hi excited to be here my name is Chris
Lambert I'm the chief technology officer
with lyft and I'd like to tell you a
little bit about our journey from being
a small scrappy startup in San Francisco
to now being the fastest-growing
provider of on-demand transportation
here in the US along the way I'll
highlight how Amazon Web Services has
helped us move faster as a company and
scale our marketplace more efficiently
I'll start back in 2012 when Liv
launched it was a really simple service
for rides on demand you could pull out
your phone hit a button and within a few
minutes a driver would show you show up
and take you anywhere you wanted to go
when we launched it was just three
servers are running in you SES and
different availability zones and our
first very first lift ride was completed
on May 31st 2012 and it's funny because
the two engineers that had built the
first prototype weren't really sure how
it was going to work in production would
it actually would the state machine work
would the ride actually happen so when
they they were tailing logs and when
they saw the ride drop-off of an hit
production they're like well maybe it
worked we actually don't know so they
they called the driver and they said hey
this is lyft
did you drop Darryl off and the driver
said yeah he's they just ran off he's
not in the car they're like okay great
thanks and I don't know who was more
surprised like the engineers that this
works or the driver that they're gonna
get a phone call after every single
drop-off I asked if they dropped him off
but it was really early on it was three
weeks from from idea to actual launch
and we were 100% on AWS at the time the
only difference now we're still 100% on
AWS but were taking advantage of many
more Amazon technologies besides ec2 so
fast forward a year we had our first big
milestone as a company 1 million rides
completed in San Francisco is going like
crazy we had launched Los Angeles and a
few other cities and things were just
taking off you can get an idea of what
that growth looks like we're just
looking at the first 15 months here with
our path to 1 million rides and this is
continued for the the last four years
however that exponential growth is great
but it didn't prepare us for what was
about to happen we decided to launch 24
additional cities
in 24 hours this was a huge effort
across the company marketing operations
engineering and of course the
engineering approach to this problem was
well let's just let's get out of the way
let's enable auto scaling let's make it
so whatever happens in the real world
whether it's a rain storm or the Super
Bowl anything that happens we can handle
our infrastructure should just scale up
seamlessly so we rolled out auto scaling
just in time for our 24 City launch went
off without a hitch we doubled our
footprint overnight and you can just see
how significant this is that last little
tick there was all in 24 hours and that
was pretty massive growth for us as a
company an auto scaling works great for
applications here but there's one more
benefit you get from it which is that we
do eight times as many rides at peak on
a Saturday night as we're doing on a
Sunday morning
so auto scaling also allows us to scale
down our infrastructure to save a
significant amount on infrastructure
cost when we don't need to pay for it
so I mentioned auto scaling application
tier that's fantastic but what about
datastore one of our biggest data stores
was outgrowing its current technology
and we decided to move it to dynamo this
was the ride location tracking system so
every GPS location for all of our rides
was stored in this system we moved it
over to dynamo and it was so simple to
scale up you had two knobs one for right
capacity one for read capacity you
didn't have to carry a pager you didn't
have to deal with chunk migrations it
just worked really really well and we've
since moved many of our other data
stores over to dynamo as well the single
biggest launch in lives history came a
few months later this was lift line lift
line is our shared ride service what
that means is if two passengers have a
very similar route and they're
requesting to ride within a few minutes
of each other we can give them the
option to share that ride with the other
passenger for a significant savings
often up to 50% off their ride this
changed our business significantly and
it was possible because of some analysis
that our data sign
team did with our Amazon redshift data
warehouse so we had all of our data in
redshift and they basically would run
simulations every few months looking at
what would be possible in terms of new
transportation modes and they realized
that 90% of our rides at peak times were
Co similar enough to another ride where
we could actually build a shared ride
product so as soon as this was the case
we kicked off a few engineering teams
and we were able to launch lyft line
August 2014 and it's been the biggest
driver of growth in our biggest markets
and is the future of the company fast
forward a year we now have a
proliferation of many different micro
services all serving production traffic
at lyft and we wanted a really easy
simple way for them to communicate with
each other and we built this pub/sub
system on top of Amazon Kinesis that
funnels every single production event
through this system so every time you
open the app every time you request a
ride every time you move the car
actually moves it goes to this this
Kinesis pipeline and any other service
that lyft can subscribe for events they
can say I care about credit card ad so
our fraud system can say let me know
anytime someone adds a new payment
method removes a payment method
I want to rescore that users fraud risk
our dynamic pricing system could say let
me know every time a driver changes
neighborhoods because I want to make
sure I'm pricing these rides as
accurately as possible this is a really
complex infrastructure with a lot of
moving parts and it's all simple for us
because of Kinesis October 2015 was
three you know three years after we
launched huge milestone billion dollar
annual run rate business is just bigger
than it's ever been to give you a sense
of scale right now there are over 10,000
people in lift rides across the country
for them they're getting getting to work
seeing friends seeing family relying on
lift for their their income downtime is
not an option for us and we've been able
to pen on a baby AWS
to provide the level of reliability and
and availability that our users have
come to expect from lyft so I talked a
little bit about the services we have in
production on March 20 16th we added our
hundreth micro service
these are all again managed
independently scaled automatically and
these services are collectively serving
over a million requests per second this
is what powers lift every time you
request a ride you're not just hitting a
single service you're probably hitting
10 or 20 different services that are
working together to make that ride go as
smooth as possible and just to give you
a little bit of insight that this is the
the set of Amazon services we're using
today in production these are all taking
rail traffic seems have depended on them
and they've all worked really really
well for us over the last four years so
last big announcement I'm excited to say
as of last month we completed 14 million
rides just for context it took us 15
minutes 15 months to get to our first
million and in the last month we've done
14 times that alone it's our biggest
month ever by pretty much any metric
we're credibly excited to be here or
hiring in San Francisco in Seattle love
to have you help come join build the
future of lyft and continue to use AWS
whenever it makes sense for our business
so thank you for having me