It only looks super obvious in hindsight and the well explained blog post. when a team of 5 is tasked with getting a completely new DNS up at the scale and integrate well with cloudflare.

if you spend cycles on nitty gritty opinions like this time to market goes out further and further out. some napkin math, 130 gen13 servers cost "only" ~$2.6M. relative to the importance of the 1.1.1.1 and the market at the time. that is nothing to cloudflare.

this is not to say good system design does not matter. it very much does, but making that call at that time would've butchered the prodcut very much similar to google+, youtube etc.

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eviks 3 hours ago | parent [-]

This one also looks pretty obvious "in foresight" (using the same tools that existed back then. Maybe owner dedupe might be less obvious and require a bit of knowledge and probing into actual data, but for rw vs ro you are fine knowing nothing?) and you forgot the napkin math re. how much your precious "time to market" would have been delayed by.

It's also not nothing, otherwise it would never be optimized away now, but left as is. After all, wasting time on optimization delays "time to market" for other useful features.

I also don't get the reference to YouTube, it's a very successful product, how was it butchered by good system design???

	▲	sophacles 9 minutes ago \| parent [-]
		Imagine you're an engineer at cloudflare, an 8 year old (at the time of launch of 1.1.1.1) company. The company is wildly popular and any service launched is going to have a lot of traffic and a lot of attacks right away. Any problems with it are going to embarass the company a lot. You're tasked with making a DNS caching recursive resolver that can operate at a large scale and will be run on thousands of servers each of which has a lot of GBs of ram. You are given some period of time to build this and make it production ready. How do you spend your time: * Focusing on making sure that the resolver works correctly? * Focusing on make sure that it actually provides improved DNS performance for internet users? * Handles an very large number of record requests/s? * Saves a few GB of ram per server? There are tradeoffs to consider. RAM is cheap, even at today's prices RAM is not the most expensive thing that can go wrong in such a scenario. Having the responses be slow or incorrect is a far more expensive problem. A good engineer would pick a simple data structure that has the right shape but might not be optimal in footprint to focus on correctness and response time. The few extra GBs of RAM per server can be dealt with later. When building things at scale you want to make sure it works correctly, fails correctly, and does the thing quickly before worrying about reducing resource consumption. I've never seen a project fail on Vec<T> vs Box<[T]> memory differeneces, or even on a few GBs of RAM usage per instance. I have seen them fail on "one wierd corner case of correctness" though, and on poorly thought through failure modes.