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Do You Need Multi-CDN Monitoring? Here's What You Need to Consider - Part 1

Tony Falco
VP Marketing
Hydrolix

Imagine you're the CEO of a major retailer on Black Friday. How your e-commerce site performs on this one day could determine whether your entire year is a success or failure.

Or maybe you're the CTO of a broadcasting company with the contract to air the most-watched championship gridiron football game in history, or maybe the Olympics, with tens of millions of users streaming through a wide range of end devices, content delivery networks (CDNs) and internet service providers (ISPs). Now is not the time for a denial of service attack that prevents millions from watching the game.

Or perhaps you're co-founder of a gaming company that just launched its first multiplayer game, and it has gone viral, with online demand surpassing your wildest dreams. What will it do to your reputation and customer experience if you are unable to scale to meet the demand?

Whether these scenarios describe your reality, fantasies or nightmares, you undoubtedly appreciate the high stakes involved and how incredibly important it is for these companies to provide high-quality, low latency content delivery and to scale to an extreme degree to handle huge spikes in traffic.

There are two key ingredients to the secret sauce that helps enterprises accomplish such amazing feats: multi-CDN and multi-CDN monitoring. In this two part series, I'll provide a short primer on both of those topics.

What is Multi-CDN?

CDNs consist of geographically distributed data centers with servers that cache and serve content close to end users to reduce latency and improve load times. Each data center is strategically placed so that digital signals can rapidly travel from one "point of presence" (PoP) to the next, getting the digital signal to the viewer as fast as possible. Traditional CDNs typically use physical servers, but many CDNs are now using an entirely digital network architecture, commonly referred to as Edge Computing.

Multi-CDN refers to the strategy of utilizing multiple CDNs (e.g., Akamai, Cloudflare, CloudFront, Fastly and Gcore) to deliver digital content across the internet. Since no one CDN completely covers the world like a blanket, companies can leverage multiple CDNs to increase their PoPs and have more widespread coverage to their customers. The multi-CDN approach not only optimizes content delivery and delivers improved performance across different regions but also enables scalability during peak times and ensures redundancy in the event something goes wrong with a PoP or a single CDN's entire network.

CDNs are a critical infrastructure component, particularly for businesses that require fast and reliable content delivery, such as streaming services, e-commerce platforms, and global enterprises. Multi-CDN takes this a step further by combining the strengths of several CDN providers, offering benefits like enhanced availability, load balancing, and improved user experiences on a global scale.

Why Would a Company Take the Multi-CDN Approach?

A multi-CDN approach brings with it a host of technical and operational challenges. So why would an organization do it?

1. Redundancy and Reliability: Relying on a single CDN provider exposes application performance to the same risks that relying on a single cloud provider does. If your only CDN provider experiences an outage or performance degradation in a specific region, it likely will impact the user experience. A multi-CDN approach reduces this risk by providing multiple pathways for content delivery.

2. Performance Optimization: Different CDNs have different strengths in different regions. By leveraging multiple CDNs, companies can direct traffic to the CDN that performs best in a given geographic area at any given time.

3. Scalability: During peak traffic times — think major online sales events or live streaming of popular content — a single CDN might struggle under the load. Multi-CDN allows companies to distribute traffic, essentially load balancing the demand.

4. Cost Management: By using multiple CDNs, teams can optimize costs by routing traffic based on pricing models, bandwidth costs, and performance metrics, ensuring they get the best available value. Using multiple CDNs for cost management is a well documented trend (e.g., this article), with some leading CDNs citing the trend as a contributing factor for declining delivery revenues for the past three years.

Users of Multi-CDN

It's probably evident at this point that multi-CDN is particularly popular among large enterprises and organizations that require robust, reliable, and scalable content delivery solutions. The kinds of applications that fit this general description include:

Streaming Services: Companies like Netflix, Disney+, and Paramount use multi-CDN to deliver video content to millions of users worldwide. By employing multiple CDNs, they ensure that their content is always available and delivered with minimal buffering, even during peak viewing times.

Gaming: Leading gaming companies use multi-CDN to create real-time, instantly responsive experiences for more than 1 billion online gamers worldwide. In gaming, low latency (100 milliseconds or less) is one of the most important aspects of the user experience.

