PRANAV NAMBIAR: Hello, everyone.
Welcome to Data Cloud Summit.
Welcome to the session on solving for the future
with Cloud Spanner.
In today's session, we're going to focus
on how Walmart goes about building
its next-generation data platform using Cloud Spanner.
My name is Pranav Nambiar.
I'm a director of product management on Google Cloud.
I also have with me Bob Lowell, who's
a senior director of engineering at Walmart.
Together, we are today going to talk more about Cloud Spanner
and how you can go about your digital transformation journey
using this service.
In today's world, we put a very high bar
on customer experience.
And what we're seeing is that digital innovators
are disrupting traditional industries
by finding unique ways to manage their data to deliver highly
personalized and enriching digital experiences.
Whether it's a ridesharing application, or a gaming
experience, or a retail experience, or a payments
platform, across the board, there's
a very high bar on delivering differentiated customer
experience.
But to deliver a differentiated experience,
you need sophisticated applications.
You need applications that can scale to millions of users.
That way, you don't end up with a crashed application
when you have a lot of customers.
You need applications that don't go down.
You need applications that are very flexible,
that are very performant and secure.
You need to be able to leverage your application
to deliver an enriching digital experience.
When you look at all this from a high level,
you will see that the most controlling factor here
is your data management layer that you have
your business-critical data.
This is the data that is critical to innovating
on your customer experience.
To put another way, to build innovative customer
experiences, you need transformative databases
to hold your operational data.
You need a database that delivers
you industry-leading availability
without any concept of a maintenance downtime.
You need a database that can scale
to whatever needs you want without you
having to manually shard your data and manage your database.
You need a database that can manage faults automatically,
that can be price-performant and secure.
All in all, I'm sure you have faced similar problems
with your databases.
Google, too, went through the same problems
with its applications.
And after a lot of research and effort,
the end result was Cloud Spanner.
Cloud Spanner is our horizontally scalable
relational database that provides you ACID transactions
and SQL capabilities at pretty much any scale, with five
nines of availability, [? easily. ?] Today,
Spanner is used by a number of large customers.
Spanner also powers most of Google's large applications.
In fact, Spanner today powers more than 2 billion requests
per second at peak.
If you think about it, to operate at this level of scale,
you need a system that is really pressure-tested in a very
intense and highly demanding environment.
And it's very difficult to find similar systems out there.
On that note, let me invite Bob, who's
going to share with you Walmart's perspective on Cloud
Spanner and provide you more details into how
they went about their digital transformation journey.
Over to you, Bob.
BOB LOWELL: Hey, thanks, Pranav.
Appreciate it.
Appreciate the opportunity to share our journey.
I've been doing database administration and engineering
for a long time, as you can see on the slide.
I've been lucky enough to spend a good chunk of my career
at Walmart, where the scale and complexity of the problem
statement is fairly unrivaled.
I came to Walmart to really help them
with their journey to cloud, specifically around data.
And the problem statement is basically how can we
build a platform that enables our application developers
to focus on the business problems
and deliver them a platform where they can access,
store, secure, and enter their data into a complete data
ecosystem without having to architect that all themselves.
So Walmart is, obviously, a big operation.
It's also a global operation.
We've got 11,000 stores across the world
in 20 different countries.
Some more interesting facts about Walmart's scale
and the impact that Walmart can have--
that's one of the most exciting things to me
about working at Walmart, is the impact that we can have--
Suresh Kumar, our CTO, said the other day, at Walmart,
you can write a single line of code
that can improve the lives of millions of people.
It's true, and it's very powerful.
The ability for us to help deliver these experiences
is very motivating.
The other thing that stands out to me on this slide
is 2.2 million employees worldwide.
You think about that, and even the HR systems at Walmart scale
well beyond what most companies have to deal with.
So digital transformation at the scale of Walmart
is a pretty consistent thing, right?
We can't take 40,000 or so different database systems
and just upgrade them or change them overnight.
You have to attach to building great customer experiences.
You have to attach to what the company is
trying to do to find the right opportunities.
We spend a lot of time working on omnichannel experiences,
the merging of online and in-store experiences
so the line is blurred between the two.
We modernize the platform by aligning with those experiences
that Walmart wants to create in order
to transform the business.
And that's how we get the-- we call
them locomotives to pull our technologies forward
with the locomotives of transformative experiences.
So this is just a quick picture of how we
have our system of record data.
We basically have, you can see, a good chunk
of relational databases--
relational databases have been the powerhouse
for many, many years--
mainframe databases, as well as some MySQL databases.
So what's the problem with that?
Walmart has to have elastic scale.
As you can probably guess, Black Friday, Cyber Monday, we
scale sometimes 10 to 100x what we
would be doing in a normal day.
We have to have great HADR BC because one minute of downtime
is huge revenue loss for Walmart,
and we really can't afford it.
We can't afford an active/passive system
that's going to take me three, four minutes to failover.
Sharding is something we've done in the past.
We have a lot of sharded systems,
but it adds a lot of complexity.
There's a limit to the vertical scaling
that you can do with a relational database,
and it forces you into partitioning
in ways that might not be natural for the application.
We need to be able to get data downstream to all
of our customers.
Relational databases have some decent tools for that,
but not everything does.
We need to be able to capture metadata and push
that downstream, as well.
Jumping to the bottom one there, NoSQL
solves a lot of these problems, but the lack
of transactionality is really difficult
when you're talking about payment systems
or capturing transactions that really need to be captured
in an ACID-compliant way.
