more improvements on the process (#147)

## Purpose

1. move Dockfiles out of source directory
2. use 'az containerapp update' with updated Dockerfile to update apps
3. build service connection for apps one by one
4. refine the steps to update pom files
5. fix open ai deployment quota issue

## Does this introduce a breaking change?
<!-- Mark one with an "x". -->
```
[ ] Yes
[x] No
```

## Pull Request Type
What kind of change does this Pull Request introduce?

<!-- Please check the one that applies to this PR using "x". -->
```
[ ] Bugfix
[ ] Feature
[ ] Code style update (formatting, local variables)
[ ] Refactoring (no functional changes, no api changes)
[x] Documentation content changes
[ ] Other... Please describe:
```

cleanup.md

@@ -36,7 +36,7 @@ If you're not going to continue to use this lab environment, run the following c
 
       `az cognitiveservices account deployment list -g $RESOURCE_GROUP -n $OPEN_AI_SERVICE_NAME -o table`
 
-   - delete the deployments on by one
+   - delete the deployments one by one
 
       `az cognitiveservices account deployment delete -g $RESOURCE_GROUP -n $OPEN_AI_SERVICE_NAME --deployment-name <deployment-name>`
 

docs/02_lab_launch/0203.md

@@ -48,10 +48,10 @@ Your MySQL database will also have a firewall enabled. This firewall will by def
 1. Run the following commands to create a database in the Azure Database for MySQL Flexible Server instance.
 
    ```bash
-    az mysql flexible-server db create \
-        --server-name $MYSQL_SERVER_NAME \
-        --resource-group $RESOURCE_GROUP \
-        -d $DATABASE_NAME
+   az mysql flexible-server db create \
+       --server-name $MYSQL_SERVER_NAME \
+       --resource-group $RESOURCE_GROUP \
+       -d $DATABASE_NAME
    ```
 
 1. You will also need to allow connections to the server from your ACA environment. For now, to accomplish this, you will create a server firewall rule to allow inbound traffic from all Azure Services.
@@ -83,7 +83,7 @@ Your MySQL database will also have a firewall enabled. This firewall will by def
    * It changes the default `spring.sql.init` values to use `mysql` configuration.
    * It adds a `spring.datasource` property for your mysql database.
 
-1. In the part you pasted, update the values of the target datasource endpoint on line 6, the corresponding admin user account on line 7, and its password on line 8 to match your configuration. Set these values by using the information in the Azure Database for MySQL Flexible Server connection string you recorded earlier in this task.
+1. In the part you pasted, update the values of `url`, `username`, `password` in the segment `spring.datasource`. Set these values by using the information in the Azure Database for MySQL Flexible Server connection string you recorded earlier in this task.
 
 1. Save the changes and push the updates you made to the _application.yml_ file to your private GitHub repo by running the following commands from the Git Bash prompt:
 

docs/02_lab_launch/0205.md

@@ -62,12 +62,27 @@ Make sure the api-gateway and admin-server microservices have public IP addresse
 
 1. Once your build has finished, you can create each of the microservices.
 
-   Create image using acr and create container apps with the image from acr.
+   Create image using acr and create container apps with the image from acr. A Dockerfile is required for acr to build the image. The content of the Dockerfile is:
 
-   You'll start with the **api-gateway**. Since this is the entrypoint to your other microservices, you will create it with an `external` ingress. Also, you will bind this app to the configserver and eureka components you created earlier.
+   ```docker
+   # syntax=docker/dockerfile:1
+
+   # run
+   FROM mcr.microsoft.com/openjdk/jdk:17-distroless
+   COPY ./target/*.jar app.jar
+   EXPOSE 8080
+
+   # Run the jar file
+   ENTRYPOINT ["java", "-Djava.security.egd=file:/dev/./urandom", "-jar", "/app.jar"]
+   ```
+
+   The content is saved in file **../tools/Dockerfile**, we use the saved file in the next steps.
+
+1. Let's start with the **api-gateway**. Since this is the entrypoint to your other microservices, you will create it with an `external` ingress. Also, you will bind this app to the configserver and eureka components you created earlier.
 
