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Since announcing the Backblaze + Vultr partnership last year<\/a>, we\u2019ve seen our mutual customers build a wide variety of applications combining Vultr\u2019s Infrastructure Cloud with Backblaze B2 Cloud Storage, taking advantage of zero-cost data transfer between Vultr and Backblaze. This week, Vultr announced Optimized Cloud Compute instances<\/a>, virtual machines pairing dedicated best-in-class AMD CPUs with just the right amount of RAM and NVMe SSDs.<\/p>\n To mark the occasion, I built a demonstration that both showcases this new capability and gives you an example application to adapt to your own use cases.<\/p>\n Imagine you\u2019re creating the next big video sharing site\u2014CatTube\u2014a spin-off of Catblaze<\/a>, your feline-friendly backup service. You\u2019re planning all sorts of amazing features, but the core of the user experience is very familiar:<\/p>\n Let\u2019s take a high-level look at how this might work…<\/p>\n The user will upload their video to a web application from their browser or a mobile app. The web application must store the uploaded user videos in a highly scalable, highly available service\u2014enter Backblaze B2 Cloud Storage<\/a>. Our customers store, in the aggregate, petabytes of media data including video, audio, and still images.<\/p>\n But, those videos may be too large for efficient sharing and streaming. Today\u2019s mobile devices can record video with stunning quality at 4K resolution, typically 3840\u2009\u00d7\u20092160 pixels. While 4K video looks great, the issue is that even with compression, it\u2019s a lot of data\u2014about 1MB per second. Not all of your viewers will have that kind of bandwidth available, particularly if they\u2019re on the move.<\/p>\n So, CatTube, in common with other popular video sharing sites, will need to convert raw uploaded video to one or more standard, lower-resolution formats, a process known as transcoding.<\/p>\n Transcoding is a very different workload from running a web application\u2019s backend. Where an application server requires high I\/O capability, but relatively little CPU power, transcoding is extremely CPU-intensive. You decide that you\u2019ll need two sets of machines for CatTube\u2014application servers and workers. The worker machines can be optimized for the transcoding task, taking advantage of the fastest available CPUs.<\/p>\n For these tasks, you need appropriate cloud compute instances. I\u2019ll walk you through how I implemented CatTube as a very simple video sharing site with Backblaze B2 and Vultr\u2019s Infrastructure Cloud using Vultr\u2019s Cloud Compute instances for the application servers and their new Optimized Cloud Compute instances for the transcoding workers.<\/p>\n The video sharing example comprises a web application, written in Python using the Django web framework<\/a>, and a worker application, also written in Python, but using the Flask framework<\/a>.<\/p>\n Here\u2019s how the pieces fit together:<\/p>\n These steps are illustrated in the diagram below.<\/p>\n There\u2019s a more detailed description in the Backblaze B2 Video Sharing Example GitHub repository<\/a>, as well as all of the code for the web application and the worker. Feel free to fork the repository and use the code as a starting point for your own projects.<\/p>\n Here\u2019s a short video of the system in action:<\/p>\n\n
Transcoding Explained: How Video Sharing Sites Make Videos Shareable<\/strong><\/h2>\n
Building a Video Sharing Site With Backblaze B2 + Vultr<\/strong><\/h2>\n
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