Netflix Tech Blog

I find that medium is even moving articles behind paywall even without consent from author. It was not happening earlier. For example - Look at Netflix Medium blog https://medium.com/@NetflixTechBlog There are few stories which are behind paywall. Do you think Netflix would have marked them explicitly behind paywall to earn money from blog?

I've been looking for a reason to dig into this tool. For those who haven't heard of RiskQuadrant, Netflix put out an article about the project about two weeks ago: https://medium.com/@NetflixTechBlog/open-sourcing-riskquant-a-library-… The project itself is at: https://github.com/Netflix-Skunkworks/riskquant.

A few I like on top of what has already been mentioned: http://rachelbythebay.com/w/ http://highscalability.com/ https://medium.com/@NetflixTechBlog

The blog post announcing this might be a better read: https://medium.com/@NetflixTechBlog/performance-under-load-3e6fa9a6058… (And while reading that and thinking "I swear I recently read something else talking about applying TCP congestion control to RPC queueing". And indeed I had: http://www.evanjones.ca/prevent-server-overload.html)

I think their point is basically "It doesn't matter" - any client that sends a request which then gets rejected automatically retries and is bound to get a server that is up and has capacity. The retry happens so fast that even with just a naive retry implementation, the end-user won't even notice the interruption. From https://medium.com/@NetflixTechBlog/performance-under-load-3e6fa9a6058… > The discovered limit and number of concurrent requests can therefore vary from server to server, especially in a multi-tenant cloud environment. This can result in shedding by one server when there was enough capacity elsewhere. With that said, using client side load balancing a single client retry is nearly 100% successful at reaching an instance with available capacity. Better yet, there’s no longer a concern about retries causing DDOS and retry storms as services are able to shed traffic quickly in sub millisecond time with minimum impact to performance. Edit: In terms of how they decide what to reject, from reading the blog post, there is a queue and there is a limit to how big the queue can be. Requests that come in while the queue is "full" get rejected immediately. They don't wait in the queue and timeout.