    ```bash
    APP_NAME=api-gateway
+   cp -f ../tools.Dockerfile ./spring-petclinic-$APP_NAME/Dockerfile
    az containerapp create \
       --name $APP_NAME \
       --resource-group $RESOURCE_GROUP \
@@ -83,19 +98,22 @@ Make sure the api-gateway and admin-server microservices have public IP addresse
       --runtime java
    ```
 
-1. Wait for the provisioning to finish, now you can create the other microservices, **customers-service**, **vets-service** and **visits-service**. These will be internal microservices, exposed by the **api-gateway**. Since these microservices connect to the MySQL database, you will also assign them the user assigned managed identity.
+1. Wait for the provisioning to finish, now you can create the other microservices, **customers-service**, **vets-service** and **visits-service**. These will be internal microservices, exposed by the **api-gateway**.
+
+   Since these microservices connect to the acr with managed identity, assign them the user assigned managed identity `USER_ID`.
 
-   To save the execute time, you may use the script **create-apps.sh** to deploy the apps:
+   To save the execute time, you may use the script **../tools/create-apps.sh** to deploy the apps:
 
    ```bash
    export RESOURCE_GROUP ACA_ENVIRONMENT MYACR USER_ID JAVA_CONFIG_COMP_NAME JAVA_EUREKA_COMP_NAME
-   ./create-apps.sh
+   ../tools/create-apps.sh
    ```
 
    Or you can run the commands one by one to create these apps:
 
    ```bash
    APP_NAME=customers-service
+   cp -f ../tools.Dockerfile ./spring-petclinic-$APP_NAME/Dockerfile
    az containerapp create \
       --name $APP_NAME \
       --resource-group $RESOURCE_GROUP \
@@ -111,6 +129,7 @@ Make sure the api-gateway and admin-server microservices have public IP addresse
       --runtime java
 
    APP_NAME=vets-service
+   cp -f ../tools.Dockerfile ./spring-petclinic-$APP_NAME/Dockerfile
    az containerapp create \
       --name $APP_NAME \
       --resource-group $RESOURCE_GROUP \
@@ -126,6 +145,7 @@ Make sure the api-gateway and admin-server microservices have public IP addresse
       --runtime java
 
    APP_NAME=visits-service
+   cp -f ../tools.Dockerfile ./spring-petclinic-$APP_NAME/Dockerfile
    az containerapp create \
       --name $APP_NAME \
       --resource-group $RESOURCE_GROUP \

docs/03_lab_monitor/0302.md

@@ -26,7 +26,7 @@ Enable logging on your Azure Container Apps environment. You can follow the belo
    WORKSPACE=la-$APPNAME-$UNIQUEID
    az monitor log-analytics workspace create \
        --resource-group $RESOURCE_GROUP \
-       --workspace-name $WORKSPACE   
+       --workspace-name $WORKSPACE
    ```
 
 1. Enable logging on your Azure Container Apps environment.

docs/03_lab_monitor/0303.md

@@ -44,69 +44,86 @@ You can follow the below guidance to do so.
 
    ```bash
    AI_CONNECTIONSTRING=$(az monitor app-insights component show --app $AINAME -g $RESOURCE_GROUP --query connectionString --output tsv)
-
    echo $AI_CONNECTIONSTRING
    ```
 
-1. Define image tag
+1. Build a image with application insights agent, and set the related environment variables.
 
-   ```bash
-   IMAGE_TAG=petclinic-ai-agent
+   We customize the Dockerfile to build the image with application insights agent. The content of the Dockerfile is
+
+   ```dockerfile
+   # syntax=docker/dockerfile:1
+
+   # build
+   FROM mcr.microsoft.com/openjdk/jdk:17-mariner AS build
+   ARG AI_VERSION=3.5.4
+   RUN yum update -y && \
+      yum install -y wget
+
+   RUN wget https://github.com/microsoft/ApplicationInsights-Java/releases/download/$AI_VERSION/applicationinsights-agent-$AI_VERSION.jar -O ai.jar --quiet
+
+   # run
+   FROM mcr.microsoft.com/openjdk/jdk:17-distroless
+
+   COPY --from=build ./ai.jar ai.jar
+   COPY ./target/*.jar app.jar
+   EXPOSE 8080
+
+   # Run with javaagent
+   ENTRYPOINT ["java", "-Djava.security.egd=file:/dev/./urandom", "-javaagent:/ai.jar", "-jar", "/app.jar"]
    ```
 
-1. You will now use Azure Container Registry with customized Dockerfile to build your image, and update the container app to enable Application Insights Agent.
+   This content is saved in file **../tools/ai.Dockerfile**, we use the saved file in the next steps.
+
+1. You will now update the container app to enable Application Insights Agent.
 