So as we're looking at our transformation,
we have a set of principles that we look at in order
to guide us on that journey of taking a technology
and transforming-- or taking an application, really,
and transforming the way that we're going
to build a platform for it.
First of all, we want to be cloud-native.
We need to take advantage of all the availability
and the geodistribution that cloud-native
can offer, the elasticity that cloud-native can offer.
And the first thing you really need to do
is understand your access patterns
for different applications, understand what the business is
trying to accomplish.
Those things go hand in hand.
You need to really deeply understand
what the business is trying to do in order to apply
the right technology to it.
So you need to look at representative workloads.
You need to benchmark.
We need to figure out the best way to standardize data access.
Without a standardization, you get a lot of snowflakes,
and it becomes very hard to maintain an enterprise
environment.
We always, like I mentioned, before,
want to change data capture.
And of course, time to market is always a pressure, right?
Walmart is moving very quickly to transform the way people
shop.
And they need a platform to do that on.
So we need to move quickly to make that happen.
We use what we call best of breed
to define products that fit our needs.
And a big part of that is what we call the ilities,
whether it's observability, availability, scalability,
operability, security.
All of these things need to be addressed in order for us
to be successful, to successfully offer a platform,
and have to be baked into any product that's going to end up
on our best of breed list.
So the good news is Spanner--
obviously why I'm here--
Spanner fit into that best of breed category.
Looking at the cloud-native capabilities,
the multi-region capabilities were very important to us.
The uptime, of course.
All of the factors were things that we deeply evaluated,
partnered with Google on to make sure
that they met the ilities part of the requirement,
as well as the capabilities part of the requirement,
the features that our customers needed in order for us
to transform the way that they're operating
their portion of the business.
So my key insights on transformative digital
transformations, or digital transformations,
is really build a partnership with Google, right?
Have them understand as well as you understand what
it is you're trying to achieve.
I really look at us as kind of the glue between the technology
and the business problem being solved.
And we're the ones that have to make sure
that that match is a good fit and it's
going to solve those business problems,
as well as improve the way that we're
running the infrastructure under the covers.
Like I mentioned several times, you
want to align with the business.
That's how you're going to create value,
and that's how you transform.
If you align with the business, the changes that you make
are going to be transformative, and not just upgrades.
You need to standardize your capabilities list when you're
running a platform and make it easy for the op team
to focus on the business differentiation,
rather than focus on trying to architect a data platform.
And finally, hire and retain people
who are passionate about the vision.
We're always looking for those types of engineers.
PRANAV NAMBIAR: Thanks a lot, Bob.
Those are really some great insights,
which I'm sure will be very valuable for many companies who
are looking forward to similar digital transformation
journeys.
I'm really excited about our partnership with Walmart,
and definitely looking forward to continuing this partnership
as we go forward.
I'm also very excited about Spanner's potential
across the board, across multiple segments.
Today, we have a number of large customers use Spanner,
mainly because Spanner offers you
all the good aspects of a relational database,
while at the same time giving you the scale and availability
equivalent of a nonrelational database.
Today, we have large retailers, gaming companies,
technology companies, and banking companies use Spanner.
And we are really focused on continuing
to innovate on Spanner so that we can take this experience
to the next level.
On that note, I wanted to share with you
some of the key highlights from our launches on Cloud Spanner.
To start with, we launched support
for PostgreSQL interface on Cloud Spanner.
This is available in preview today.
And as you all know, PostgreSQL interface
is easily becoming the de facto standard
for relational databases.
With this launch, we want to democratize access
to Spanner's capability with the familiar PostgreSQL
interface for our customers.
Continuing on the theme of democratization,
I'm also happy to share with you that we added support
for granular instances on Spanner.
This is again available in preview today,
and will be in GA shortly.
If you look at a typical Spanner instance as 1,000 processing
units of compute capability, granular instances
gives you the ability to provision 1/10 of that.
In other words, 100 processing units.
This makes it more cost-effective to run
smaller workloads on Spanner.
Continuing on the theme of cost-effectiveness,
I'm also excited to share with you
that we recently launched support
for Committed Use Discounts.
With this, you can actually commit
to a specific level of usage for one year or three years,
and in return get 20% or 40% discount, respectively.
These discounts apply to all your projects
in all the regions where you are in.
That way, you're not locked into a specific set of resources.
I'm also excited to share with you
that Spanner change streams is coming soon.
With change streams, you can easily access and integrate
Spanner with other downstream systems.
With change streams, pretty much in near-real time,
you can access all the changes in Spanner
and update your downstream analytics engines.
Or, you could easily set up triggers
to set up business logic based on specific data patterns.
You could even use change streams
to archive your changes in your Spanner
database in near-real time.
All in all, with change streams, we
want to make the data in Spanner more accessible
and make it easily integratable with the rest of your broader
data ecosystem.
With that said, I want to call out
that I've only highlighted a few of Spanner's key launches.
We are continuously focusing on a very rapid innovation
momentum.
To give you a sense of it, just in 2021 alone,
we had 58 launches on Spanner.
We're going to continue on this momentum,
and looking forward to building more such launches
in the coming years.
In the end, if what we've shared today resonates with you,
I definitely suggest that you check out our online material.
If you're new to Spanner, you should definitely
check out our Spanner Database Unlimited video series
on YouTube.
And of course, there are a bunch of sessions in Data Cloud
Summit on Spanner.
We also have a session focused on database ecosystem
and strategy.
Do check it out.
Finally, I would like to thank you
all for joining the session.
Thank you, Bob, for sharing all your valuable insights
on digital transformation.
I wish you all the very best in your transformation journey
going forward.
Thank you.
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