Stef van der Ziel, our keynote speaker, has been in the streaming industry since 1994, and as founder of Jet-Stream, oversaw the development of Jet-Stream Cloud, a European-based streaming platform. He discussed the challenges associated with creating your own encoding infrastructure, how to choose the best transcoding technology, and the cost savings available when you build your own platform.
Stef started by recounting the evolution and significance of transcoding in the streaming industry. To help set the stage, he described the streaming process, starting with a feed from a source like a camera. This feed is encoded and then transcoded into various qualities. This is followed by origin creation, packaging, and, finally, delivery via a CDN.
Stef emphasized the distinction between encoding and transcoding, noting that the latter is mission-critical too. If errors occur during transcoding, the entire stream can fail, leading to poor quality or buffering issues for viewers.
He then related that quality and viewer experience are paramount for transcoding services, regardless of whether they are cloud-based or on-premises. However, cost management is equally crucial.
Beyond the direct costs of transcoding, incorrect settings can lead to increased bandwidth and storage costs. Stef noted the often-overlooked human operational costs associated with managing a streaming platform, especially in the realm of transcoding. Expertise is essential, necessitating either an in-house team or hiring external experts.
Stef observed that while traffic prices have decreased significantly over the years, transcoding costs have remained relatively high. However, he noted a current trend of decreasing transcoding costs, which he finds exciting.
Lastly, in line with the theme of sustainable streaming, Stef emphasized the importance of green practices at every step of the streaming process. He mentioned that Jet-Stream has practiced green streaming since 2004 and that the intense computational demands of transcoding and analytics make them resistant to green practices.
CHOOSING TRANSCODING OPTIONS
In discussing transcoding options, Stef related that CPU-based encoding can deliver very good quality, but that it’s costly in terms of CPU and energy usage. He noted that the quality of GPU-based encoding was lower than CPU and less cost and power efficient than ASICs.
FIGURE 1. Stef found CPU and ASIC-based transcoding quality superior to GPU-based transcoding.
The real game-changer, according to Stef, is ASIC-based encoding. ASICs not only offer superior quality but also minimal latency, a crucial factor for specific low-latency use cases.
Compared to software transcoding, ASICs are also much more power efficient. For instance, while CPU-based transcoding could consume anywhere from 2,800 to 9,000 watts for transcoding 80 OTT channels to HD, ASIC-based hardware transcoding required only 308 watts for the same task. This translates to an energy saving of at least 89%.
Beyond energy efficiency, ASICs also shine in terms of scalability. Stef explained that the power constraints of CPU encoding might limit the capacity of a single rack to 200 full HD channels. In contrast, a rack populated with ASIC-based transcoders could handle up to 2,400 channels concurrently. This capability means increased density, optimized use of rack space, and overall heightened efficiency.
Not surprisingly, given these insights, Stef positioned ASIC-based transcoding as a clear frontrunner over CPU- and GPU-based encoding methods.
OTHER FEATURES TO CONSIDER
Once you’ve chosen your transcoding technology, and implemented basic transcoding functions, you need to consider additional features for your encoding facility. Drawing from his experience with Jet-Stream’s own products and services, Stef identified some to consider.
- Containerize operation in Kubernetes containers so any crash, however infrequent, is self-contained and easily replaceable, often without viewers’ noticing.
- Stack multiple machines to build a microcloud and implement automatic scaling and pooling.
Combine multiple technologies like decoding, filtering, origin, and edge serving, into a single server. That way, a single server can provide a complete solution in many different scenarios.
BEYOND THE BASICS
Beyond these basics, Stef also explained the need to add a flexible and capable interface to your system and to add new features continually, as Jet-Stream does. For example, you may want to burn in a logo or add multi-language audio to your stream, particularly in Europe. You may want or need to support subtitles and offer speech-to-text transcription.
If you’re supporting multiple channels with varying complexity, you may need different encoding profiles tuned for each content type. Another option might be capped CRF encoding to minimize bandwidth costs, which is now standard on all NETINT VPUs and transcoders. On the distribution side, you may need your system to support multiple CDNs for optimized distribution in different geographic regions and auto-failover.
Finally, as your service grows, you’ll need interfaces for health and performance status. Some of the performance indicators that Jet-Stream systems track include bandwidth per stream, viewers per stream, total bandwidth, and many others.
The key point is that you should start with a complete list of necessary features for your system and estimate the development and implementation costs for each. Knowledge of sophisticated products and services like those offered by Jet-Stream will help you understand what’s essential. But you really need a clear-eyed view of the development cost and time before you undertake creating your own encoding infrastructure.
COST AND ENERGY SAVINGS
Fortunately, it’s clear that building your own system can be a huge cost saver. According to Stef, on AWS, a typical full AC channel would cost roughly 2,400 euros per month. By creating his own encoding infrastructure, Jet-Stream reduced this down to 750 euros per month.
FIGURE 2. Running your own system can deliver significant savings over AWS.
Obviously, the savings scale as you grow, so “if you do this times 12 months, times five years, times 80 channels, you’re saving almost 8 million euros.” If you run the same math on energy consumption, you’ll save 22,000 euros on energy costs alone.
By running the transcoding setup on-premises, the cost savings can even be doubled. On-premises is a popular choice to bring more control over core streaming processes back in house.
Overall, Stef’s keynote effectively communicated that while creating your own encoding infrastructure will involve significant planning and development time and cost, the financial reward can be very substantial.