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About 300 hours of video are uploaded to YouTube every minute. The main technology to delivery YouTube content to various clients is HTTP adaptive streaming and the majority of today’s internet traffic comprises streaming audio and video. In this paper, we in- vestigate content provisioning for HTTP adaptive streaming under predefined aspects representing content features and upload charac- teristics as well and apply it to YouTube. Additionally, we compare the YouTube’s content upload and processing functions with a commercially available video encoding service. The results reveal insights into YouTube’s content upload and processing functions and the methodology can be applied to similar services. All experi- ments conducted within the paper allow for reproducibility thanks to the usage of open source tools, publicly available datasets, and scripts used to conduct the experiments on virtual machines.