Compute engine lets you run Windows virtual machines on Google's Global infrastructure. Let's learn more about starting and running Windows VMs in Compute Engine. We'll also discuss managing Windows deployments. In this module, we'll see how to get open running with Microsoft Windows server on sequel server on Google Cloud, using compute engine. Let's get started by looking at compute engine fundamentals. Compute engine is the infrastructure as a service product on Google Cloud. In this section, we'll look at the main features of the product and identify advantages of compute engine as a key foundation for your Windows workloads. When you get started with compute engine, you'll notice how easy it is to provision a virtual machine with the perfect configuration to suit your needs. You'll be able to select up to 64 virtual CPUs per machine with between .9 and 6.5 GB of memory per CPU. You have the choice of standard and SSD persistent disks and local SSDs. You'll be able to get open running quickly with available Windows Server images and Linux images. You might be surprised to see Linux images in a class about running Windows workloads and Google Cloud but later on, you'll see how you can take your existing C sharp and dot net skills and apply them to code applications that run on Linux. Here is how you create a compute engine virtual machine with the Cloud Console, web browser user interface. You should enter a suitable name for the VM. And set the appropriate zone, which will determine the Google data center where the machine will be created. You can also see the machine type. This shows to virtual CPUs and 7.5 GB of memory. And a 50 gigabyte boot disk with the Windows Server 2016 image. There are lots of other configuration options, but this shows all the basic choices that you'll need to make. Once your machines are configured, you'll connect them to each other using Google's virtual private cloud network resource. You'll automatically benefit from Google's extremely high performance network. Meaning that you'll get two gigabits per second of bandwidth per core between machines running in the same zone, with an upper limit of 16 gigabits per second of bandwidth. In addition, when you provision resources in different Google regions, traffic between them will flow exclusively over Google's own fiber network. Resulting in lower latency and higher throughput than if the traffic was routed through the public internet. To protect virtual machines there is a powerful flexible yet simple to configure firewall. You'll be able to make your Google resources available as a seamless extension of your on premises environment using Google's virtual private network. Finally, we'll see later that Google's infrastructure will enable you to run your application, high availability and scalability taken care of with a http and https load bouncer or a TCP and UDP load bouncer. At the time this video is recorded, Google's Windows Server images included Windows Server 2012 R2, 2016 and 2019. All with both Desktop and Core versions available as well as 20h2 Core version. The price for the virtual machines provisioned on Google compute engine includes the Windows Server license. This costs four cents per core per hour. And it's pro rated permanent with a minimum of ten minutes. Just like compute engine zone hardware building. Next, let's look at Microsoft Sequel Server support. Google supplies pre configured compute engine images for express, web, standard, and enterprise editions. With 2012, 2014, and 2019 versions available for all except express. Each Sequel server edition can be deployed in a variety of versions of Windows Server. Take a look at the docks for more information on this. Once again, the default price includes both the Microsoft Windows Server and Sequel Server license cost. With the same permanent building. However, in this case, you'll be able to bring your own license. If you need a pre configured Windows infrastructure that's ready to go, then you want to look at Google Client Marketplace. This example shows the ASP.NET framework solution that comes preinstalled with internet information services and ASP.NET. There is also a highly available Sequel Server solution which will install multiple servers and configure the network to enable Sequel Server always on availability groups. We'll take a look at this later on in this module. Once your virtual machines are up and running, you want to connect to them to perform general systems operation tasks such as installing and configuring Windows features and your own applications. You'll be able to connect using remote desktop protocol and you can even do this without leaving your browser. Or by installing the current RDP for Google Cloud extension. Of course, you can also use Microsoft RDP clients instead. It's common to configure your Google compute engine Windows virtual machines using startup scripts. Startup scripts can either run once on first boot, in system preparation or on every boot and they can be written as batch command or powershell scripts. This example shows a powershell script that could be used to automate connecting the Windows compute engine instance to an active directory Domain. Compute engine offers very high quality infrastructure. It also offers extremely cost effective infrastructure. Here are four ways to save money on virtual machines. First we've mentioned already, the compute engine VMs are build per minute rather than per hour. Second, there are a wide range of pre configured virtual machines with up to 64 cores and 204 GB of RAM. It's possible to select the perfect number of cores divisible by two and the perfect amount of memory between .9 gigabytes and .65 gigabytes of RAM per core. For example, you can select a virtual machine with 18 cores and 36GB of RAM, if that's what will fit your workload best. 3rd, if your standard VMs for a sustained period, you'll benefit from lower permanent costs. For example, if you run a machine for a complete month then the cost per minute of that virtual machine will be 30% cheaper than the standard permanent charge. Finally, if you have workloads that can tolerate interruptions such as rendering frames of a video, you can run preempt herbal instances at 80% lower permanent costs than standard. These machines have a maximum lifetime of 24 hours, but maybe preempted by Google if the resources that they consume are needed to run out work.