>> Hey, good news.
We're back with another episode from
the Well-Architected series as part of the Azure Enablement show,
and today we're bringing back Saket to talk more
about the Azure Advisor stuff that we were
talking about in the previous video which gives us
a expert advice at our fingertips.
Saket is bringing along another expert
who could be able to give us insight into
the internals of Azure Score and
other cool ways to pull this data into our own systems.
Look forward to see you soon.
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>> Welcome to the Azure Enablement show.
We will be discussing the challenges you,
and our other tech savvy customers have encountered.
Together, we'll be talking with experts to
find out how they think about these problems,
recommended tools and best practices and tips
they've learned from years of experience that you can use.
Today, we're going to be continuing
our discussion about Azure Advisor,
a tool that provides essential advice at
your fingertips for improving your Azure workloads.
So last place we left off,
I was a customer learning about Azure Advisor
and Saket told me
something really interesting that
there was this tool that I can use.
I think what I want to do is go back to being
a customer and I'd like to hear more
about this feature that we have so I understand how I can use it.
Hey, Saket, thanks for coming back again today.
I was hoping we could pick up where we left off.
You were telling me that there's this feature that's
in Advisor that will give me some sense of
how well relative to other people.
Let me try that again. Can we just start that one more time?
Sorry. I'll start with the snap and I'll just keep on going.
Okay, cool. Hey, Saket,
thank you for coming back.
Last time we left off,
you were telling me that this feature in
Advisor that allows me to have
a sense of how well I'm doing, relatively speaking.
In terms of my recommendations and stuff like that,
can you tell me a little bit more about that?
>> Yeah. Sure thing, David. I think
we are talking about Advisor Score.
>> Yeah.
>> [inaudible] score. I brought
with me the perfect person to talk about it.
Let me introduce you to Matt.
He's the data science expert for Advisor Score.
>> Cool. Hey, Matt.
>> Hey, guys. Hey, Saket.
Thanks for the generous introduction, David.
Great to be here with you today.
How's business?
I hear you're coming from Contoso Hotel, is that right?
>> Yeah. Things are going I think pretty well,
but I'm still trying to get a sense of
like I have a ton of recommendations.
They're affecting some number of resources.
I'm getting some cost optimization numbers,
but I don't know whether this is good,
whether this is bad, whether I have a lot of them,
too many of them, not enough.
So can you give me some sense of this Advisor Score thingy?
>> Yeah. Adviser score
is I think just exactly what you're looking for.
As customers start to grow and
they invest more and they put more on Azure,
they find that their recommendations in Advisor
will just start to proliferate like crazy.
They'll be more of them than there are bunnies like cute,
little bunnies in the forest outside my window here in Redmond.
It's out of control and you don't know how to manage it.
You don't know if it's good, you don't know if it's bad,
you don't know if you need to eliminate them,
or welcome them as your friends.
So the Advisor Score is going to solve
a lot of those problems for you.
In addition to those tools that I believe Saket shared with you,
the digests and the alerts.
The Advisor Score, I'd like to tell you
just a couple of things and introduce it to you.
>> Okay.
>> We've developed it to be
the industry standard for the Cloud computing posture
of your organization or
really any organization on the planet of any size.
It's a single number that will tell you how well you're doing on
adopting Microsoft's best practices to run workloads in the Cloud.
It's useful again for a very large organization who's
running thousands of workloads and
shared services across an enterprise.
It's also useful for these small businesses and anyone in between,
so I think it's going to be useful for you as well.
It aligns really well.
While it has a single number that you can report to
your leadership and it tells you how well you're
doing across all these workloads,
it also breaks down into
the five pillars of the Well-Architected Framework.
You'll get a number for your entire Azure ecosystem
to tell you how well you're doing adopting best practices.
It would also be able to break it down by
each of the five pillars of the Well-Architected Framework.
So you'll see a score for cost optimization,
operational excellence,
performance efficiency, reliability, and security.
>> Cool.
>> I want to take you over to the Azure portal
and actually just show you some of these features,
and the first feature I want to show you is
this unique ability for the Advisor Score
to actually traverse hierarchies.
So if you're a director at Contoso and you're responsible for
a large ecosystem of dozens of
applications and eventually hopefully
that will grow into even more,
then you've got to be responsible for
the risks that you need to
mitigate across all of those recommendations.
There could be thousands of them,
and then if you want to go really deep into
just one specific architecture.
When Saket and I were chatting, he said something about how you
are interested in SmartHotel360 app.
It's like some new concierge service.
If that's scoped to a single subscription
and you can just focus in on that one subscription,
you get a score for just that one workload.
>> Cool. Anyway, I could see
this and actually it sounds really cool.
