4 ms·

Some quick math: last I heard, Lyft was doing 1M rides a day. That's 1M transactions per day, or "only" 11 transactions per second. Of course there's lot more (

by mv4 8y ago

Some quick math: last I heard, Lyft was doing 1M rides a day. That's 1M transactions per day, or "only" 11 transactions per second. Of course there's lot more (assuming 10x) supporting transactions to enable one ride - search, matching, status updates. Let's say that adds another 100 transactions per second. Rounding up to 150/sec. What am I missing? In terms of data usage and storage, matching is by geography, meaning their data is easy to shard. So, how's this $8M per month? edit: fixed a typo

thinkingkong 8y ago
Your math isnt wrong but the load isnt simply averaged out over the entire day. There will be peak capacity times way way higher than the lowest times. I would guess orders of magnitude larger. You have to build for peak capacity. If their target response time is 100ms or something then that adds in lots of complexity.
- mv4 8y ago
  I agree the load will fluctuate - but will mostly follow predictable patterns daily and weekly. However, that's what the cloud's elasticity is for - and AWS makes it easy (and inexpensive) to expand and contract when implemented correctly. Man, I would love an opportunity to optimize something like that!
  - MisterPea 8y ago
    Right?! The cost is way too high for their use case, even considering a large padding to OPs quick maths. Part of my team one month stopped all development and solely focused on reducing AWS costs and we cut our monthly bill by 50% (probably around 4 dev's yearly salary) It's not easy, but optimizing AWS resources is an absolute must.
kennywinker 8y ago
Idk, but I will say that there is definitely stuff going on beyond the ride. I.e. for every n people who open the app only a small number will book a ride. Billing services, driver location tracking, analytics stuff, etc are all going to balloon the amount of computing that the service uses.
wrs 8y ago
There are also location updates happening every few seconds for all active drivers, which is a lot of updates per second. Again, though, easily shardable.
m0zg 8y ago
>> So, how's this $8M per month? Microservices? :-)
buboard 8y ago
they must be running some gargantuan machinelearning/particle detecting/alien signal analyzing operation, otherwise its impossible to imagine where these levels of petaflops are being wasted
dillondoyle 8y ago
Also remember the drivers are sharing location constantly even when not currently driving a client. And I would guess your transactions per ride is off by at least one order of magnitude, especially if you count a transaction between services (e.g. gps to push, payment to user table, whatever)
tim333 8y ago
10x might be a bit low. During a ride the app is probably constantly in touch with the server updating its position and getting new maps, updates on the positions of others etc. Could be more like 10,000x? And when you are just walking around with the app in your pocket they may be tracking you - dunno.

by mv4 8y ago

thinkingkong 8y ago

Your math isnt wrong but the load isnt simply averaged out over the entire day. There will be peak capacity times way way higher than the lowest times. I would guess orders of magnitude larger. You have to build for peak capacity. If their target response time is 100ms or something then that adds in lots of complexity.

mv4 8y ago
I agree the load will fluctuate - but will mostly follow predictable patterns daily and weekly. However, that's what the cloud's elasticity is for - and AWS makes it easy (and inexpensive) to expand and contract when implemented correctly. Man, I would love an opportunity to optimize something like that!
- MisterPea 8y ago
  Right?! The cost is way too high for their use case, even considering a large padding to OPs quick maths. Part of my team one month stopped all development and solely focused on reducing AWS costs and we cut our monthly bill by 50% (probably around 4 dev's yearly salary) It's not easy, but optimizing AWS resources is an absolute must.

kennywinker 8y ago

Idk, but I will say that there is definitely stuff going on beyond the ride. I.e. for every n people who open the app only a small number will book a ride. Billing services, driver location tracking, analytics stuff, etc are all going to balloon the amount of computing that the service uses.

wrs 8y ago

There are also location updates happening every few seconds for all active drivers, which is a lot of updates per second. Again, though, easily shardable.

m0zg 8y ago

>> So, how's this $8M per month? Microservices? :-)

buboard 8y ago

they must be running some gargantuan machinelearning/particle detecting/alien signal analyzing operation, otherwise its impossible to imagine where these levels of petaflops are being wasted

dillondoyle 8y ago

Also remember the drivers are sharing location constantly even when not currently driving a client. And I would guess your transactions per ride is off by at least one order of magnitude, especially if you count a transaction between services (e.g. gps to push, payment to user table, whatever)

tim333 8y ago

10x might be a bit low. During a ride the app is probably constantly in touch with the server updating its position and getting new maps, updates on the positions of others etc. Could be more like 10,000x? And when you are just walking around with the app in your pocket they may be tracking you - dunno.