good morning good evening good afternoon depending on where you are in the world right now today we're going to spend a few minutes and talk about public cloud and how it's a lot like dinner now everybody loves a good dinner everybody's having a great time even the little girl in the bottom right hand corner of the screen is drinking a beer it's just a good time for all and i know when i was a kid we didn't have a whole lot but matriarch of the family my mom made sure that we all went out as a family every once in a while to a really good dinner the problem is every every family has an uncle phil good old drunk uncle phil would wander in pull over the sommelier and start ordering wine now he wasn't necessarily the smartest guy when it came to wine so he didn't necessarily like it every single time maybe he didn't finish the bottle and sometimes it was a pretty expensive bottle of wine what that led to was when the check came a little bit of sticker shock so one of the things that my mom realized is you had to understand the people who were at dinner and you had to put some guard rails and some policies on what we could do at dinner and i'm sure we've all experienced something like this like say at a sales kickoff or something like that where you go to the bar and there are three pre-selected bottles of wine all decent wine all within a pretty good price range well that's the type of policies we want to set up for cloud now it's not wine policies it's cloud policies but the similarities exist so let me go ahead and just show you that in my instance now in this instance we're looking at the dashboard this dashboard starts with the cloud spending analytics and we could just kind of just highlight that in the last 30 days we spent about 2 grand which is interesting to know but let's start drilling into some of the details behind it starting with this cloud spend cloud spend gives us this dashboard that says in that 2800 that we just spent 45 percent of it's on compute 35 percent of its own storage 10 on database you get the picture great way to take a look and say hey it looks like we're spending a lot on databases or something else we could do remix this that kind of thing gives you that ability then forecasted as well on the optimization side however this is going to be a result of our policies let's start right here on the unused machines we're saying that unused i'm going to save nine thousand seven hundred and three dollars by spinning down unused machines now these are machines uh in the case of uh uh uncle phil these are machines that he ordered and never never actually uh drank any of that wine you know similarly to by right sizing the right sizing is the other side of the coin for the unused machines right sizing is saying that he ordered that wine but he didn't drink the whole bottle maybe next time we want to say okay only order a glass whatever the case may be right and then of course the business hours and this is another guardrail that we get set up it says hey you know what this server that you spun up it's a it's a test server and the testing team the qa team is only in between the hours of 8 am and 6 pm so you know at 10 80 pm it doesn't have to be running anymore let's shut it down here's what's really cool about all that we can start getting look at the details of that too so if i jump into my right sizing for example the details of it here are going to point out this machine for example is currently at a m5.4 large you want to drop it to a c5.2 large it's going to save about 200 a month we can do the same thing with unused machines we don't also know who owns these machines we could say this configuration item i'm going to save 73 a month by spinning it down and right now that's going to be affecting this organization here so we should probably go talk to them here's where i look at the business hours these are machines that may be running out of business hours what determined business hours based upon the policy right with this particular machine can save 34 dollars a month all these different things add up to the pretty significant savings now what's super interesting about this is this is sitting on top of the workflow that you've already got in your it service management pro subscription the implication here is you haven't got to invest in yet another technology spin up yet another team of people go through yet another training you can leverage the investment you've made in servicenow technology to write workflow to integrate with anything else in the platform but also it implies that when i do this change i'm integrating your existing change process so i've said that this machine can only run during certain business hours that is implemented by opening a change and because i know who's associated with this machine i've got the ability to send that change through the proper routing put it in front of the change advisory board they say yay or nay and i can even run workflow to automate shutting it down right so jumping back over to my presentation that's a quick demo of what cloud insights does now let me give you a little bit more context cloud insights in and of itself is a great tool but it sits inside a greater context of an it asset management life cycle and you've heard me talk about this before starts with the request bubble that request is something that you currently own in your it service management pro subscription that's your service portal fulfillment step is something you currently own in your it service management pro the deploy step you can even automate deployment using your integration hub the monitor step is going to be what you're currently familiar with with servicenow software asset management professional and servicenow hardware asset management professional in this case for cloud that's going to be your cloud insight step service from retire are classic features of the it service management pro so the idea here is that uncle phil comes in and starts here at the deploy stage sits right down at the table goes over pulls the mater d over and the somalia over and orders a bottle of wine or in this case uncle phil opens up his amazon console and starts spinning up machines for himself what we want to do is have uncle phil start here at the request stage and end at the retire stage going to the full life cycle what does that look like let me jump over back to my instance and i'm going to show you this has been the experience of the manage step what i want to point out is i'm logged in here as a system administrator it's a tech rat guy who wants to come in and manage his stuff no problem but i want to give uncle phil his own experience so i'm logged in as uncle phil here now on the service request port well this looks really familiar to you guys right so you already understand this i click on request something i then say i want a new qa server from amazon and i have a limited menu of what i can order from in this case i can just pick one of these objects you already know what happens next i can order it and then i i get asked specific questions what's it for how big do you need it how long do you need it and that's the guardrails we can kind of put around this thing so uncle phil knows that we're paying attention once i check out it goes through the normal fulfillment process i've just handled request it's now in the fulfill we can even put workflow together to automate the deploy the idea behind this is is we've got those guard rails for uncle phil now and this is something that you can leverage what you currently own so hopefully had a good time have a little bit of a conversation about dinner hopefully i made you hungry maybe you're even thinking about having a quick glass of wine not a problem but in this case what your next steps are reach out to your servicenow sales representative figure out a way to get this on your next contract