E-commerce Platforms: During high-traffic events like Black Friday, massive surges in traffic can compromise the user experience — a potentially catastrophic problem for online retailers. Just a delay of a few seconds can lead to customer dissatisfaction, lower conversion rates, and lost revenue. Multi-CDN helps distribute traffic, reducing server loads and keeping response times within the desired service level objectives.

Other Global Enterprises: Businesses operating on a global scale use multi-CDN to ensure consistent content delivery and user experience across different markets.

Challenges of Multi-CDN

Implementing and operating multi-CDN isn't trivial. First and foremost, managing multiple CDNs demands a sophisticated orchestration capability to ensure you can manage service requests and content delivery across different providers with different architectures, SLAs, APIs, etc. This involves complex routing logic, real-time traffic monitoring, and dynamic decision-making to autonomously switch among CDNs as needed.

This brings up what is probably the biggest single barrier: data standardization. Or, more accurately, the lack of data standardization. Each CDN likely will have different logging formats and naming conventions, making it challenging to aggregate and analyze data. Companies must standardize log data across CDNs to gain meaningful insights and monitor performance effectively. Organizations that run multi-CDN will tell you this can be a big lift.

Cost management is another challenge. While it's true that multi-CDN can reduce costs by placing loads on the CDNs that are most cost effective for a given set of conditions, it can also lead to higher expenses if the various contract commitments are not managed carefully. Multi-CDN can also indirectly increase costs by requiring more server-related resources, introducing software or hardware issues, and increasing the need for oversight in general.

And of course, with any architecture that spans multiple environments, security and all the compliance it demands has to be addressed. But that's a topic for its own article.

How Multi-CDN Monitoring Can Address These Challenges

In Part 1 of this series I've defined multi-CDN and explored the benefits and challenges it brings to organizations that rely on super-fast and reliable content delivery to their end users. In Part 2, we'll look at how monitoring can address the challenges of multi-CDN and help organizations capitalize on this valuable approach.

Read: <a href="https://www.apmdigest.com/do-you-need-multi-cdn-monitoring-heres-what-you-need-to-consider-part-2" target="_blank">Do You Need Multi-CDN Monitoring? Here's What You Need to Consider - Part 2</a>

Tony Falco is VP Marketing at Hydrolix

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 ...

Do You Need Multi-CDN Monitoring? Here's What You Need to Consider - Part 1

Tony Falco
VP Marketing
Hydrolix

Imagine you're the CEO of a major retailer on Black Friday. How your e-commerce site performs on this one day could determine whether your entire year is a success or failure.

Or maybe you're the CTO of a broadcasting company with the contract to air the most-watched championship gridiron football game in history, or maybe the Olympics, with tens of millions of users streaming through a wide range of end devices, content delivery networks (CDNs) and internet service providers (ISPs). Now is not the time for a denial of service attack that prevents millions from watching the game.

Or perhaps you're co-founder of a gaming company that just launched its first multiplayer game, and it has gone viral, with online demand surpassing your wildest dreams. What will it do to your reputation and customer experience if you are unable to scale to meet the demand?

Whether these scenarios describe your reality, fantasies or nightmares, you undoubtedly appreciate the high stakes involved and how incredibly important it is for these companies to provide high-quality, low latency content delivery and to scale to an extreme degree to handle huge spikes in traffic.

There are two key ingredients to the secret sauce that helps enterprises accomplish such amazing feats: multi-CDN and multi-CDN monitoring. In this two part series, I'll provide a short primer on both of those topics.

What is Multi-CDN?

CDNs consist of geographically distributed data centers with servers that cache and serve content close to end users to reduce latency and improve load times. Each data center is strategically placed so that digital signals can rapidly travel from one "point of presence" (PoP) to the next, getting the digital signal to the viewer as fast as possible. Traditional CDNs typically use physical servers, but many CDNs are now using an entirely digital network architecture, commonly referred to as Edge Computing.

Multi-CDN refers to the strategy of utilizing multiple CDNs (e.g., Akamai, Cloudflare, CloudFront, Fastly and Gcore) to deliver digital content across the internet. Since no one CDN completely covers the world like a blanket, companies can leverage multiple CDNs to increase their PoPs and have more widespread coverage to their customers. The multi-CDN approach not only optimizes content delivery and delivers improved performance across different regions but also enables scalability during peak times and ensures redundancy in the event something goes wrong with a PoP or a single CDN's entire network.

