WAF - Operational Excellence Hands On Activity

The operational excellence pillar covers the operations processes that keep an application running in production. Deployments must be reliable and predictable. Automated deployments reduce the chance of human error. Fast and routine deployment processes won't slow down the release of new features or bug fixes. Equally important, how does your application respond to spikes in demand, as well as how do you monitor and alert on your applications?

Resources

Why are we doing this?

The goal of this activity to give you some hands on experience with several principles Operational Excellence:

Activities

Activities
Architecture
Prerequisites
Deploy Azure Monitor Log Analytics Workspace and App Insights
Deploy Azure App Service and Web App
Configure App Insights and Diagnostics
Configure Azure Alerts and Autoscaling
- Alerts
- Autoscaling
Query Logs
Clean Up
What did we accomplish?
References

Architecture

Once this lab is completed you should have an Architecture that looks something like the diagram below.

Prerequisites

An Azure Subscription.

Deploy Azure Monitor Log Analytics Workspace and App Insights

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Navigate to the Azure Portal https://portal.azure.com
Click on the Cloud Shell. You may be prompted to create a storage account if this is your first time to use the cloud shell.
Ensure that you use Bash for the Cloud Shell

Set the context to the subscription you want to use.

az account set --subscription "<your subscription name or Id>"

Create a Resource Group and Log Analytics Workspace by typing these commands in the Cloud Shell.

az group create --name rg-opex --location northcentralus

az monitor log-analytics workspace create -g rg-opex -n la-ws-opex

Run the following commands to get the WorkspaceId and the Workspace Key, alternatively you can get them from the Portal as well.

az monitor log-analytics workspace show -g rg-opex --workspace-name la-ws-opex --query customerId

az monitor log-analytics workspace get-shared-keys -g rg-opex --workspace-name la-ws-opex

Create App Insights for the Web app

az extension add -n application-insights

wsID=$(az monitor log-analytics workspace show --workspace-name la-ws-opex -g rg-opex --query id --output tsv)

az monitor app-insights component create --app ai-opex \
--location northcentralus \
--kind web \
--resource-group rg-opex \
--application-type web \
--workspace $wsID

Deploy Azure App Service and Web App

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Deploy an App Service Plan and create a Web App

az appservice plan create -g rg-opex -n asp-opex-1 --location northcentralus --sku S1

let randomNum=$RANDOM*$RANDOM
webAppName=waopex$randomNum
az webapp create -g rg-opex -p asp-opex-1 -n $webAppName

webAppId=$(az webapp show -g rg-opex -n $webAppName --query id --output tsv)

Create a deployment to the Web App, using a sample application. This is manual, to automatically sync you would need a Git Token. For the lab, we'll just use the manual integration.

gitRepo=https://github.com/Azure-Samples/php-docs-hello-world

az webapp deployment source config --name $webAppName \
--resource-group rg-opex \
--repo-url $gitRepo --branch master \
--manual-integration

Verify the web app by getting the Url and opening the web site. You should see Hello World!
```
echo http://$webAppName.azurewebsites.net
```
Verify deployment settings in the Portal.
1. In the portal, navigate to the rg-opex resource group and click on the app service you created.
2. Click on the Deployment Center
3. Verify that the Repository and Branch are set.

Configure App Insights and Diagnostics

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Configure App Insights for the Web app

az monitor app-insights component connect-webapp -a ai-opex \
-g rg-opex \
--app ai-opex \
--web-app $webAppId

Let's verify that the Web App has been configured with your Application Insights you just created.
1. In the portal, navigate to the rg-opex resource group and click on the app service.
1. Click on 'View Application Insights data -->' this will take you to the Application Instights instance.

Create Diagnostic Settings for the Web app

 wsID=$(az monitor log-analytics workspace show --workspace-name la-ws-opex -g rg-opex --query id --output tsv)

az monitor diagnostic-settings create --resource $webAppId --name diagWebApp --workspace $wsID --logs '[{"category":"AppServiceHTTPLogs","enabled":true,"retentionPolicy":{"enabled":false,"days":0}},{"category":"AppServiceConsoleLogs","enabled": true,"retentionPolicy":{"enabled":false,"days":0}}]' --metrics '[{"category":"AllMetrics","enabled":true,"retentionPolicy":{"enabled":false,"days":0}}]'

Let's verify the Diagnostic settings were created in the portal.
1. In the portal, navigate to the rg-opex resource group and click on the app service.
1. Click on Diagnostic Settings in the Monitoring Section
1. Click on the Edit Settings of the diagWebApp setting
1. You should see the settings as we created them in the CLI.
Create some load from the Cloud Shell. You may leave this running while you complete the lab.
```
while true
do
    curl http://$webAppName.azurewebsites.net
done
```
Type Ctrl+C when finished with load test after the lab.

