MARK MIRCHANDANI: Active Assist recommenders
can help proactively uncover a lot of opportunities
to improve things, including the performance of your Cloud
workloads.
Imagine this scenario.
You've got a web server and an application server,
each hosted on Compute Engine virtual machines.
An update to the application server
was rolled out two weeks ago that added
a bunch of new features.
Since then, there's been an uptick
in the number of timeout errors on the web server
when it attempts to communicate with the application server.
It seems that performance has been compromised,
and it's starting to affect the business.
How can you avoid this scenario from happening
in the first place?
One way is by keeping an eye out for opportunities
to improve performance.
Let's see how Active Assist can assist you with that.
It's not always easy to figure out
what could be causing performance issues
and how you can improve the situation.
When it comes to Compute Engine instances,
an ideal place to start is making sure
that you're using the correct machine
types for your workloads.
In the previous video, we talked about how the VM machine type
recommender can help you reduce costs by offering rightsizing
recommendations.
Remember, applying rightsizing recommendations
that resize your VM to a smaller machine type
will let you avoid wasted resources
and optimize for costs.
However, when resource constraints are detected inside
of your VM, rightsizing recommendations
to resize to a larger machine type
will optimize for performance.
The VM machine type recommender will recommend a larger machine
type when it identifies a VM that is persistently
throttled by insufficient resources,
such as CPU or memory.
Here, an n2-highcpu-32 offers a better fit
for the memory used, as well as offering
the CPUs that are actually needed to run the workload.
In our scenario from the start of this video,
this very well might have resolved those performance
issues.
These recommendations are created
by analyzing data from Cloud Monitoring over the past eight
days.
Compute Engine offers a number of standard machine
types with fixed CPU and memory amounts.
If none of those fit the requirements identified
by a recommender, a custom machine type
might be offered with appropriate amounts
of CPU and memory.
Rightsizing recommendations aren't
just limited to single instances, either.
You can also receive rightsizing recommendations for VMs
in a managed instance group.
These recommendations will come from the appropriately named
Managed Instance Group machine type recommender,
but they work very much like the single instance
recommendations.
This is especially useful for cases where you may not
be able to increase the size of the instance group
or for workloads that just don't work well with auto-scaling.
For Managed Instance Groups, metrics
are collected and analyzed from all
of the instances in the group.
That way, the recommendation won't
undersize for any of the individual instances.
As always, you know your workloads best.
When you receive those recommendations,
you can choose to review and apply
them or just dismiss them and hide them
from the Cloud Console.
You can always view them in the History
page of the Recommendation Hub.
Beyond just virtual machines, there's
a few recommenders that can help you
maintain or improve performance of other Cloud resources.
For example, if you're using Cloud SQL,
you can receive recommendations from the Cloud SQL
out-of-disk recommender.
These recommendations come from looking at the disk space
usage of a Cloud SQL instance.
By analyzing the storage utilization trends
over the last 30 days, recommendations
can be generated if an instance is likely to run out of space.
The recommendations will suggest either
manually increasing storage capacity,
enabling the ability to automatically increase storage,
or deleting data to free up disk space.
Active Assist can help you be proactive and avoid
downtime or performance issues that
could be caused by running out of disk space on your Cloud SQL
instances.
Performance issues can be tricky to deal with.
The recommenders we've looked at today
can help you stay on top of performance issues
by analyzing usage data and suggesting ways
to fix resource constraints.
You can check out the documentation
to try these out for yourself, and don't
forget about the Recommendation Hub
where you can see all sorts of helpful recommendations.
Stay tuned for the next video, where
we'll look at some more recommendations that
will focus around strengthening security in your Cloud
environment.
See you there.