A 3-tier application architecture on Red Hat Device Edge

2. As a root user, start the MicroShift service by entering the following command:

   $ sudo systemctl start microshift

3. To configure your RHEL machine to start MicroShift when your machine starts, enter the following command:

   $ sudo systemctl enable microshift

4. Follow the Procedure to Access the MicroShift cluster.

3. Create the application user and grant privileges to qod database:

mysql>create user 'appuser'@'10.42.0.0/16' identified with mysql_native_password by 'Appuser@1';
    mysql> grant all privileges on qod.* to 'appuser'@'10.42.0.0/16' ;

4. Load the data in qod database:

   mysql> source /var/lib/mysql-files/1_createdb.sql
       mysql> source /var/lib/mysql-files/2_authors.sql
       mysql> source /var/lib/mysql-files/3_genres.sql
       mysql> source /var/lib/mysql-files/4_quotes.sql

Deploy presentation and application containers

1. Download the resource definition files from microshift-qod.

2. Edit the qod-db-credentials file and update the DB_HOST with base64 encoded hostname of your RHEL where the MySQL is installed and configured:

    $ hostname | base64

Example:

[root microshift-qod]# cat qod-db-credentials
    kind: Secret
    apiVersion: v1
    metadata:
      name: qod-db-credentials
    data:
      DB_HOST: bXlzcWwtdm0=
      DB_PASS: QXBwdXNlckAx
      DB_USER: YXBwdXNlcg==
    type: Opaque
    [root microshift-qod]#

3. Create a namespace qod in the MicroShift cluster:

   $ oc create namespace qod

Optional: Switch to namespace qod:

$ oc config set-context --current --namespace=qod

Optional: Set alias for oc config set-context --current --namespace:

$ alias oc-project='oc config set-context --current --namespace'

4. Deploy the Presentation and Application tiers on MicroShift in qod namespace with Kustomize:

   $ oc apply -k ./microshift-qod -n qod

5. Check the status of the applications deployed:

   $ oc get all -n qod

The following example illustrates the kind of output you should expect:

$ oc get all -n qod
    NAME                        READY   STATUS  RESTARTS   AGE
    pod/qod-api-5d6bf8b5fc-88m6q   1/1  Running   0         6m32s
    pod/qod-web-79cf4c949b-fz2hq   1/1  Running   0         6m32s
    NAME            TYPE        CLUSTER-IP  EXTERNAL-IP   PORT(S)   AGE
    service/qod-api   ClusterIP   10.43.52.46   <none>        8080/TCP   6m32s
    service/qod-web   ClusterIP   10.43.31.180   <none>       8080/TCP   6m32s
    NAME                    READY   UP-TO-DATE   AVAILABLE   AGE
    deployment.apps/qod-api   1/1   1           1           6m32s
    deployment.apps/qod-web   1/1   1           1           6m32s
    NAME                                DESIRED   CURRENT   READY   AGE
    replicaset.apps/qod-api-5d6bf8b5fc   1      1       1       6m32s
    replicaset.apps/qod-web-79cf4c949b   1      1       1       6m32s
    $

Open the web browser in the Red Hat Linux host and key in qod-web service IP address with port 8080 to test the 3-tier application deployed. In the above example, IP address of qod-web service is 10.43.31.180. You should see output similar to what is shown in Figure 2.

Optional: To check the application from command line, run the following code:

$ curl 10.43.31.180:8080/random | grep '<i>'

The following example illustrates the kind of output you should expect:

$ curl 10.43.31.180:8080/random | grep '<i>'
      % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current
                                     Dload  Upload   Total   Spent    Left  Speed
    100  1144  100  1144    0     0  44000      0 --:--:-- --:--:-- --:--:-- 44000
              <i>So long as the memory of certain beloved friends lives in my heart, I shall say that life is good.</i>

Conclusion

The 3-tier architecture, coupled with Red Hat Device Edge, provides flexibility and isolation for deploying and managing edge applications. 

The following use cases demonstrate the versatility of the 3-tier architecture in edge computing, enabling a wide range of applications that require low latency, high performance, and real-time processing capabilities.

1. Edge analytics:

   • Real-time data processing: Analyzing large volumes of data generated at the edge to extract valuable insights and make timely decisions.

   • Machine learning: Training and deploying machine learning models at the edge for tasks such as predictive maintenance, anomaly detection, and object recognition.

2. Content delivery networks (CDNs)

   • Caching content: Storing frequently accessed content closer to end-users to reduce latency and improve performance.

   • Dynamic content generation: Generating customized content based on user location, preferences, and device characteristics.

3. Edge gaming:

   • Low-latency gaming: Providing immersive gaming experiences with minimal lag by processing game logic and rendering graphics closer to the player.

   • Multiplayer gaming: Enabling real-time multiplayer interactions with reduced network latency.

4. Augmented and virtual reality:

   • Real-time rendering: Processing and rendering complex 3D graphics and environments at the edge for immersive AR/VR experiences.

   • Interactive content: Enabling interactive content and experiences that respond to user inputs in real time.

5. Edge robotics:

   • Autonomous systems: Controlling and coordinating autonomous robots and drones for tasks such as inspection, delivery, and surveillance.

   • Real-time decision-making: Enabling robots to make quick decisions based on local data and environmental conditions.