The Importance Of CDN Selection To Achieve Broadcast-Grade Streaming Experiences - Part 1

Multi-CDN is a standard model for today’s D2C Streamers, which automatically requires a CDN selection solution. As streaming aims to be broadcast-grade and cost-effective, how are CDN Selection solutions evolving to support these objectives?


Other articles in this series:


The Rise Of Multi-CDN & CDN Selection

For a long time, CDN selection and multi-CDN were in a chicken-and-egg situation – how could one emerge and grow without the other? To many D2C Streamers, multi-CDN was not a priority because price and quality were good enough from their single supplier. Plus, a multi-CDN set-up brought new complexities such as managing multiple suppliers, inserting an extra layer of technology into the chain, and supporting multiple delivery points from the Origin.

But things changed as content delivery volumes increased. The CDN market began to see significant price competition. CDNs started to have failures and “good-enough performance” was no longer good enough for D2C Streamers seeking strong business results from their growing investments.

Today, the standards expected from a streaming service are high, both from consumers and from media executives. Quality must be as close to broadcast-grade as possible, to deliver an excellent Quality of Experience (QoE) which leads to better viewer engagement and lower customer churn. Delivery cost must enable a streaming service to economically scale as the volume of content delivered grows exponentially and peak audiences expand towards the size of traditional prime-time linear TV audiences.

With these market-level changes, multi-CDN has taken off and solidified the demand for CDN selection solutions.

Initially, CDN selection was simple. The primary function was to allocate enough traffic to each CDN to ensure that committed traffic levels and expected price per unit of delivery were achieved. But as multi-CDN has matured, and the business importance of streaming has grown, CDN selection has become much more sophisticated.

Now, D2C Streamers require CDN Selection solutions to deliver multiple business-critical benefits such as avoiding service outages and reducing churn, eliminating capacity bottlenecks, enabling a global streaming product strategy with consistent distribution platform implementation, and tailoring distribution methods to meet various budgets and performance needs.

Today’s Best Practice

From a technology perspective, there are three areas of focus to assure a high quality of streaming content delivery. First, the actual delivery platform itself – the encoder, packager, origin and CDN. Second, the player – ensuring it works well with the wide range of devices. Third, the choice of profiles – encoding profiles must be handled well by the whole delivery chain from encoder to player.

CDN is the primary item in these focus areas where second-by-second dynamism exists. It is important to consider subjects like network performance variability, network scalability, network location, network type, network capacity, and potentially highly variable costs (figure 1). In other words, the way the whole network infrastructure performs after the Origin and before the Player can be impacted by many factors that are outside the control of the technical decisions made by the D2C Streamer.

Therefore, today’s CDN Selection best practice is based on sophisticated and real-time decision-making logic to adapt quickly to changes in the network environment that affect stream performance.

Figure 1: Considerations involved in multi-CDN set-up and CDN selection.

Figure 1: Considerations involved in multi-CDN set-up and CDN selection.

Because different CDNs will have different answers to the questions in Figure 1, D2C Streamers need to closely manage their relationships with each CDN provider. The focus on multi-CDN has led to D2C Streamers working to obtain cost parity between CDNs, in order that the CDN selection process can predominantly focus on performance, which is where the impactful day-to-day variability is observed.

Within the focus on performance, the subjects of CDN capacity location, capacity transparency, and capacity guarantees have become the latest hot topics. Simply “delivering 50PB in a month” is not enough. The delivery of those 50PB must meet exacting performance standards. It is like asking a courier to not just drop the package at the right address, but also ensure the customer receiving it is impressed with the condition of the package and the level of customer care and attention provided.

Leading D2C Streamers today engage in dynamic CDN measurement and selection. This enables real-time decision-making at every moment of the day. CDN capacity utilisation (i.e., consumer demand) can vary easily depending on consumer behaviour and the content publication activities driven by all the businesses simultaneously utilising the CDN capacity. Capacity supply can also vary due to outages and planned maintenance, not only at the CDN level but also at the ISP level which can force large-scale stream re-routing. Regardless, the streaming show must go on and the streams must somehow be delivered well.

