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Monitoring Alert: Don't Get Lost in the Clouds

Mehdi Daoudi
Catchpoint

The cloud is the technological megatrend of the new millennium, creating ease-of-use, efficiency and velocity for small businesses to large enterprises. But it was never meant to be the only answer for every situation. In the world of digital experience monitoring (DEM) — where the end user experience is paramount — cloud-based nodes, along with a variety of other node types, are used to build a view of the end user's digital experience. But major companies are now depending solely on cloud nodes for DEM. Research from Catchpoint, in addition to real-world customer data, shows this is a mistake.

Bottom line: if you want an accurate view of the end user experience, you can't monitor only from the cloud. And if you're using the cloud to monitor something also based in the cloud (like many customer-facing apps), you're compounding the problem. You can't expect an accurate last mile performance view by measuring a digital service from the same infrastructure in which it's located.

This is akin to the mistake many made in the early days of monitoring: tracking site performance by measuring only from the data center where the site was hosted. That's far too limited a perspective, given the multitude of performance-impacting elements beyond the firewall. Let's take a look at cloud-only monitoring limitations and how to effectively navigate them.

How Cloud-Only Monitoring Can Create Blind Spots

For example, last year a company received alerts that its services were down. After a mad scramble to fix the problem, it discovered the services were fine, and the alerts were caused by an outage on their cloud-based monitoring nodes! The end user experience was untouched. Good news, but also proof of the noise and false positives that can occur when you monitor from only one place, and in particular, from a cloud-only view.

This led to further research. One example was a series of synthetic monitoring tests on a single request to a website hosted on AWS's Washington DC data center. The test was run from cloud-only nodes on AWS, with parallel tests on synthetic monitoring nodes running in traditional internet data center backbone locations. The test was ran starting August 1, 2018 from seven different nodes — the Washington DC AWS data center, three backbone nodes in Washington DC, and three backbone nodes in New York, NY. This consisted of over 1.7 million measurements. Here are the results.


As you can see, the performance (response times) of tests run only from the cloud are faster by a significant margin. The median response time from the AWS node (bottom line, in orange) was 31ms, while the median response time from Level3's Washington DC backbone node was 117ms; and from Verizon's New York backbone node, 167ms. The cloud node measurement alone does not provide a realistic view of how end users are experiencing this particular site, and would lull an operations team into a false sense of security — not the kind of performance gap a retail website wants, particularly while we are in the critical holiday shopping season.

Why is this so? Tests run from the cloud on a cloud-located site enjoy some form of dedicated network connection as well as preferential data routing. Think of it like a VIP's cleared traffic route through a crowded city. This streamlined data path is far afield from that of an average end user, who receives his/her content after a long, circuitous route through ISPs, CDNs, wireless networks and various other pathways.

Applications Not Suitable for Cloud-Only Monitoring

Another way of explaining this: cloud-only monitoring does not track performance along the entire application delivery chain, nor does it provide the diagnostics required to manage that chain. Any single point along that path — ISPs for example — can create problems impacting the end user experience.

Important tracking processes not suitable for cloud-only monitoring may also include:

■ SLA measurements for third-parties along the delivery chain

■ Provider performance testing for services like CDNs, DNS, ad servers

■ Benchmarking for competitors in your industry

■ Network or ISP connectivity issues

■ DNS availability or validation of service

Where Cloud-Only Monitoring Is Beneficial

Of course, it's not all bad news. Cloud monitoring can provide valuable insights for certain applications such as:

■ Determining availability and performance of an application or service from within the cloud infrastructure environment

■ Performing first mile testing without deploying agents in physical locations

■ Testing some of the basic functionality and content of an application

■ Evaluating the latency of cloud providers back to your infrastructure

Conclusion and Best Practices

The key to avoiding the cloud-only DEM trap is to understand that the accuracy of your monitoring strategy depends on how your measurements are taken and from which locations. Cloud-based vantage points can be a valuable piece of the monitoring puzzle, but should not be relied upon as your sole monitoring infrastructure, as they won't be able to track the many network layers comprising the internet.

The answer will most likely be adding a blend of backbone, broadband, ISP, last mile and wireless monitoring. Start where your customers are located and work your way back along the delivery chain. By canvassing all the elements that can impact their experience you'll have the most accurate view of that experience, as well as the best opportunity to preempt performance problems before end users are affected.

Mehdi Daoudi is CEO and Co-Founder of Catchpoint

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Monitoring Alert: Don't Get Lost in the Clouds

Mehdi Daoudi
Catchpoint

The cloud is the technological megatrend of the new millennium, creating ease-of-use, efficiency and velocity for small businesses to large enterprises. But it was never meant to be the only answer for every situation. In the world of digital experience monitoring (DEM) — where the end user experience is paramount — cloud-based nodes, along with a variety of other node types, are used to build a view of the end user's digital experience. But major companies are now depending solely on cloud nodes for DEM. Research from Catchpoint, in addition to real-world customer data, shows this is a mistake.

Bottom line: if you want an accurate view of the end user experience, you can't monitor only from the cloud. And if you're using the cloud to monitor something also based in the cloud (like many customer-facing apps), you're compounding the problem. You can't expect an accurate last mile performance view by measuring a digital service from the same infrastructure in which it's located.

This is akin to the mistake many made in the early days of monitoring: tracking site performance by measuring only from the data center where the site was hosted. That's far too limited a perspective, given the multitude of performance-impacting elements beyond the firewall. Let's take a look at cloud-only monitoring limitations and how to effectively navigate them.

