As a cloud professional who is already familiar with AWS, you know that designing a multi-tier architecture includes the compute layer. In general, your compute layer designs include virtual machines (VM). Some of the considerations involved in configuring virtual machine include the following:

• How can you create and deploy VMs using a graphic interface?
• How can you connect to VMs securely?
• How can you enable communication between your instances?

In AWS, your organization deploys VMs, called Elastic Compute Cloud instances, programmatically through the AWS Command Line Interface (AWS CLI) and the AWS Software Development Kit (SDK). VM instances can also be deployed with the AWS Management Console.

To interact with your Elastic Compute Cloud (EC2) instances, you use a key pair to securely connect through Secure Shell (SSH) in Linux instances or to decrypt the administrator password in Windows instances. Alternatively, for instances where a key pair may pose a security risk, you use the AWS Systems Manager Session Manager to manage your EC2 instances through an interactive browser-based shell.

To enable communication between instances, a simple pattern is to place them inside of the same VPC using the proper definitions in route tables to allow traffic between subnets.

Now you will explore how to create a similar architecture in Google Cloud.

Overview

In this lab, you will create virtual machines (VMs) and connect to them. You will also create connections between the instances.

Objectives

In this lab, you will learn how to perform the following tasks:

• Create a Compute Engine virtual machine using the Google Cloud console.
• Create a Compute Engine virtual machine using the gcloud command-line interface.
• Connect between the two instances.

Task 1. Sign in to the Google Cloud console

For each lab, you get a new Google Cloud project and set of resources for a fixed time at no cost.

1. Sign in to Qwiklabs using an incognito window.

2. Note the lab's access time (for example, 1:15:00), and make sure you can finish within that time.
   There is no pause feature. You can restart if needed, but you have to start at the beginning.

3. When ready, click Start lab.

4. Note your lab credentials (Username and Password). You will use them to sign in to the Google Cloud Console.

5. Click Open Google Console.

6. Click Use another account and copy/paste credentials for this lab into the prompts.
   If you use other credentials, you'll receive errors or incur charges.

7. Accept the terms and skip the recovery resource page.

Task 2. Create a virtual machine using the Cloud console

1. In the Navigation menu (), click Compute Engine > VM instances.
2. Click CREATE INSTANCE.
3. On the Create an Instance page, for Name, type my-vm-1.
4. For Region and Zone, select the region and zone assigned by Google Cloud Skills Boost.
5. For Machine type, accept the default.
6. For Boot disk, if the Image shown is not Debian GNU/Linux 11 (Bullseye), click Change and select Debian GNU/Linux 11 (Bullseye).
7. Leave the defaults for Identity and API access unmodified.
8. For Firewall, click Allow HTTP traffic.
9. Leave all other defaults unmodified.
10. To create and launch the VM, click Create.

Note: The VM can take about two minutes to launch and be fully available for use.

Click Check my progress to verify the objective. Create a virtual machine using the Cloud console

Task 3. Create a virtual machine using the gcloud command line

1. In the Cloud console, on the top right toolbar, click the Activate Cloud Shell button ().

2. Click Continue.

3. To display a list of all the zones in the region to which Google Cloud Skills Boost assigned you, enter this partial command gcloud compute zones list | grep followed by the region that Google Cloud Skills Boost or your instructor assigned you to.

   Your completed command will look like this:

   gcloud compute zones list | grep {{{ project_0.default_region | REGION }}}

4. Choose a zone from that list other than the zone to which Google Cloud Skills Boost assigned you. For example, if Google Cloud Skills Boost assigned you to region and zone you might choose zone .

5. To set your default zone to the one you just chose, enter this partial command gcloud config set compute/zone followed by the zone you chose.

   Your completed command will look like this:

   gcloud config set compute/zone {{{ project_0.default_zone_2 | ZONE 2 }}}

6. To create a VM instance called my-vm-2 in that zone, execute this command:

   gcloud compute instances create "my-vm-2" \ --machine-type "e2-medium" \ --image-project "debian-cloud" \ --image-family "debian-11" \ --subnet "default"

Note: The VM can take about two minutes to launch and be fully available for use.