Dynamic CDN Measurement & Selection

Leading CDN Selection solutions enable D2C Streamers to operate dynamically. They offer powerful configuration abilities that can apply, in real-time, all defined business rules at a very granular level and optimise stream performance across a range of KPIs that can be defined and prioritised by the D2C Streamer.

The theoretical design of these solutions is relatively straightforward. The acid test is how they practically perform under real-life conditions, handling all required real-time computational processing. Although it may be possible in the CDN Selection system to drill down to device type and operating system type by country, ISP and ASN, and make delivery choices depending on live vs. VOD and the type of bitrate profile for different content, the reality is that making large-scale, real-time CDN selection choices at this level might be impractical. But as the world of streaming continues to evolve, these granular capabilities will become critical to success.

Figure 2: High-level CDN selection process.

Figure 2: High-level CDN selection process.

As shown in Figure 2, CDN selection is an initial task for each stream request, which becomes a continuous task as the stream is delivered to the consumer over time. Some CDN Selection solutions start with the premise that multi-CDN selection will first be driven by commercial rules that are fixed, such as minimum delivery commitments in a contract. This will set an initial business rule to deliver a certain quantity to one CDN which will primarily be managed by allocating a percentage of traffic to that CDN. This percentage-based solution, which depends on accurately forecasting total content delivery to allocate delivery correctly between CDNs, can lead to under- or over-utilisation of a particular CDN. Therefore some solutions have moved away from having percentage-allocation as a primary rule and instead they allow CDN Selection decisions to initiate with a wide range of factors, like capacity availability (e.g., I have 1 Tbps of capacity on my private CDN that must always be fully utilised), region (e.g., I deliver all my content in Germany, and I should deliver 100% of my content in the Frankfurt region to ISP “1” using CDN “A”), and content type (e.g., deliver 4K live content on CDN A, deliver all other content on any CDN).

The granularity of these business rules depends on how the content, network, and consumer are understood by the system. If the understanding is high-level - “the consumer is on ISP 1 in Country 1” (i.e., a simple DNS approach) - then CDN Selection simply passes responsibility for good delivery to the CDN. But if it is possible to understand the consumer’s location more precisely (e.g., through eDNS0 implementations) and profile (i.e., with client-side data), and it is possible to understand how the CDN is configured in terms of server locations, capacity availability, connectivity types with ISPs, etc., then CDN selection can be highly sophisticated, and the D2C Streamer can have more control of the delivery process.

Once a CDN has been initially selected by these business rules, then the next step is to complete the selection based on performance. Using performance checks is a win-win for the D2C Streamer and the CDN, because content will only be allocated for delivery on a CDN if it is performing well enough at that time.

Performance decisions need to be based on QoE and QoS, as measured by the client-side tools and the server-side tools. QoE takes priority in most solutions, which includes measures like rebuffering ratio, start-up time, start-up errors, and sustained bitrate. The CDN Selection tools must have granular, real-time data for all these metrics to support good decisions.

“In the NPAW Suite there are over 70 different quality KPIs and more than 90 different metadata elements associated with each playback,” states NPAW’s CDN Balancer Business Unit Head, Luis Lopez Chousa. “Analysing this multi-dimensional data matrix in real-time can involve millions of calculations, which means D2C Streamers can make pinpoint automated decisions about how to deliver their content given the environmental conditions at the time.”

Jose Jesus, Director of Product for Experience Insights Suite at Conviva, states “D2C Streamers normally set up business policies to meet their CDN commitments while at the same time using each CDN when and where it performs best. It is important that algorithms optimise performance within business policy constraints, but if a CDN’s performance deviates too far from the baseline then it needs to be temporarily avoided. Typical metrics D2C Streamers want to improve are connection induced rebuffering ratio, bitrate, technical video start-up failures, and technical video playback failures”.

Once a CDN has been selected Switching Modes ensure that the usage of each CDN is maximised for ongoing cost and performance. There are multiple switching modes as described in Figure 3.

Figure 3: Descriptions of Switching Modes in leading CDN Selection solutions.

Figure 3: Descriptions of Switching Modes in leading CDN Selection solutions.

Part 1 of this article has described the existing best practices. Part 2 describes more forward-looking capabilities that are set to take CDN Selection capabilities to the next level.

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