Stop releasing bugs with fully automated end-to-end test coverage (Sponsored) Bugs sneak out when less than 80% of user flows are tested before shipping. But how do you get that kind of coverage? You either spend years scaling in-house QA — or you get there in just 4 months with QA Wolf
You know what the really incredible scale issue this article highlights? The absolutely staggering expenditure of time and resources for such a banal outcome.
To paraphrase Hayao Miyazaki, this model of online service was a mistake. I'm not bashing on FAANG, either; The company I recently started working for as a contractor is much smaller than them but it's equally wasteful: dozens of engineers just to book and manage appointments for an outpatient medical procedure — something that prior to the Internet people used to manage just fine by ringing up their local clinic and making an appointment with the receptionist. How on earth is this an improvement for humanity or the public, or even the patients? I understand the value proposition to the company —and the value proposition to my bank account which feeds and keeps a roof over my family — but I fail to understand the genuine need and benefit for end users or clinicians, really. What a time to be alive!
Netflix has always been at the cutting edge of high performance streaming. Curious if other streaming platforms like Disney+ or HBO have made the same R&D investments as Netflix to stay performant. Netflix just seems so much further ahead.
That is an excellent summary of the technology stack employed by Netflix.
I spent several hours creating a visual guide on How Netflix Uses Machine Learning To Decide What Content To Create Next For Its 260M Users. 🎬
TL;DR: "Embeddings" - capturing a show's essence to find similar hits & predict audiences across regions. This helps Netflix avoid duds and greenlight shows you'll love.
You know what the really incredible scale issue this article highlights? The absolutely staggering expenditure of time and resources for such a banal outcome.
To paraphrase Hayao Miyazaki, this model of online service was a mistake. I'm not bashing on FAANG, either; The company I recently started working for as a contractor is much smaller than them but it's equally wasteful: dozens of engineers just to book and manage appointments for an outpatient medical procedure — something that prior to the Internet people used to manage just fine by ringing up their local clinic and making an appointment with the receptionist. How on earth is this an improvement for humanity or the public, or even the patients? I understand the value proposition to the company —and the value proposition to my bank account which feeds and keeps a roof over my family — but I fail to understand the genuine need and benefit for end users or clinicians, really. What a time to be alive!
Netflix has always been at the cutting edge of high performance streaming. Curious if other streaming platforms like Disney+ or HBO have made the same R&D investments as Netflix to stay performant. Netflix just seems so much further ahead.
What an interesting read. I had no idea Netflix was originally built on microservices.
Their evolution is fascinating, and as a consumer of several different streaming services, it feels like Netflix is still ahead of the curve.
That is an excellent summary of the technology stack employed by Netflix.
I spent several hours creating a visual guide on How Netflix Uses Machine Learning To Decide What Content To Create Next For Its 260M Users. 🎬
TL;DR: "Embeddings" - capturing a show's essence to find similar hits & predict audiences across regions. This helps Netflix avoid duds and greenlight shows you'll love.
Here is a visual guide covering key technical details of Netflix's ML system: https://codecompass00.substack.com/p/how-netflix-uses-machine-learning