet connection with a specific ISP, further increasing complexity and application dependency.

As applications are moving from private data centers to the cloud, the only sites that will remain under management with visibility and control will be office locations. Additionally, if an employee uses a third party application, the only visibility we have is from the employee's perspective because we don’t manage the cloud infrastructure that hosts the application. Ultimately, SNMP falls short monitoring the end-user experience; can the users use their applications and get their job done?

What are the options available to network administrators?

There are two ways to monitor the user experience: passive traffic capture and active monitoring.

Passive traffic capture

With passive capture we collect and analyze real user traffic. This remains useful if we want to know the in and out of a gateway for forensics and post mortem analysis. However, with hundreds or thousands of users, the amount of data can be overwhelming, requiring high storage capacity to save only a few days’ worth of data. Also, it captures network and application performance data only when there are active users on the network. A typical use case is to scan for top talkers and take measurements to mitigate excessive bandwidth utilization.

Active Monitoring

Active monitoring works by simulating a user on the network by emulating the user behavior. This is accomplished by agents installed exactly where the users are: on the wired or wireless network as clients. This gives the flexibility to test and monitor the network independent to the user behavior. Historical data can be stored for months or years. If a VPN split tunnel fails, you might not know of the incident until a user picks up the phone to open a ticket. With active monitoring you can be notified within seconds.

Real end-user monitoring and passive capture are taking the front seat and IT professionals have started complementing or replacing SNMP with a new generation of monitoring tools. This trend will continue and it will change the landscape of the application performance monitoring arena.

Panos Vouzis is Co-Founder and COO of NetBeez.

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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 ...

End-User Monitoring is Displacing SNMP

Panos Vouzis

The cloud revolution has affected all facets of the IT realm, including network and application monitoring. SNMP monitoring gives us the status of our devices, but doesn’t capture the end-user experience. We need to know what users experience regardless of what device, network and ISP connects them to cloud applications.

On-premise hardware is being eliminated one router and one switch at a time. Since 2015, we have been seeing security-sensitive sectors migrating infrastructure from private to public cloud providers. The less hardware under management, the less important SNMP monitoring is.

In the not so distant future, the only hardware that will exist on-premise will be an edge device managed over the cloud. This will reduce the amount of hardware remaining under IT’s management. Overall complexity won’t go away, though, due to the number and gamut of devices connected to the network.

The IoT transformation within our connected world enables everything from personal devices to modern appliances to talk with us, and with each other refrigerators and door locks to talk to us and to each other. Each of these devices might also have its own Internet connection with a specific ISP, further increasing complexity and application dependency.

As applications are moving from private data centers to the cloud, the only sites that will remain under management with visibility and control will be office locations. Additionally, if an employee uses a third party application, the only visibility we have is from the employee's perspective because we don’t manage the cloud infrastructure that hosts the application. Ultimately, SNMP falls short monitoring the end-user experience; can the users use their applications and get their job done?

What are the options available to network administrators?

There are two ways to monitor the user experience: passive traffic capture and active monitoring.

Passive traffic capture

With passive capture we collect and analyze real user traffic. This remains useful if we want to know the in and out of a gateway for forensics and post mortem analysis. However, with hundreds or thousands of users, the amount of data can be overwhelming, requiring high storage capacity to save only a few days’ worth of data. Also, it captures network and application performance data only when there are active users on the network. A typical use case is to scan for top talkers and take measurements to mitigate excessive bandwidth utilization.

Active Monitoring

Active monitoring works by simulating a user on the network by emulating the user behavior. This is accomplished by agents installed exactly where the users are: on the wired or wireless network as clients. This gives the flexibility to test and monitor the network independent to the user behavior. Historical data can be stored for months or years. If a VPN split tunnel fails, you might not know of the incident until a user picks up the phone to open a ticket. With active monitoring you can be notified within seconds.

Real end-user monitoring and passive capture are taking the front seat and IT professionals have started complementing or replacing SNMP with a new generation of monitoring tools. This trend will continue and it will change the landscape of the application performance monitoring arena.

Panos Vouzis is Co-Founder and COO of NetBeez.

Hot Topics

The Latest

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.

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 ...