Configure Azure Alerts and Autoscaling

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Alerts

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Now we will configure alerts to let us know when our Web App begins to consume a certain % of CPU Utilization.

Navigate to https://portal.azure.com .
Ensure you are in your subscription.
Navigate or search for Alerts and click on it.
Click on + Create > Alert rule
Click on + Select Scope
Filter by App Service plans and select the asp-opex-1 item then click Done.
Click on Next: Condition > Then select the CPU Percentage signal
Configure the signal logic, for the lab utilize the graph to make a decision as to when this might trigger. In this scenario, my utilization is pretty low, so I will set it to 2
Click on Next: Action > + Create action group
Create the action group. Save it in rg-opex resource group and name it agEmail
Click on Next: Notifications >
- Choose: Email/SMS message/Push/Voice
- Name: EmailMe
- Email: [ Use your email address ]
Click on Next: Actions >. We won't add any specific actions right now.
Click Review + Create.
Click Create to finish the action group creation.
Click on Next: Details > Setting the following
- Subscription: Choose your subscription
- Resource group: rg-opex
- Severity: Informational
- Alert rule name: Alert CPU
- Alert description: CPU Alert
- Enable upon creation: On
- Automatically resolve alerts: On
Click on Review + create. Then Create.

Autoscaling

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Now we will configure autoscale for our Web App to scale out and scale in when our Web App begins to consume a certain % of CPU Utilization.

Navigate to https://portal.azure.com .
Ensure you are in your subscription.
Navigate or search for Monitor anc click on it.
In the Settings Section click on Autoscale
Click on the rg-opex App Service Plan deployed previously.
Click on Custom autoscale.
Set the following Values
1. Scale mode: Scale based on a metric
2. Rules: + Add Rule - This will be the scale out rule
  - Metric Source: Current Resource (asp-opex-1)
  - Time aggregation: Average
  - Metric namespace: App Service plans standard metrics
  - Metric name: CPU Percentage
  - Dimension Name: Instance
  - Operator: =
  - Dimension Values: All Values
  - Operator: Greater than
  - Metric threshold to trigger scale action: 20 (Set this value below the CpuPercentage in the screen, just to trigger a scale out event. This is just for demonstration purposes, you should carefully evaluate what the actual threshold should be)
  - Duration (minutes): 5
  - Time grain (minutes): 1
  - Time grain statistic: Average
  - Operation: Increase count by
  - Instance count: 1
  - Cool down (minutes): 5
3. Repeat the previous step with one minor change to make the Scale in rule.
  1. Set the Metric threshold to trigger scale action: 15
  2. Set the Operation: Decrease count by
4. Now you should have a Scale out and Scale in rule
5. Instance Limits Minimum: 1
6. Instance Limits Maximum: 1
7. Instance Limits Default: 1
8. Click Save
9. After some time, you can click on the 'Run History' in the tool bar of the auto scale setting to see the observed instance count over time to observe when your app service plan scales out and in.

Query Logs

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Now lets learn how to write and execute a KQL Query against Log Analytics.

Navigate to https://portal.azure.com
Ensure you are in your subscription
Navigate to the rg-opex resource group
Click on your Log Analytics Workspace Item la-ws-opex
In the GeneraL Section click on Logs
Close the 'Queries' dialog window.

Enter the following KQL in the query text box and click Run. Then view the results.

    // Find In AzureMetrics 
    // Find in AzureMetrics to search for a specific value in the AzureMetrics table. Note that this query requires updating the <SeachValue> parameter to produce results 
    // This query requires a parameter to run. Enter value in SearchValue to find in table.
    let SearchValue =  "RG-OPEX";
    AzureMetrics
    | where * contains tostring(SearchValue)
    | take 1000

Clean Up

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To clean up the lab, run the following command in the cloud shell.

az group delete --name rg-opex

What did we accomplish?

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Automated infrastructure deployment using CLI script.
Configured Monitoring for Logs and Metrics with Diagnostic Settings.
Automated Web App Deployment from GitHub.
Configured Alerts and Autoscaling
Queried Log Analytics

shadmsft/boot-camp-waf-opex

WAF - Operational Excellence Hands On Activity

Resources

Why are we doing this?

Activities

Architecture

Prerequisites

Deploy Azure Monitor Log Analytics Workspace and App Insights

Deploy Azure App Service and Web App

Configure App Insights and Diagnostics

Configure Azure Alerts and Autoscaling

Alerts

Autoscaling

Query Logs

Clean Up

What did we accomplish?

References