
Scalability at YouTube
About this video
A PyCon 2012 talk by early YouTube engineer Mike Solomon on how YouTube scaled its architecture, which is mostly Python.
Why it appears in the archive
HN mostly cites it as evidence that YouTube was built on Python and as background on how it scaled.
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From the Hacker News discussion
YouTube (owned by Google) is mainly Python. Here a talk from Pycon 2012, the technical part starts around 10 min. in: [VIDEO]
Read original comment ↗The real beauty of Python is the fact that it is easy for beginning programmers, yes, but it has also a lot to offer for experienced coders concerning all the advanced things they might need. It's no accident that services like Dropbox[1] or YouTube[2], both arguably very complex systems, are relying on Python as their language of choice. [1] [LINK] [2] [VIDEO]
Read original comment ↗>Facebook and YouTube were both created later, and in PHP youtube was always done in python as far as I understand. [VIDEO] But yeah, back in 2002-3 coldfusion was an option.
Read original comment ↗Scalability at YouTube: [VIDEO] The Python is the less likely think that will suffocate you. What did you suffer from in past projects with each of these languages?
Read original comment ↗For reference, YouTube runs on Python[1,2,3]: > 1. Python and Django: YouTube’s backend is predominantly written in Python, offering a balance of performance and readability. > 2. Google Cloud Platform... > 3. Java and C++: YouTube also utilizes Java and C++ for specific backend services, as they provide better performance for certain tasks. --- A long time ago, I looked into these Python frameworks: - [LINK] - [LINK] [1]: [LINK] [2]: [LINK] [3]: [VIDEO]
Read original comment ↗They improve their stack on multiple fronts 1 - They use their own custom hardware encoders now optimised for their scale (previously they’d use a ton of intel cpu for encoding) This is often not possible for smaller startups to have their own custom hardware, but one could setup their own Xilinx FPGA based hardware accelerated encoding servers, Xillinx Alveo Boards are popular for media acceleration, they support both ffmpeg and gstreamer for acceleration needs. Nvidia Nvenc encoding is decent too but mostly for the most popular encoding types, and honestly an fpga based accelerator is probably better after cpu unless you have gpus lying around. 2 - Much lower bandwith costs, a lot of startups build their streaming applications on top of AWS, but that’s insanely expensive due to the insanely expensive price of AWS itself As a streaming service you could immediately cut down costs by shifting to ovhcloud, hetzner etc, they often have dedicated gameserver like offerings which are beneficial for streaming usecases too. That itself should allow you to bring down costs by 10x or even more (you have to choose the plan correctly on other tho, ovh, hetzner etc say you have unlimited bandwith on some packages but there is always a catch or they throttle you later, need to be careful about the offering you choose but otherwise a lot better) 3 - Having colocation hosts with your own servers setup and each video encoded at different sizes for different media devices also help only sendi
Read original comment ↗