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Lab 3: Utilize Automation to Audit XC Configurations¶

The following lab tasks will guide you through using automation to audit deployed configurations within Distributed Cloud. Terraform will be utilized to deploy multiple HTTP Load balancers so that their configurations can be compared against a desired configuration state. A custom python API backend with a web front end will then be utilized to compare the HTTP Load balancer states.

Expected Lab Time: 40 minutes

Task 1: Deploy multiple HTTP load balancers with Terraform¶

In this task, you will create a tfvars file to specify environment variables unique to your environment. This tfvars file is slightly more advanced than the file used in Lab 2. This tfvars file utilizes a list object to specify mulitple key value pairs for each load balancer you want to create. The list object is utilized within a for expression within the Terraform resource to loop through each item in the list. This allows Terraform to create multiple objects using a single resource definition. After the tfvars file is created, you will intialize, plan, and apply your Terraform configuration to create multiple HTTP load balancers within your namespace.

Create a tfvars File for Specifying Environment Specific Variables
If you aren’t already in the Visual Studio Code browser tab, select that tab. If you closed the tab you can re-open Visual Studio Code by opening your UDF deployment and clicking on the VS CODE Access method under the Client system.
From the EXPLORER panel within Visual Studio Code, right click the MultipleLB folder, and then select new file. Enter the name terraform.tfvars for the new file that is created and press enter. Note Make sure you are right clicking on the MultipLB folder. We want to create this terraform.tfvars file within that directory so it only applies to the configuration within that same directory.*
This will open the terraform.tfvars file in the right panel of Visual Studio Code, enter the following values into the file: api_p12 = "../credentials/xc-api-cert.p12" tenant_name = "f5-xc-lab-app" namespace = "<namespace>" loadbalancers = [ { advertise_public = false dns_managed = false hostname = "lb1" name = "lb1" port = 80 waf_name = "non-standard" }, { advertise_public = false dns_managed = false hostname = "lb2" name = "lb2" port = 80 waf_name = "non-standard" }, { advertise_public = false dns_managed = false hostname = "lb3" name = "lb3" port = 80 waf_name = "non-standard" } ] Note Replace <namespace> with your assigned namespace. You need to wrap the namespace in “”. If your assigned namespace is brave-collie, enter: namespace = “brave-collie”

Create a tfvars File for Specifying Environment Specific Variables

If you aren’t already in the Visual Studio Code browser tab, select that tab. If you closed the tab

you can re-open Visual Studio Code by opening your UDF deployment and clicking on the VS CODE

Access method under the Client system.

From the EXPLORER panel within Visual Studio Code, right click the MultipleLB folder, and then

select new file. Enter the name terraform.tfvars for the new file that is created and press enter.

Note

Make sure you are right clicking on the MultipLB folder. We want to create this terraform.tfvars file *within that directory so it only applies to the configuration within that same directory.

This will open the terraform.tfvars file in the right panel of Visual Studio Code, enter the following

values into the file:

api_p12     = "../credentials/xc-api-cert.p12"
tenant_name = "f5-xc-lab-app"
namespace   = "<namespace>"
loadbalancers = [
  {
     advertise_public = false
     dns_managed      = false
     hostname         = "lb1"
     name             = "lb1"
     port             = 80
     waf_name         = "non-standard"
  },
  {
     advertise_public = false
     dns_managed      = false
     hostname         = "lb2"
     name             = "lb2"
     port             = 80
     waf_name         = "non-standard"
  },
  {
     advertise_public = false
     dns_managed      = false
     hostname         = "lb3"
     name             = "lb3"
     port             = 80
     waf_name         = "non-standard"
  }
]

Note

Replace <namespace> with your assigned namespace. You need to wrap the namespace in “”. If your assigned namespace is brave-collie, enter: namespace = “brave-collie”

