Hi I'm Nancy Berliner with HPE Technical Marketing Engineering.
This video will explore HPE's new intelligent QOS
feature for HPE Alletra 9000 and Primera storage rays.
I'll take a look at how to set it up and monitor its effects.
Both Alletra 9000 in Primera already have a manual QOS feature called
priority optimization that lets you set latency, i apps and throughput goals.
It's a very sophisticated feature that has helped
many of our service providers achieve their SLAs.
However, many other customers don't want or need such sophistication.
They simply want to make sure that low
priority workloads don't become noisy neighbors and impact
more important workloads.
Intelligent QOS does just that.
And because it was built on the shoulders of AI that was already in the OS,
Intelligent QOS is super easy to set up and use, so let's go take a look.
To use intelligent QOS,
you need to first enable it at a system level, it's not on by default
From the dashboard in DSCC, you can simply edit
your system settings and toggle on intelligent QOS for
your storage. As long as it's an all flash array
and there aren't already any manual QOS settings,
you're good to go.
Then all you need to do is to set the relative priorities for your workloads
when you create them.
To create a group of volumes,
click on the plus sign in the volumes area and enter all the required info:
workload type, size and host access.
Intent based provisioning recommends the best fit storage array
and you can choose that system or select a different one.
Now on the screen where you create your volume set,
you can select the priority level.
Lowest, low and medium are for non critical
workloads whose performance is subject to capping
while high and highest are for critical
workloads whose performance will never be capped.
Intelligent QOS runs continuously on the system and if it determines
that host performance is being impacted by a low priority bully volume,
it will automatically cap that volume's IO.
Once you've created your workload,
you can navigate to the volume set and verify the QOS settings.
You can also change those settings at any time.
For example,
if you created a test workload with a
low priority setting when it deploys into production,
you could edit its volume set and move the priority to high.
Or maybe you're just running some tests over a weekend
and you don't want your workloads performance to be capped for the duration
of the test. For that type of situation,
we have a toggle switch that allows you to leave the
priority as is but exclude the set from QOS capping.
I've created this workload in DSCC but I should mention that you can also
set the priority for workloads created in either the onboard UI or the CLI.
However, it's only in DSCC that you can see when QOS
capping was invoked and monitor its effects.
To demonstrate that,
I'll head over to a different system that's multi tenant, running sequel,
server production and development instances.
On the main dashboard
it's immediately apparent in the issues area that
intelligent QOS rules have been applied.
You can click on any of the volumes in the list to
get more info and a short explanation of how QOS works.
And from here, you can go directly to the performance graphs
for this volume or for the system as a whole,
which is where we'll go first.
If the system's AI finds that a high priority workloads performance is
suffering, it will look to see if there are bully volumes that are responsible.
The analysis is performed every 30 minutes
and a vertical orange line appears on the graph
each time volumes are capped. Here,
hovering over one of those lines and clicking on the resulting box reveals that
it's the low priority sequel development volumes that
were capped to protect the production workload.
Although you specify priority for an entire volume set,
it's only individual volumes that are identified
as bullies and capped, not the entire set.
On the performance graph for any volume affected,
a purple dotted line indicates the threshold below which throughput
is capped. Volumes are periodically reevaluated for releasing or recapping
This volume was actually capped at a slightly
lower throughput level in the second go around.
Before we go,
let's take a look at what's really important.
The high priority sequel production workload that's being protected.
Prior to QOS capping,
this volume had spikes of over two milliseconds
read latency and over one millisecond write latency.
After QOS was invoked,
the spikes were barely noticeable, sub millisecond
levels for both reads and writes.
That's Intelligent QOS in action.
Super easy to set up but still very effective in
ensuring good performance for the system's most important workloads.
Thanks for watching.
For more information on the HPE Cloud Experience,
visit hpe.com/storage.