>> Yeah, let's bring it up. Again, once you're into Advisor,
I think Saket talked to you about how to navigate to Advisor.
You can type it into the search bar.
Anywhere you are in Azure portal,
go to that search bar at the top of the screen,
type in Advisor, and then you can see on
the left navigation pane there's an Advisor Score.
Just click that and you see the screen you've got here.
Then here, you can type in your subscriptions.
At the bottom of the search results for just Contoso,
I can see that you have three subscriptions
for the SmartHotel360 app,
you've got one production subscription
and then two non-production subscriptions.
So if you wanted to scope this just
to your production subscriptions,
you could do that and you could get your score.
Once you've decided what kind of scope you want,
and for now I'm just going to leave it to all of
your Contoso subscriptions and we can
take a look at the entire portfolio,
then you can take a look and I'll
orient you to the three core features.
The first one is your score,
so this is an aggregate score.
It's a single number,
and it looks across all of the five pillars of
the Well-Architected Framework for all of your resources,
and it gives you one number to know how
well you're adopting Microsoft's best practices.
So if your CTO knocks on the door
and he wants to make sure or she wants to make
sure that you're doing everything that you possibly can in order
to ensure that you're building Well-Architected applications,
then that's going to be available for
you there, that single number.
>> Okay, cool. So that's my score,
but how do I know whether that's good or not?
>> Yeah, that's a great question.
Honestly, it's going to be up to
every single individual organization to
figure out what kind of risks they want to take,
which is why it's important that you can break this score
down and look at each individual category.
Here at Microsoft, for example,
where we build a lot of our internal applications on Azure,
we like to think about the split
between production and non-production subscription.
You might be willing to take a little bit more risk on
non-production subscriptions or non-production resources
and the reliability category.
So you might let that one fall a little bit,
but you also don't want to be paying too
much for non-production resources.
So you want to keep your costs score very high,
and it's good to think about these different category scores
as something that you could balance.
You can split it by workload,
split it by production and non-production,
and think about what's going to be best for
you and your organization.
I would also say in addition to that,
another way to know if you have a good score
is just to look at the history.
What we've got is a history that will tell
you how well you're doing and you can set
benchmarks against yourself and make sure that you're
constantly improving or at least staying the same.
That way, as you continue to grow
your investment on Azure and build more applications,
you'll know that you're taking the right necessary steps to adopt
the best practices that we're recommending and ensure that
you're getting your workloads in
the position they wanted them to be in.
If you decide to go in and just remediate
all the recommendations in a very short period of time,
you can change the filters here on this.
You can look at this at a daily grain, a weekly grain,
or a monthly grain to know if your scores are moving
quickly or just look at it over the course of an entire quarter.
Those are the baseline introductions to
the score just to give you a sense of what you're doing,
and that's the question that came to me with
originally as, how well am I doing?
Finally, you can see that.
>> Cool. The next obvious question here is,
what do I got to do to improve my score?
>> Yeah, that's a fairly obvious question,
and we try to make it even an obvious
answer by putting here at the bottom of the screen.
If you go into the portal,
you can see that there is the potential score impact,
the reliability score impact.
So as you traverse across
the different categories from left to right,
you can see the costs, security and reliability.
You'll see the score impact.
Here's the reliability score impact,
and we've actually ranked each one of these recommendations by
the amount that your score will improve
if you go remediate the recommendations.
It makes it fairly simple and
intuitive for you to improve your score.
>> Okay. Can I ask another question
about something that I'm seeing here on the screen?
>> Yeah, please.
>> I have this vague memory that once upon a time,
instead of this score,
there were a bunch of accounts where we just counting
up the number of recommendations in each one of the categories.
Why is the score any better than the count?
What's different between just a straight up count?
>> Yeah. That's a good question. A couple of things.
One, as you continue to grow your investment,
let's say today you only have your one SmartHotel360 application,
you might only have five, six, seven, eight recommendations.
But if you onboard a second application,
you continue to migrate from your datacenter or
just building that new things in Azure.
Those counts are going to go up,
and it's going to seem suspect.
What we do is we put in this number.
It allows you to compare one application to another application,
one subscription to another subscription,
one small dev team that is
scope all their workloads to a single subscription.
Now, you can compare that to your overall portfolio,
and you're going to get a one-to-one number.
You can just compare the percentage from zero to 100,
and you know which ones are doing better and
which ones doing better across the five categories.
I would also say that we've added a couple of things to
provide this score that's working behind the scenes in the model.
For example, you have
two virtual machines that both have
a recommendation that need to be addressed.
One of those virtual machines cost you, let's say,
$1,000 a day, and the other one only cost you $100 a day.
You're going to want to spend a little bit more time looking at
that $1,000 a day virtual machine.
