Skip to main content

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

While 87% of manufacturing leaders and technical specialists report that ROI from their AIOps initiatives has met or exceeded expectations, only 37% say they are fully prepared to operationalize AI at scale, according to The Future of IT Operations in the AI Era, a report from Riverbed ...

Many organizations rely on cloud-first architectures to aggregate, analyze, and act on their operational data ... However, not all environments are conducive to cloud-first architectures ... There are limitations to cloud-first architectures that render them ineffective in mission-critical situations where responsiveness, cost control, and data sovereignty are non-negotiable; these limitations include ...

For years, cybersecurity was built around a simple assumption: protect the physical network and trust everything inside it. That model made sense when employees worked in offices, applications lived in data centers, and devices rarely left the building. Today's reality is fluid: people work from everywhere, applications run across multiple clouds, and AI-driven agents are beginning to act on behalf of users. But while the old perimeter dissolved, a new one quietly emerged ...

For years, infrastructure teams have treated compute as a relatively stable input. Capacity was provisioned, costs were forecasted, and performance expectations were set based on the assumption that identical resources behaved identically. That mental model is starting to break down. AI infrastructure is no longer behaving like static cloud capacity. It is increasingly behaving like a market ...

Resilience can no longer be defined by how quickly an organization recovers from an incident or disruption. The effectiveness of any resilience strategy is dependent on its ability to anticipate change, operate under continuous stress, and adapt confidently amid uncertainty ...

Mobile users are less tolerant of app instability than ever before. According to a new report from Luciq, No Margin for Error: What Mobile Users Expect and What Mobile Leaders Must Deliver in 2026, even minor performance issues now result in immediate abandonment, lost purchases, and long-term brand impact ...

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 ...

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

While 87% of manufacturing leaders and technical specialists report that ROI from their AIOps initiatives has met or exceeded expectations, only 37% say they are fully prepared to operationalize AI at scale, according to The Future of IT Operations in the AI Era, a report from Riverbed ...

Many organizations rely on cloud-first architectures to aggregate, analyze, and act on their operational data ... However, not all environments are conducive to cloud-first architectures ... There are limitations to cloud-first architectures that render them ineffective in mission-critical situations where responsiveness, cost control, and data sovereignty are non-negotiable; these limitations include ...

For years, cybersecurity was built around a simple assumption: protect the physical network and trust everything inside it. That model made sense when employees worked in offices, applications lived in data centers, and devices rarely left the building. Today's reality is fluid: people work from everywhere, applications run across multiple clouds, and AI-driven agents are beginning to act on behalf of users. But while the old perimeter dissolved, a new one quietly emerged ...

For years, infrastructure teams have treated compute as a relatively stable input. Capacity was provisioned, costs were forecasted, and performance expectations were set based on the assumption that identical resources behaved identically. That mental model is starting to break down. AI infrastructure is no longer behaving like static cloud capacity. It is increasingly behaving like a market ...

Resilience can no longer be defined by how quickly an organization recovers from an incident or disruption. The effectiveness of any resilience strategy is dependent on its ability to anticipate change, operate under continuous stress, and adapt confidently amid uncertainty ...

Mobile users are less tolerant of app instability than ever before. According to a new report from Luciq, No Margin for Error: What Mobile Users Expect and What Mobile Leaders Must Deliver in 2026, even minor performance issues now result in immediate abandonment, lost purchases, and long-term brand impact ...

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 ...