JENNY BROWN: File storage is a critical need
for many enterprise applications and workloads.
But file storage is about more than just disk space.
It's about finding a solution that
is fast, consistent, scalable, and still simple to use.
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Some of the most common use cases
for file storage in enterprise applications
are media rendering, data analytics,
and managing shared content.
These complex situations require flexible and scalable
solutions.
Plenty of us have heard it before.
Storage is cheap, but with needs growing exponentially
to fit use cases like these, companies want flexibility
to scale on demand and meet specific performance
needs of their application and user demands.
And now that companies are turning
to cloud computing solutions for applications
and for their infrastructure, there's
a growing demand for cloud-based file systems.
To meet the needs of customers looking
for a fully managed cloud-based storage product,
Google offers Filestore.
Filestore gives users a simple native experience
for standing up managed Network Attached Storage, or NAS,
for their compute engine and Google Kubernetes
engine instances.
We also rely on file storage partners such as NetApp
and Dell EMC Isilon Today, we're going
to show you how to quickly configure and attach your file
system to a compute instance.
Say we have an intensive workload and many clients,
and high throughput is critical.
To begin, I'll name my instance, for example, Performance Test.
Next, I have to select a service tier.
Since I need a high-performance application
with many connected clients, I'll go with High Scale.
For help picking the tier that's right for you,
you can check out the comparison table.
The storage type for High Scale is SSD, which works for me,
and with Basic, I would also have the option of HDD.
I'll keep capacity at 60 terabytes
and can always scale up or down when needed without any service
interruption.
As I specify different capacities,
I can check the calculator for cost and performance estimates.
Now I have to choose a location.
Since my clients are located in US Central 1,
the default location is perfect.
I can set a specific zone or let the deployment decide for me.
Next, I'll select the network used by my clients
so they'll be able to access this file system.
Once I have a network, I'll allocate an IP range
or let the service do this for me.
The file system mount point IP address will
be selected from this range.
Next, I'll give my share a name, DCC.
This will be represented in the mount location later.
Even though I can grant or restrict
access to my file system through IP-based controls,
I'll leave it open for now.
And now I'm ready to create my instance.
Once it's ready, I can see all my instance details
and copy the mount point string.
Now I'll SSH into a client VM I already created
and mount my file system using the mount point I copied
earlier to slash MNT directory.
Let's run some load and take a look at the performance.
I'm starting with 256 clients performing simultaneously
with intensive IOPs.
You can see the clients are building their working set.
And here you can see the latency leveling off
at 10 milliseconds and IOPs reaching 150,000,
since my clients are saturating the instance.
I need higher performance and more capacity,
so I'm going to scale up my instance from 60
terabytes to 320 terabytes.
After my instance scales up, you can see the graphs start
to change.
Here the latency graph drops, showing much lower latency,
and the IOPs graph is climbing to 600,000 IOPs.
As we'd expect, the total throughput
is also growing accordingly.
For anyone that's ever managed their own storage
and panicked because they needed to slap another physical drive
in a server before they ran out of space,
this is pretty exciting.
Today, we saw how Google Cloud file
storage is used to migrate traditional applications,
modernize existing applications with Kubernetes,
and scale to meet the performance demands
of big compute workloads.
For media rendering to genomics processing,
Google's file storage can meet the needs
of business critical workloads.
Thanks for joining us, and please check out
our website and documentation to learn
even more about Filestore.
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