How does this corrospond with growth? I imagine having 100% uptime is much harder the bigger a platform is, so did Github grow a lot in the same period?
I’m not questioning wether or not Microsoft has issues, I just find it relevant wether or not they very suddenly saw a 2000% increase in server usage or something.
I imagine having 100% uptime is much harder the bigger a platform is, so did Github grow a lot in the same period?
its not there are scale points where once you hit a critical number you need to re-architect your backend. 1k,10k,1mil, etc. usually these vary based on your app. but they’re usually exponential so once you hit the higher levels it takes much longer to reach the next level.
on top of that you usually by the higher tiers have proper backpressure and signals being sent to the frontend systems to dynamically manage the load generated. so suddenly uptime is much easier.
when you see large repeated failures like this the cause is almost always corporate causing issues.
reducing engineering budget.
not listening to engineering department on product decisions. (see the recent product manager AI generated commit that got merged and caused a mild uproar of 'co authored by copilot)
rushing nonsense out before its ready.
it this particular case i bet it cutting engineering head count and increase AI slop generated code without proper review by engineers. which ive been hearing a lot more from my engineering friends.
How does this corrospond with growth? I imagine having 100% uptime is much harder the bigger a platform is, so did Github grow a lot in the same period?
I’m not questioning wether or not Microsoft has issues, I just find it relevant wether or not they very suddenly saw a 2000% increase in server usage or something.
its not there are scale points where once you hit a critical number you need to re-architect your backend. 1k,10k,1mil, etc. usually these vary based on your app. but they’re usually exponential so once you hit the higher levels it takes much longer to reach the next level.
on top of that you usually by the higher tiers have proper backpressure and signals being sent to the frontend systems to dynamically manage the load generated. so suddenly uptime is much easier.
when you see large repeated failures like this the cause is almost always corporate causing issues.
it this particular case i bet it cutting engineering head count and increase AI slop generated code without proper review by engineers. which ive been hearing a lot more from my engineering friends.