CDNs are a critical infrastructure component, particularly for businesses that require fast and reliable content delivery, such as streaming services, e-commerce platforms, and global enterprises. Multi-CDN takes this a step further by combining the strengths of several CDN providers, offering benefits like enhanced availability, load balancing, and improved user experiences on a global scale.

Why Would a Company Take the Multi-CDN Approach?

A multi-CDN approach brings with it a host of technical and operational challenges. So why would an organization do it?

1. Redundancy and Reliability: Relying on a single CDN provider exposes application performance to the same risks that relying on a single cloud provider does. If your only CDN provider experiences an outage or performance degradation in a specific region, it likely will impact the user experience. A multi-CDN approach reduces this risk by providing multiple pathways for content delivery.

2. Performance Optimization: Different CDNs have different strengths in different regions. By leveraging multiple CDNs, companies can direct traffic to the CDN that performs best in a given geographic area at any given time.

3. Scalability: During peak traffic times — think major online sales events or live streaming of popular content — a single CDN might struggle under the load. Multi-CDN allows companies to distribute traffic, essentially load balancing the demand.

4. Cost Management: By using multiple CDNs, teams can optimize costs by routing traffic based on pricing models, bandwidth costs, and performance metrics, ensuring they get the best available value. Using multiple CDNs for cost management is a well documented trend (e.g., this article), with some leading CDNs citing the trend as a contributing factor for declining delivery revenues for the past three years.

Users of Multi-CDN

It's probably evident at this point that multi-CDN is particularly popular among large enterprises and organizations that require robust, reliable, and scalable content delivery solutions. The kinds of applications that fit this general description include:

Streaming Services: Companies like Netflix, Disney+, and Paramount use multi-CDN to deliver video content to millions of users worldwide. By employing multiple CDNs, they ensure that their content is always available and delivered with minimal buffering, even during peak viewing times.

Gaming: Leading gaming companies use multi-CDN to create real-time, instantly responsive experiences for more than 1 billion online gamers worldwide. In gaming, low latency (100 milliseconds or less) is one of the most important aspects of the user experience.

E-commerce Platforms: During high-traffic events like Black Friday, massive surges in traffic can compromise the user experience — a potentially catastrophic problem for online retailers. Just a delay of a few seconds can lead to customer dissatisfaction, lower conversion rates, and lost revenue. Multi-CDN helps distribute traffic, reducing server loads and keeping response times within the desired service level objectives.

Other Global Enterprises: Businesses operating on a global scale use multi-CDN to ensure consistent content delivery and user experience across different markets.

Challenges of Multi-CDN

Implementing and operating multi-CDN isn't trivial. First and foremost, managing multiple CDNs demands a sophisticated orchestration capability to ensure you can manage service requests and content delivery across different providers with different architectures, SLAs, APIs, etc. This involves complex routing logic, real-time traffic monitoring, and dynamic decision-making to autonomously switch among CDNs as needed.

This brings up what is probably the biggest single barrier: data standardization. Or, more accurately, the lack of data standardization. Each CDN likely will have different logging formats and naming conventions, making it challenging to aggregate and analyze data. Companies must standardize log data across CDNs to gain meaningful insights and monitor performance effectively. Organizations that run multi-CDN will tell you this can be a big lift.

Cost management is another challenge. While it's true that multi-CDN can reduce costs by placing loads on the CDNs that are most cost effective for a given set of conditions, it can also lead to higher expenses if the various contract commitments are not managed carefully. Multi-CDN can also indirectly increase costs by requiring more server-related resources, introducing software or hardware issues, and increasing the need for oversight in general.

And of course, with any architecture that spans multiple environments, security and all the compliance it demands has to be addressed. But that's a topic for its own article.

How Multi-CDN Monitoring Can Address These Challenges

In Part 1 of this series I've defined multi-CDN and explored the benefits and challenges it brings to organizations that rely on super-fast and reliable content delivery to their end users. In Part 2, we'll look at how monitoring can address the challenges of multi-CDN and help organizations capitalize on this valuable approach.

Read: <a href="https://www.apmdigest.com/do-you-need-multi-cdn-monitoring-heres-what-you-need-to-consider-part-2" target="_blank">Do You Need Multi-CDN Monitoring? Here's What You Need to Consider - Part 2</a>

Tony Falco is VP Marketing at Hydrolix

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 ...