 So, thank you for joining me this afternoon. My name is Sumit. I work as a TME for NetApp, and I'm here to talk about how do you make your OpenStack cloud or hybrid cloud better, faster, and smarter. Now, just to give you guys a little background, NetApp's global engineering cloud spans across 9R and D-Labs, and we have a VM capacity of about 75,000, and we have over 5,000 users. Most of these users comprise of in-house developers who use this cloud to provision their test beds or development environments. Now, all of this is mostly powered by OpenStack, and the reason we did that was, again, I mean, if you go back to the points of the flexibility and cost efficiency that OpenStack brings to the table. Now, if you look at the scale, and if you think about it with so many users, you're obviously going to have some key set of challenges, and we can perhaps organize these challenges into three primary areas, or perhaps we can ask three questions. So, first and foremost, how do we gain key business and performance insight? And for example, find bottlenecks, and make sure that we are accelerating our workloads and improving performance. Also, with such a scale and so many users, it becomes important that you're planning for the future, and you are making purchasing decisions based on critical information and actual business requirements. Also, how do we know, or rather, is there a way to ensure that we are applying intelligent operations within our cloud? So, again, going back to the point of, are we able to simplify and automate things? So, one trend that we usually notice is that, let's say, a user provisions a virtual machine for three months, approximately, but they only end up using it for a couple of hours. Now, wouldn't it be nice to be able to automatically detect these trends and then perhaps reclaim these resources as and when the need arises? Also, we didn't just want to stop at collecting and analyzing all of this data. We wanted to make sure that we were plugging all of this useful information into third-party competence for things like billing, help desk, you know, different parts of a data center workflow. So having that ability to integrate with third-party competence was really important. And that is, you know, those are the problems, some of the problems that NetApp's on-command insight can help solve, which is an open platform for managing your hybrid cloud environment. And of course, that includes OpenStack. And it's able to do all of this stuff because it's using machine learning and statistical analysis in the background to correlate and analyze the different logical and physical pieces of your infrastructure. It's also able to identify anomalies so that you can be more proactive. It also tracks capacity. So again, going back to the point that we need to be ready for the future. So having those capacity metrics allows you to plan for the future in a better manner. And last but not the least, being able to integrate, being able to use all of this critical, this useful amount of information in an automated fashion across the different pieces or across the different components of your data center workflow. So again, without further ado, I'm going to do a quick demo. I'm going to walk you through some of the dashboards and widgets that on-command insight brings to your disposal. And I'll also show you some of the things that on-command insight can help you accomplish. All right, so here I'm logged into my on-command insight dashboard. So assets dashboard is one of many which is available. At the top, you can see the capacity by Wender, by Tier, and other metrics. And the bottom, I can see the top 10 utilized pools. And then on the right, in the bottom, I can see a heat map or a word cloud of VMs with the most amount of IOPS requirements. Like I said, this is one of the many dashboards of my disposal. So let's bring up the OpenStack Operations dashboard. Now we can see all of the instances that are currently running and some useful information displays such as memory utilization, latency, IOPS, throughput, et cetera. Now remember that all of that you see on the screen, the dashboards, the widgets, they're completely customizable. So you can pick a piece of information if it's of more value to you. Here for example, I can look at VMs that are provisioned more than 500 gigabytes of storage but are currently not running. So again, leading back to the point of reclaiming some of these resources if the need arises. On Command Insight also allows us to enforce policy. So for example, if I wanted to create a policy that an alert should be generated every time a VM went over a specific threshold for CPU or memory utilization or something else perhaps, I can very easily do that. And I can combine these set of rules in a number of ways. So that again gives me a lot of flexibility to work with. So next we'll look at one of the very really cool things about On Command Insight. So it allows you to diagnose issues and correlate it to other entities or other resources in your cloud. So here for example, we can see a latency spike for this current VM. And if you look on the right, it's On Command Insight is automatically correlating it to another entity. In this case, it's a hypervisor. So let's click on that and you'll notice that it has the latency of this VM has a 69% correlation to the CPU utilization of the underlying hypervisor. So let's plot that and just for fun, let's take a look at what that looks like. So you'll notice that about the same time as my latency went up, the CPU utilization hit 100% mark as well. So let's take a look at the hypervisor. So I now have my hypervisor dashboard open and I'm seeing all the different metrics associated with it. You'll notice that the correlation window on the right has been automatically updated. So now I can see, for example, the first one on the list is the VM that we looked at previously. So remember, the latency was 69% correlated to the CPU utilization of this hypervisor. Now the CPU utilization of this hypervisor is in turn 46% correlated to the IOPS requirement of another virtual machine. So if we were to dig down further, we can perhaps deduce that there is, in fact, an indirect correlation between the latency of the first VM and the IOPS requirement of the second VM. I can also bring out metrics from all the other virtual machines or instances that are running on this hypervisor. So for example, if I wanted to look at the IP throughput for all my virtual machines or perhaps only a few of them, I can do that, create an area graph, for example, zoom in on time and look for specific events. Which might be of interest. In addition to all of this, I can also look at things like the OS mount resources. I'm looking at my NFS shares, for example, here, and any other violations, policy violations that may have occurred. Now remember, going back to the point that all of this is completely customizable, so your dashboard may not look the same as mine. So again, you know, we talked about being able to integrate with third party components and that is why On Command Insight provides you with a really easy and flexible REST API to work with. So let's take an example and let's look at what this documentation looks like. So again, for example, right from the dashboard, I can enter different parameters, try out my code in real time, and take a look at the response body. And that again gives your developers a lot of flexibility to work with. Now the last thing that I want to talk about is the reporting warehouse, which allows you to create reports. And there are lots of inbuilt reports such as window-specific reports, regular reports, et cetera. But in addition to all of this, On Command Insight also comes with a really good business intelligence solution. So that allows you to author reports based on different metrics, for example, storage efficiency, port capacity, switch performance, et cetera. Just to show you guys an example of how easy and fast that was. Now let's say you find something missing, right? And so we have this marketplace kind of an experience that allows you to download pre-built reports and run them against your cloud or your environment and change them as the need arises. So if we take a look at an example, here we have the application allocation versus cost consumption. And again, not only can you identify key current trends, but also forecast future trends, so that's really useful. In addition to all of this, we also have widgets and other resources for you to consume. Now just to reiterate, if you're running a large open stack cloud or a large hybrid cloud, it can be challenging to monitor large service levels, optimize capacity. And we also ran into issues where the troubleshooting time was really, really big. And we couldn't work with that. And that's where NetApps On Command Insight comes into the picture. Not only did it allow us to analyze current performance and capacity, but also allowed us to reduce service delivery and diagnosis times by almost 98%. So time to market for new capabilities across data centers was reduced by 97%. Moreover, it allowed us to reduce application downtime, make sure that we were optimizing capacity and doing things in a more efficient manner, and enforce policies, which in turn, if you think about it, allows you to ensure high availability among various other things. And we were able to do this again because we were able to identify underutilized or unused resources and reclaim them as necessary, which brought down our storage capped capex by 20% and increased our return on investment. In addition to all of this, On Command Insight also allowed us to look at current trends and future trends and provided us with reports on costs for different metrics, which again, it was very useful in our use case. If you want to try the hands-on demo, you can do so online. If you scan the QR code, it will take you right to the page. They're also available in Boot D3, so you can come talk to us and we'll discuss how we can help make your OpenStack Cloud faster, better, and smarter. That's all I had for you guys. Thank you very much for listening patiently.