Because first of all,
in the cost categories going to save you
more money if you right size it.
But it's also a clickable in
the other categories like reliability because the price,
although you may not be interested in
saving cost when you think about reliability,
the price of the resource
serves as a proxy for its relative importance to
the overall architecture of
the application that you're running, so we look at that.
We also have a very long history of
millions of recommendations that
have come into the Advisor portal,
and then been remediated by the customers.
We know which recommendations are typically pretty easy and
almost a trivial task to go out a fail over.
Then those that need a little bit more planning,
and need a little bit more attention and need
a developer team to see if this is the right action for us.
So we have a long history of that,
and we built this onto the model such that if you're
taking action on those easy to remediate recommendations,
your score is going to be weighted as
such and random will reflect those points,
versus the ones that might take a little bit more time,
then we'll give you that time.
But as the time passes,
your score will have incremental weight
being added to it or I guess I should say,
being detriment from it as you
take more time to adopt those recommendations.
So that's all happening behind the scenes.
It'll tell you on this reliability score impact,
which wants to implement first.
>> So the theory is the ones that are easier.
The expectation is that you'll hit them first,
and that will raise your score faster?
>> That's right.
>> Okay. That makes no sense.
One more data question because I
know that I have gone to the portal and looked at my scores,
and I know I've made some remediation,
and it wasn't necessarily immediately reflected in my score.
It leads me to the question in general,
how often does the score refresh?
Come to think of it. How often does
all the advisor stuff in general refresh?
>> Yeah. That's a big two-part question.
The first thing I can tell you about
the score is that it refreshes daily.
So every day you come back and you go to
take actions on your recommendations,
you'll see that score reflect those changes.
But advisor has literally
a hundreds of recommendations that are
coming from lots of different data sources,
so we have different timelines for all of them.
I think Saket would actually
probably the best to tell you a little bit about
the other timelines and guarantees that you'll have an advisor.
>> Thank you, Matt. So let's break down your question, David.
The first part you talked about is
the refresh frequency of all the recommendations.
We have a high count of recommendations.
Our customer promise there is like we will refresh
the recommendation at least once in 24 hours.
So every day, we have
at least all the recommendation refresh to once for our customers.
Now, that being said,
there are lot of
recommendations which have a higher frequency of refresh.
We have recommendations which refresh
every one hour or 30 minutes also.
So that's the refresh frequency for recommendations.
Now, the second part is advisor score.
Our commitment to customers there is,
we will refresh their advisor score once in 24 hours.
We have a daily refresh,
you have taken action today,
you can expect that recommendation not to show tomorrow,
and their advisor score being updated by tomorrow.
>> That was very cool.
I know we're basically out of time,
but I have one more,
by the way question, I'm hoping to ask you Saket.
What I'm curious about because I was talking with
some people back at my shop is,
they were saying that they don't want
to spend any time in the portal,
they're not portal people.
Is there a way to get all this cool stuff
without having to use the portal?
>> Great question, David. I think we miss
talking about advisor endpoints,
so let's talk about it.
Advisor has Advisor API.
This is public facing API,
and you can use it to get all the recommendations.
So any at-scale fetch for your recommendation data,
you can use Advisor API.
You can also build automation and
other connectors over the response of this API.
Advisor data is also present in Azure Resource Graph,
so you can form complex queries in Azure Resource Graph,
and you can get the recommendation data there.
Let me show you a PowerShell window and
quickly walk you through a couple of
commands to fetch the data super fast.
This is the PowerShell.
How I got to here is I just clicked on
the "Cloud Shell" button from Azure portal,
and this is your PowerShell window.
This is the first command I'm going to type.
You can easily see what I'm doing is,
I'm selecting a subscription,
which is your subscription, David,
Contoso Hotel, and I'm going to execute this command.
Now, the context is with the subscription.
Then next thing I'm going to do is just fetch
the advisor recommendation for that subscription.
You can easily see, you'll have
all the recommendation coming for that subscription.
That's a super easy two-line command.
Similarly, our API also are super easy,
it's just one HTTPS code with the right parameters,
and you will have all the recommendations with you.
>> So that's really cool. That means that I can stack that stuff
into my existing systems and display them anywhere I want,
which is really quite cool.
Well, I've said we're
almost out of time, and we're definitely out of time.
I want to thank both you Saket and you
Matt for taking the time to talk to me about this.
I think it's probably time for me to move back in the Host Mode.
Well, that was pretty cool. We got a chance to
see more about Azure Advisor.
We get to dive into Azure score,
and we got some sense of how
to put in that information into our own stuff.
With that, I want to thank you for watching this.
I want to thank Saket and Matt for taking the time to talk to me,
and I hope you'll join us for other videos in this series.
Take care and I'll speak a little bit later on.
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