-   Do this first for the **api-gateway** service. Notice how you are also setting the `APPLICATIONINSIGHTS_CONNECTION_STRING` and `APPLICATIONINSIGHTS_CONFIGURATION_CONTENT` environment variables.
+   Do this first for the **api-gateway** service. Notice how you are also setting the environment variables `APPLICATIONINSIGHTS_CONNECTION_STRING` and `APPLICATIONINSIGHTS_CONFIGURATION_CONTENT`.
 
    ```bash
    APP_NAME="api-gateway"
+   cp -f ../tools/ai.Dockerfile spring-petclinic-$APP_NAME/Dockerfile
 
-   az acr build -g $RESOURCE_GROUP --registry $MYACR --image spring-petclinic-$APP_NAME:$IMAGE_TAG --file spring-petclinic-$APP_NAME/ai.Dockerfile spring-petclinic-$APP_NAME
-
    az containerapp update \
       --name $APP_NAME \
       --resource-group $RESOURCE_GROUP \
-      --image $MYACR.azurecr.io/spring-petclinic-$APP_NAME:$IMAGE_TAG \
+      --source ./spring-petclinic-$APP_NAME \
       --set-env-vars APPLICATIONINSIGHTS_CONNECTION_STRING=$AI_CONNECTIONSTRING APPLICATIONINSIGHTS_CONFIGURATION_CONTENT='{"role": {"name": "'$APP_NAME'"}}'
    ```
 
 1. Once the app **api-gateway** deployment has succeeded, execute the same statements for the other microservices **customers-service**, **vets-service** and **visits-service**.
 
-   To save the execute time, you may use the script **build-update-apps.sh** to deploy the apps:
+   To save the execute time, you may use the script **../tools/build-update-apps.sh** to deploy the apps:
 
    ```bash
    export RESOURCE_GROUP MYACR IMAGE_TAG AI_CONNECTIONSTRING
-   ./build-update-apps.sh
+   ../tools/build-update-apps.sh
    ```
 
    Or you can run the commands one by one to build and update these apps:
 
    ```bash
    APP_NAME="customers-service"
-   az acr build -g $RESOURCE_GROUP --registry $MYACR --image spring-petclinic-$APP_NAME:$IMAGE_TAG --file spring-petclinic-$APP_NAME/ai.Dockerfile spring-petclinic-$APP_NAME
-
+   cp -f ../tools/ai.Dockerfile spring-petclinic-$APP_NAME/Dockerfile
    az containerapp update \
       --name $APP_NAME \
       --resource-group $RESOURCE_GROUP \
-      --image $MYACR.azurecr.io/spring-petclinic-$APP_NAME:$IMAGE_TAG \
+      --source ./spring-petclinic-$APP_NAME \
       --set-env-vars APPLICATIONINSIGHTS_CONNECTION_STRING=$AI_CONNECTIONSTRING APPLICATIONINSIGHTS_CONFIGURATION_CONTENT='{"role": {"name": "'$APP_NAME'"}}'
 
    APP_NAME="vets-service"
-   az acr build -g $RESOURCE_GROUP --registry $MYACR --image spring-petclinic-$APP_NAME:$IMAGE_TAG --file spring-petclinic-$APP_NAME/ai.Dockerfile spring-petclinic-$APP_NAME
-
+   cp -f ../tools/ai.Dockerfile spring-petclinic-$APP_NAME/Dockerfile
    az containerapp update \
       --name $APP_NAME \
       --resource-group $RESOURCE_GROUP \
-      --image $MYACR.azurecr.io/spring-petclinic-$APP_NAME:$IMAGE_TAG \
+      --source ./spring-petclinic-$APP_NAME \
       --set-env-vars APPLICATIONINSIGHTS_CONNECTION_STRING=$AI_CONNECTIONSTRING APPLICATIONINSIGHTS_CONFIGURATION_CONTENT='{"role": {"name": "'$APP_NAME'"}}'
 
    APP_NAME="visits-service"
-   az acr build -g $RESOURCE_GROUP --registry $MYACR --image spring-petclinic-$APP_NAME:$IMAGE_TAG --file spring-petclinic-$APP_NAME/ai.Dockerfile spring-petclinic-$APP_NAME
-
+   cp -f ../tools/ai.Dockerfile spring-petclinic-$APP_NAME/Dockerfile
    az containerapp update \
       --name $APP_NAME \
       --resource-group $RESOURCE_GROUP \
-      --image $MYACR.azurecr.io/spring-petclinic-$APP_NAME:$IMAGE_TAG \
+      --source ./spring-petclinic-$APP_NAME \
       --set-env-vars APPLICATIONINSIGHTS_CONNECTION_STRING=$AI_CONNECTIONSTRING APPLICATIONINSIGHTS_CONFIGURATION_CONTENT='{"role": {"name": "'$APP_NAME'"}}'
    ```
 
@@ -115,3 +132,87 @@ You can follow the below guidance to do so.
 