How Cloud-Only Monitoring Can Create Blind Spots

For example, last year a company received alerts that its services were down. After a mad scramble to fix the problem, it discovered the services were fine, and the alerts were caused by an outage on their cloud-based monitoring nodes! The end user experience was untouched. Good news, but also proof of the noise and false positives that can occur when you monitor from only one place, and in particular, from a cloud-only view.

This led to further research. One example was a series of synthetic monitoring tests on a single request to a website hosted on AWS's Washington DC data center. The test was run from cloud-only nodes on AWS, with parallel tests on synthetic monitoring nodes running in traditional internet data center backbone locations. The test was ran starting August 1, 2018 from seven different nodes — the Washington DC AWS data center, three backbone nodes in Washington DC, and three backbone nodes in New York, NY. This consisted of over 1.7 million measurements. Here are the results.


As you can see, the performance (response times) of tests run only from the cloud are faster by a significant margin. The median response time from the AWS node (bottom line, in orange) was 31ms, while the median response time from Level3's Washington DC backbone node was 117ms; and from Verizon's New York backbone node, 167ms. The cloud node measurement alone does not provide a realistic view of how end users are experiencing this particular site, and would lull an operations team into a false sense of security — not the kind of performance gap a retail website wants, particularly while we are in the critical holiday shopping season.

Why is this so? Tests run from the cloud on a cloud-located site enjoy some form of dedicated network connection as well as preferential data routing. Think of it like a VIP's cleared traffic route through a crowded city. This streamlined data path is far afield from that of an average end user, who receives his/her content after a long, circuitous route through ISPs, CDNs, wireless networks and various other pathways.

Applications Not Suitable for Cloud-Only Monitoring

Another way of explaining this: cloud-only monitoring does not track performance along the entire application delivery chain, nor does it provide the diagnostics required to manage that chain. Any single point along that path — ISPs for example — can create problems impacting the end user experience.

Important tracking processes not suitable for cloud-only monitoring may also include:

■ SLA measurements for third-parties along the delivery chain

■ Provider performance testing for services like CDNs, DNS, ad servers

■ Benchmarking for competitors in your industry

■ Network or ISP connectivity issues

■ DNS availability or validation of service

Where Cloud-Only Monitoring Is Beneficial

Of course, it's not all bad news. Cloud monitoring can provide valuable insights for certain applications such as:

■ Determining availability and performance of an application or service from within the cloud infrastructure environment

■ Performing first mile testing without deploying agents in physical locations

■ Testing some of the basic functionality and content of an application

■ Evaluating the latency of cloud providers back to your infrastructure

Conclusion and Best Practices

The key to avoiding the cloud-only DEM trap is to understand that the accuracy of your monitoring strategy depends on how your measurements are taken and from which locations. Cloud-based vantage points can be a valuable piece of the monitoring puzzle, but should not be relied upon as your sole monitoring infrastructure, as they won't be able to track the many network layers comprising the internet.

The answer will most likely be adding a blend of backbone, broadband, ISP, last mile and wireless monitoring. Start where your customers are located and work your way back along the delivery chain. By canvassing all the elements that can impact their experience you'll have the most accurate view of that experience, as well as the best opportunity to preempt performance problems before end users are affected.

Mehdi Daoudi is CEO and Co-Founder of Catchpoint

Hot Topics

The Latest

Artificial intelligence (AI) has become the dominant force shaping enterprise data strategies. Boards expect progress. Executives expect returns. And data leaders are under pressure to prove that their organizations are "AI-ready" ...

Agentic AI is a major buzzword for 2026. Many tech companies are making bold promises about this technology, but many aren't grounded in reality, at least not yet. This coming year will likely be shaped by reality checks for IT teams, and progress will only come from a focus on strong foundations and disciplined execution ...

AI systems are still prone to hallucinations and misjudgments ... To build the trust needed for adoption, AI must be paired with human-in-the-loop (HITL) oversight, or checkpoints where humans verify, guide, and decide what actions are taken. The balance between autonomy and accountability is what will allow AI to deliver on its promise without sacrificing human trust ...

More data center leaders are reducing their reliance on utility grids by investing in onsite power for rapidly scaling data centers, according to the Data Center Power Report from Bloom Energy ...

In MEAN TIME TO INSIGHT Episode 21, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses AI-driven NetOps ... 

Enterprise IT has become increasingly complex and fragmented. Organizations are juggling dozens — sometimes hundreds — of different tools for endpoint management, security, app delivery, and employee experience. Each one needs its own license, its own maintenance, and its own integration. The result is a patchwork of overlapping tools, data stuck in silos, security vulnerabilities, and IT teams are spending more time managing software than actually getting work done ...

2025 was the year everybody finally saw the cracks in the foundation. If you were running production workloads, you probably lived through at least one outage you could not explain to your executives without pulling up a diagram and a whiteboard ...

Data has never been more central to a greater portion of enterprise operations than it is today. From software development to marketing strategy, data has become an essential component for success. But as data use cases multiply, so too does the diversity of the data itself. This shift is pushing organizations toward increasingly complex data infrastructure ...

Enterprises are not stalling because they doubt AI, but because they cannot yet govern, validate, or safely scale autonomous systems, according to The Pulse of Agentic AI 2026, a new report from Dynatrace ...

For most of the cloud era, site reliability engineers (SREs) were measured by their ability to protect availability, maintain performance, and reduce the operational risk of change. Cost management was someone else's responsibility, typically finance, procurement, or a dedicated FinOps team. That separation of duties made sense when infrastructure was relatively static and cloud bills grew in predictable ways. But modern cloud-native systems don't behave that way ...