hey everybody in today's episode of the azure enablement show i'm joined by jeff who is a
cloud financial architect he's going to be walking me through how to think
about estimating your azure virtual machine costs using a new azure virtual machine cost estimator
make sure you join us for some great demos as well
hey everybody my name is sarahleen and welcome to the azure enablement show in the show we're
having technical conversations with microsoft experts about some of the common questions or
concerns you may have with your cloud adoption journey now in previous episodes we covered off
what the cloud adoption framework is and how it can accelerate your cloud adoption journey
we've also been talking about cloud economics and how you can successfully build your cloud business
case in today's episode i'm joined by jeff who is a cloud financial architect and he's going to be
talking to me about the new azure virtual machine cost estimator now welcome back to the show jeff
thanks it's always a pleasure and it's always uh and i always enjoy talking about cloud economics
and and how financials map to like architectural changes um so i love playing that role of a data
center architect that kind of likes to do his own taxes so it's always a pleasure uh
doing these sessions with you awesome now if we think about the cloud adoption framework
inside the strategy phase we talk about business justification and building your business case
and when you're building that business case estimating and figuring out the cost of
running your environment inside the cloud is a big factor for a lot of people and with that in mind
we have this new azure virtual machine cost estimator and that can help you with that could
you explain a bit more about that please jeff yeah absolutely so in essence it's a power bi template
with an excel file that feeds data into the power bi template what we discovered
is when you're looking at even larger scale data centers more than 100 compute units for example
um it's challenging for customers to go to our online cost calculator our azure calculator
that's web-based and put all of those technical criteria in there and find the right matches
so we created a template um the azure co virtual machine cost estimator so you could feed in a
much larger list along with some additional specifications like the number of chords that
are assigned to that compute unit um the memory footprint and the utilization of those and even
um the monetary or fiscal value or currency value that you want to actually have the price
list generate um along with like the different azure targets you want to place your workloads in
um so it helps you automate that process awesome this sounds very good and i do love a power bi
template or report and jeff could you show me and walk me through this please oh absolutely
let's go ahead and share and take a look at it um so this is the main part of the dashboard
um now the data i'm feeding into it right now i just randomly created a hundred thousand compute
units now in most of our customer cases we're not going to see footprints that large but at
least it shows the flexibility and scale that you can use this particular tool in and what
it's doing is it's placing that entire compute footprint into our different offer constructs
whether it's go pay you go pricing or one or three year reserved instances those longer term commits
or with or without the azure hybrid benefit so you could see the different price points and
cash flow differences as you place your workloads in different offers that are available from azure
awesome now you mentioned um different pricing plans there on different programs like hybrid
benefit and pay-as-you-go could you just explain a wee bit about the differences between all of them
and where they fit inside your cost estimations oh absolutely so pay-as-you-go pricing is in essence
on-demand usage based pricing inside of azure you pay for what you're actually using that percentage
up time of of your compute particular compute unit and as you can see in this model it is a
higher price point versus like reserved instances where you have one or three year terms or commits
of compute utilization and you'll notice that the cash flow requirements to support those workloads
is much lower as you make longer term commits with reserved instances and then in addition to that we
have the azure hybrid benefit which is uh attached to an agreement with microsoft where you have
enabled license portability for windows as well as your sql licensing that that licensing asset or
investment that you already have you could further leverage to lower your hourly price point for a
compute awesome now what happens if we don't want to use your sample data jeff how do we actually
plug in our real world data into this template oh absolutely so let's walk through that and um
within the template itself the very first tab is a little bit of a high two guide so as i'm walking
through this if you're not taking notes certainly this page will be super helpful for you but i'll
walk through these steps and and so you know how to customize it in the way you want so starting
with the data input which is an excel file and it's and we'll provide download links for both
for this excel file for the pbx at the end of this presentation but starting with the excel file we
have this first tab of on-premise compute units um this is where i randomly generated a hundred
thousand or sorry uh yes a hundred thousand compute units as well as i randomly assign them to
an environment whether it's dev or pre pre-production or production level systems
um and then i also set whether or not it's running windows because we want to be able
to quantify the cash flow delta between compute units that are running windows and those that
are not and then also show you the hybrid benefit cash flow benefit as as we're doing the analysis
there's also columns for the number of vcpus or cores that are assigned to that compute unit
the memory footprint and also some fields of resource utilization so if you're not using 100 of
the number of cores or memory footprint you could put in percentage utilizations of those resources
and then this last column in this first tab defines where you're placing the workload um
in this particular case i randomly assigned uh compute units to any data center in azure so we
pretty much have global coverage for this 100 000 compute unit footprint um now second to that you
could also set the currency on the second tab we have it set to us dollars but for the currencies
that we support in azure the list is here and you could just go ahead and pick those um and then
you could also filter out what compute series you prefer in azure like i've filtered out some of the
a series and the b series and and some of the v5 series that are in pre-production so their
pre-production pricing at this point in time but i wanted concrete modeling pricing so i kind of
filtered those out and you just set true or false for those and then this last tab of the data that
you're feeding in from the excel is the azure regions and i set every global region to true
but you can go through and pick those particular regions depending on your requirements
so after you do that you can go back to that power bi dashboard that pbix file and there's a little
bit of customization that you have to do primarily pointing the file to that excel that you just
customized now the way you do that is you go into one of the data feeds and just kind of edit query
and if you're familiar with excel and power bi we're going into the power query uh editor in the
back end of it and we're just going to change the variable that sets the path onto the particular
excel that we just downloaded like you see up here it's going to my path the c drive and a folder
where that excel file is located and that's the other other last component you want to customize
and then after all that's set up and you've created your own customized list of compute
in excel pointed the pbx file to that particular excel file um everything's set up and ready to
go and you should see that the representation of price points for the different offer constructs
that looks awesome jeff thank you so much for doing that but i'm thinking about the
non-virtual machine and resources that you may want to have in the cloud does this um report
help us with that or what's the process for for estimating the cost of non-virtual machines yeah
the current version is really targeting virtual machines but an additional reason that we did it
in this particular way with this approach is it's an excellent example to extend to other meters and
pass services inside of azure for example these particular data feeds where we're pulling in
license pricing and compute pricing are coming from our publicly accessible retail pricing api
so they're great examples great starts that you could use as a reference to pull in sql
managed instance meters at the past levels or other meters if you want to build a model that's
inclusive of a more complex overall architecture so it's a great example to really start with
excellent so where can people go if they want to download this and start to use it and use it
to estimate their cost chef excellent certainly starting at the cloud economics site on azure.com
as well as we're going to provide a link here in in the window that you can go to which is a
direct link to download the tool sets so you could download them locally and again don't
forget to set the path when within power bi to go to the excel file and customize your data and you
should be all set excellent thank you so much for joining me today jeff it's been a pleasure
having you on the show also thank you to all of our viewers for tuning in please do check out
future episodes of the azure enablement show and definitely check out our back catalogue as well