Initialize, Plan, and Apply Your Terraform Code
In the Terminal at the bottom of Visual Studio Code, change directory into the MultipleLB folder.: cd ~/workspace/appworld-f5xc-automation/Terraform/MulitipleLB/
In the Terminal at the bottom of Visual Studio Code, run the following command to initialize the Terraform environment: terraform init
Review the Init Results. You should see a Terraform has been successfully initialized! message. DO NOT PROCEED AND ASK A LAB ASSISTANT FOR HELP IF YOU DON’T SEE THE SUCCESSFULLY INITIALIZED MESSAGE.
In the Terminal, enter the following command and press Enter: terraform plan
Review the Plan results. This shows what Terraform is planning to create.
In the Terminal, enter the following command and press Enter: terraform apply
When prompted Do you want to perform these actions?, type yes and press Enter.
Review the Apply results. This shows what Terraform created.

Initialize, Plan, and Apply Your Terraform Code

In the Terminal at the bottom of Visual Studio Code, change directory into the MultipleLB folder.:

cd ~/workspace/appworld-f5xc-automation/Terraform/MulitipleLB/

In the Terminal at the bottom of Visual Studio Code, run the following command to initialize the Terraform

environment:

terraform init

Review the Init Results. You should see a Terraform has been successfully initialized! message.

DO NOT PROCEED AND ASK A LAB ASSISTANT FOR HELP IF YOU DON’T SEE THE SUCCESSFULLY INITIALIZED MESSAGE.

In the Terminal, enter the following command and press Enter:

terraform plan

Review the Plan results. This shows what Terraform is planning to create.

In the Terminal, enter the following command and press Enter:

terraform apply

When prompted Do you want to perform these actions?, type yes and press Enter.

Review the Apply results. This shows what Terraform created.

Task 2: Audit your load balancer configurations¶

In this task, you will use a custom written web frontend and python API backend to audit your Distributed Cloud load balancer configurations. The python API backend utilizes the Distributed Cloud API to gather information from Distributed Cloud and format or tranform that data for presentation in the Web frontend. Creating the web frontend and python API backend are beyond the scope of this lab, but the source code is available if you would like to review outside of the lab.

Web Frontend API - https://github.com/aconley245/xc-audit

Python API Backend - https://github.com/aconley245/xc-audit-api

Use the XcAudit Web Application
Open Firefox from your UDF deployment by clicking on the FIREFOX Access method under the Client system.
Firefox should load the XcAudit Web App by default, but if it doesn’t enter http://10.1.1.4:8080 into the url bar in Firefox.
Enter f5-xc-lab-app in the Distributed Cloud Tenant field and your API Token value in the Distributed Cloud API Token field and then click Submit. Note If you didn’t save your API Token, you can create a new one following the procedure outlined in Lab 1.
An Alert pop up will let you know that your Distributed Cloud Credentials have been saved. Click OK.
Click on the WAF Audit tile to Audit your deployed WAF policies.
Click on the Load Balancer WAF Audit tile to Audit your deployed load balancers.
Select your Namespace from the Select Namespace dropdown and then select the WAF policy that you want to audit against from the Select WAF Policy dropdown. In a few seconds, the table will populate showing all of the configured load balancers and their configured WAF policy name. If the WAF policy matches the WAF policy matches the WAF policy selected, the table row will be highlighted in green. If the WAF policy doesn’t match or if a WAF policy is not defined, the table row will be highlighted in yellow.

Use the XcAudit Web Application

Open Firefox from your UDF deployment by clicking on the FIREFOX Access method under the Client

system.

Firefox should load the XcAudit Web App by default, but if it doesn’t enter http://10.1.1.4:8080 into the

url bar in Firefox.

Enter f5-xc-lab-app in the Distributed Cloud Tenant field and your API Token value in the Distributed

Cloud API Token field and then click Submit.

Note

If you didn’t save your API Token, you can create a new one following the procedure outlined in Lab 1.

An Alert pop up will let you know that your Distributed Cloud Credentials have been saved. Click OK.