7. To close the Cloud Shell, execute the following command:

   exit

Click Check my progress to verify the objective. Create a virtual machine using the gcloud command line

Task 4. Connect between VM instances

1. In the Navigation menu, click Compute Engine > VM instances.

   You will see the two VM instances you created, each in a different zone.

   Notice that the Internal IP addresses of these two instances share the first three bytes in common. They reside on the same subnet in their Google Cloud VPC even though they are in different zones.

2. To open a command prompt on the my-vm-2 instance, click SSH in its row in the VM instances list.

3. Use the ping command to confirm that my-vm-2 can reach my-vm-1 over the network:

   ping my-vm-1.{{{ project_0.default_zone_1 | ZONE 1 }}}

   Notice that the output of the ping command reveals that the complete hostname of my-vm-1 is my-vm-1..c.PROJECT_ID.internal, where PROJECT_ID is the name of your Google Cloud Platform project. The Cloud console automatically supplies Domain Name Service (DNS) resolution for the internal IP addresses of VM instances.

4. Press Ctrl+C to abort the ping command.

5. Return to the Cloud Console tab.

6. Click SSH in the my-vm-1 row in the VM instances list.

7. At the command prompt on my-vm-1, install the Nginx web server:

   sudo apt-get install nginx-light -y

8. Use the nano text editor to add a custom message to the homepage of the web server:

   sudo nano /var/www/html/index.nginx-debian.html

9. Use the arrow keys to move the cursor to the line just below the h1 header. Add text like this, and replace YOUR_NAME with your name:

   Hi from YOUR_NAME

10. Press Ctrl+O and then press Enter to save your edited file, and then press Ctrl+X to exit the nano text editor.

11. Confirm that the web server is serving your new page. At the command prompt on my-vm-1, execute this command:

    curl http://localhost/

    The response will be the HTML source of the web server's home page, including your line of custom text.

12. Return to the command prompt on my-vm-2

13. To confirm that my-vm-2 can reach the web server on my-vm-1, at the command prompt on my-vm-2, execute this command:

    curl http://my-vm-1.{{{ project_0.default_zone_1 | ZONE 1 }}}/

    The response will again be the HTML source of the web server's home page, including your line of custom text.

14. In the Navigation menu, click Compute Engine > VM instances.

15. Copy the External IP address for my-vm-1 and paste it into the address bar of a new browser tab.

You will see your web server's home page, including your custom text.

Note: If you forgot to click Allow HTTP traffic when you created the my-vm-1 VM instance, your attempt to reach your web server's home page will fail. You can add a firewall rule to allow inbound traffic to your instances, although this topic is out of scope for this course.

Congratulations!

In this lab, you created virtual machine (VM) instances in two different zones and connected to them using ping, ssh, and HTTP.

Google Compute Engine and Amazon Elastic Compute Cloud (EC2) are both Infrastructure-as-a-Service (IaaS) offerings from Google Cloud and Amazon Web Services (AWS), respectively. Now that you have a better understanding of Compute Engine, let’s take a look into some of the key similarities and differences between Compute Engine and EC2:

Similarities:

• Both Google Cloud and AWS offer virtual machines (VMs) that can be launched quickly and easily.
• Both services can scale up or down quickly and easily, based on demand.
• Both services offer high availability and fault-tolerance features, such as automatic failover and load balancing.
• Both services offer various security features, such as virtual private clouds (VPCs), firewalls, and encryption.
• Both services offer a wide variety of operating systems, including Windows and Linux.
• Both of these VM options include a programmatic and graphical interface to deploy and manage instances; you can do this through the CLI client, SDK, graphic console.
• You can connect to either your EC2 instances or GCE VMs using common protocols like SSH or RDP.
• AWS and Google Cloud also provide a secure way to connect to your instances without opening RDP or SSH ports, in Google Cloud this feature is known as Identity-Aware Proxy (IAP), in AWS you use AWS Systems Manager Session Manager.

Differences:

• While both services offer a pay-as-you-go pricing model, there are some differences in the pricing structure. For example, GCE charges based on the amount of CPU and memory used, while EC2 charges based on the type of instance and the amount of time the instance is running.

End your lab

When you have completed your lab, click End Lab. Google Cloud Skills Boost removes the resources you’ve used and cleans the account for you.

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