    {: .note }
    > To make sure everything is back up and running as expected, you may want to double check if all your services are back up and running. Check console log if you are seeing any service in failed state.
+
+## Analyze application specific monitoring data
+
+Now that Application Insights is properly configured, you can use this service to monitor what is going on in your application. You can follow the below guidance to do so.
+
+- [Application Insights Overview dashboard](https://learn.microsoft.com/azure/azure-monitor/app/overview-dashboard)
+
+Use this guidance to take a look at:
+- The Application Map
+- Performance data
+- Failures
+- Metrics
+- Live Metrics
+- Availability
+- Logs
+
+To get the logging information flowing, you should navigate to your application and to the different sub-pages and refresh each page a couple of times. It might take some time to update Application Insights with information from your application.
+
+Step by step operations
+
+1. In your browser, navigate to the Azure Portal and your resource group.
+
+1. Select the Application Insights resource in the resource group. On the overview page you will already see data about Failed requests, Server response time, Server requests and Availability.
+
+   ![ai_overview](../../images/ai_overview.png)
+
+1. Select _Application map_. This will show you information about the different applications running in your Spring Cloud Service and their dependencies. This is where the role names you configured in the YAML files are used.
+
+   ![application map](../../images/app-map.png)
+
+1. Select the _api-gateway_ service. This will show you details about this application, like slowest requests and failed dependencies.
+
+   ![api-gateway](../../images/api-gateway.png)
+
+1. Select _Performance_. This will show you more data on performance. 
+
+   ![performance](../../images/api-gw-perf.png)
+
+1. You can also drag your mouse on the graph to select a specific time period, and it will update the view.
+
+1. Select again your Application Insights resource to navigate back to the _Application map_ and the highlighted _api-gateway_ service.
+
+1. Select _Live Metrics_, to see live metrics of your application. This will show you near real time performance of your application, as well as the logs and traces coming in
+
+   ![live metrics](../../images/live-perf.png)
+
+1. Select _Availability_, and next _Create Standard test_, to configure an availability test for your application.
+
+1. Fill out the following details and select _Create_: 
+
+   - *Test name*: Name for your test
+   - *URL*: Fill out the URL to your api-gateway
+   - Keep all the default settings for the rest of the configuration. Notice that Alerts for this test will be enabled.
+
+   Once created every 5 minutes your application will now be pinged for availability from 5 test locations.
+
+1. Select the three dots on the right of your newly created availability test and select _Open Rules (Alerts) page_.
+
+1. Select the alert rule for your availability test. By default there are no action groups associated with this alert rule. We will not configure them in this lab, but just for your information, with action groups you can send email or SMS notifications to specific people or groups.
+
+   - [Create and manage action groups in the Azure portal](https://docs.microsoft.com/azure/azure-monitor/alerts/action-groups) 
+
+1. Navigate back to your Application Insights resource.
+
+1. Select _Failures_, to see information on all failures in your applications. You can click on any of the response codes, exception types or failed dependencies to get more information on these failures.
+
+   ![failures](../../images/failure.png)
+
+1. Select _Performance_, to see performance data of your applications' operations. This will be a similar view to the one you looked at earlier.
+
+   ![performance](../../images/perf2.png)
+
+1.  Select _Logs_, to see all logged data. You can use Kusto Query Language (KQL) queries to search and analyze the logged data
+
+   * [Log queries in Azure Monitor](https://docs.microsoft.com/azure/azure-monitor/logs/log-query-overview) 
+
+   {:style="counter-reset:step-counter 16"}
+1.  Select _Queries_ and next _Performance_.
+
+1.  Double click _Operations performance_. This will load this query in the query window.
+
+1.  Select _Run_, to see the results of this query.
+
+   ![performance](../../images/performance3.png)