Click on the WAF Audit tile to Audit your deployed WAF policies.

Click on the Load Balancer WAF Audit tile to Audit your deployed load balancers.

Select your Namespace from the Select Namespace dropdown and then select the WAF policy that you want

to audit against from the Select WAF Policy dropdown. In a few seconds, the table will populate

showing all of the configured load balancers and their configured WAF policy name. If the WAF policy

matches the WAF policy matches the WAF policy selected, the table row will be highlighted in green. If the

WAF policy doesn’t match or if a WAF policy is not defined, the table row will be highlighted in yellow.

Task 3: Modify the MulitipleLB Terraform configuration so the load balancers are using different WAF policies¶

In this task, you will modify your MultiLB Terraform configuration so the load balancers are using different WAF policies and then verify the changes in the XcAudit web application. This task is designed to use the skills you have learned in the previous tasks/labs and does not include detailed step by step directions.

Modify the MulitipleLB Terraform Configuration
Modify the MulitipleLB Terraform configuration so the configured load balancers are using the WAF policy that was created in Lab 2. Note You do not need to modify the main.tf file to accomplish this step.
Plan and apply your new configuration.
Verify the results within the XcAudit web application.

Task 4: Clean up the Distributed Cloud environment¶

In this task, you will remove the load balancers you created using the Terraform destroy command.

Clean up the Distributed Cloud environment
If you aren’t already in the Visual Studio Code browser tab, select that tab. If you closed the tab you can re-open Visual Studio Code by opening your UDF deployment and clicking on the VS CODE Access method under the Client system.
In the Terminal at the bottom of Visual Studio Code, change directory into the MultipleLB folder.: cd ~/workspace/appworld-f5xc-automation/Terraform/MulitipleLB/
In the Terminal, enter the following command and press Enter: terraform destroy
When prompted Do you really want to destroy all resources?, type yes and press Enter.
Review the results and verify that the three load balancers were destroyed.
In the Terminal at the bottom of Visual Studio Code, change directory into the Terraform folder.: cd ~/workspace/appworld-f5xc-automation/Terraform/
In the Terminal, enter the following command and press Enter: terraform destroy
When prompted Do you really want to destroy all resources?, type yes and press Enter.
Review the results and verify that the three load balancers were destroyed.

Clean up the Distributed Cloud environment

If you aren’t already in the Visual Studio Code browser tab, select that tab. If you closed the tab

you can re-open Visual Studio Code by opening your UDF deployment and clicking on the VS CODE

Access method under the Client system.

In the Terminal at the bottom of Visual Studio Code, change directory into the MultipleLB folder.:

cd ~/workspace/appworld-f5xc-automation/Terraform/MulitipleLB/

In the Terminal, enter the following command and press Enter:

terraform destroy

When prompted Do you really want to destroy all resources?, type yes and press Enter.

Review the results and verify that the three load balancers were destroyed.

In the Terminal at the bottom of Visual Studio Code, change directory into the Terraform folder.:

cd ~/workspace/appworld-f5xc-automation/Terraform/

In the Terminal, enter the following command and press Enter:

terraform destroy

When prompted Do you really want to destroy all resources?, type yes and press Enter.

Review the results and verify that the three load balancers were destroyed.

End of Lab 3
This concludes Lab 3. In this lab, you learned how to use a for loop in Terraform to create multiple objects from a single Terraform resource block. You then utilized the XcAudit Web Application to audit the WAF policies applied to the load balancers within your namespace. Finally you used the terraform destroy command to remove all of the Distributed Cloud objects that you created using Terraform.

End of Lab 3

This concludes Lab 3. In this lab, you learned how to use a for loop in Terraform to create multiple objects

from a single Terraform resource block. You then utilized the XcAudit Web Application to audit the WAF

policies applied to the load balancers within your namespace. Finally you used the terraform destroy

command to remove all of the Distributed Cloud objects that you created using Terraform.

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