DO180 - ch08s03

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Lab: Troubleshoot and Scale Applications

Navigate the OpenShift web console to identify CPU-consuming workloads.

Troubleshoot and fix a failed MySQL pod.

Manually scale an application.

Configure health probes.

Outcomes

You should be able to troubleshoot malfunctioning workloads, configure deployments, and scale applications.

As the student user on the workstation machine, use the lab command to prepare your system for this exercise.

This command ensures that all resources are available for this exercise. The command also creates the compreview-scale project and deploys some applications in that project.

The command creates the /home/student/DO180/labs/compreview-scale/resources.txt file. The resources.txt file contains the URLs of your OpenShift cluster and the name of the images that you use during the exercise. You can use the file to copy and paste these URLs and image names.

[student@workstation ~]$ lab start compreview-scale

Specifications

The API URL of your OpenShift cluster is https://api.ocp4.example.com:6443, and the oc command is already installed on your workstation machine.

The URL of the OpenShift web console is https://console-openshift-console.apps.ocp4.example.com. When you access the web console, select Red Hat Identity Management as the authentication mechanism.

Log in to the OpenShift cluster as the developer user with the developer password. The password for the admin user is redhatocp.

Perform the following tasks to complete the comprehensive review:

A pod in the cluster is consuming excessive CPU and is interfering with other tasks. Identify the pod and remove its workload.
The compreview-scale project already includes a web application at http://frontend-compreview-scale.apps.ocp4.example.com. When you access this URL, the application returns a list of quotations from famous authors. The application is broken for now, and is missing some configuration to be ready for production.
The application uses two Kubernetes Deployment objects. The frontend deployment provides the application web pages, and relies on the quotesdb deployment that runs a MySQL database. The lab command already created the services and routes that connect the application components and that make the application available from outside the cluster.
Fix the application and make it ready for production:
- The quotesdb deployment in the compreview-scale project starts a MySQL server, but the database is failing. Review the logs of the pod to identify and then fix the issue.
  Use the following parameters for the database:
  Name Value
  Username operator1
  Password redhat123
  Database name quotes
- You security team validated a new version of the MySQL container image that fixes a security issue. The new container image is registry.ocp4.example.com:8443/rhel9/mysql-80:1-237.
  Update the quotesdb deployment to use this image. Ensure that the database redeploys.
  The classroom setup copied the image from the Red Hat Ecosystem Catalog. The original image is registry.redhat.io/rhel9/mysql-80:1-237.
- Add a probe to the quotesdb deployment so that OpenShift can detect when the database is ready to accept requests. Use the mysqladmin ping command for the probe.
- Add a second probe that regularly verifies the status of the database. Use the mysqladmin ping command as well.
- Configure CPU and memory usage for the quotesdb deployment. The deployment needs 200 millicores of CPU and 256 MiB of memory to run, and you must restrict its CPU usage to 500 millicores and its memory usage to 1 GiB.
- Add a probe to the frontend deployment so that OpenShift can detect when the web application is ready to accept requests. The application is ready when an HTTP request on port 8000 to the /status path is successful.
- Add a second probe that regularly verifies the status of the web front end. The front end works as expected when an HTTP request on port 8000 to the /env path is successful.
- Configure CPU and memory usage for the frontend deployment. The deployment needs 200 millicores of CPU and 256 MiB of memory to run, and you must restrict its CPU usage to 500 millicores and its memory usage to 512 MiB.
- Scale the frontend application to three pods to accommodate for the estimated production load.
- To verify your work, access the http://frontend-compreview-scale.apps.ocp4.example.com URL. The application returns a list of quotations from famous authors.

Name	Value
Username	`operator1`
Password	`redhat123`
Database name	`quotes`

Use the OpenShift web console to identify and then delete the pod that consumes excessive CPU.
1. Use a web browser to access the https://console-openshift-console.apps.ocp4.example.com URL.
2. Select Red Hat Identity Management, and then log in as the admin user with the redhatocp password. Click Skip tour if the Welcome to the Developer Perspective message is displayed.
3. Switch to the Administrator perspective and then navigate to Observe → Dashboards.
4. Select the Kubernetes / Compute Resources / Cluster dashboard, and then click Inspect in the CPU Usage graph.
5. Set the zoom to five minutes and then hover over the graph. Notice that the interface lists the compreview-scale-load namespace in the first position, which indicated that this namespace is the first CPU consumer.
6. Navigate to Observe → Dashboards and then select the Kubernetes / Compute Resources / Namespace (Workloads) dashboard. Select the compreview-scale-load namespace and then set the time range to the last five minutes. The computeprime deployment is the workload that consumes excessive CPU.
7. Navigate to Workloads → Deployments and then select the compreview-scale-load project. Select the menu for the computeprime deployment and then click Delete Deployment. Click Delete to confirm the operation.

Review the logs of the pod that is failing for the quotesdb deployment. Set the missing environment variables in the quotesdb deployment.

[student@workstation ~]$ oc login -u developer -p developer \
  https://api.ocp4.example.com:6443
Login successful.
...output omitted...

Set the compreview-scale project as the active project.

[student@workstation ~]$ oc project compreview-scale
...output omitted...

List the pods to identify the failing pod from the quotesdb deployment. The names of the pods on your system probably differ.

[student@workstation ~]$ oc get pods
NAME                        READY   STATUS             RESTARTS         AGE
frontend-5fb85b4c75-5s7xr   0/1     CrashLoopBackOff   14 (2m52s ago)   50m
quotesdb-9b9776479-4z4g9    0/1     CrashLoopBackOff   14 (3m4s ago)    50m

Retrieve the logs for the failing pod. Some environment variables are missing.

[student@workstation ~]$ oc logs quotesdb-9b9776479-4z4g9
=> sourcing 20-validate-variables.sh ...
You must either specify the following environment variables:
  MYSQL_USER (regex: '^[a-zA-Z0-9_]+$')
  MYSQL_PASSWORD (regex: '^{[a-zA-Z0-9_~!@#$%}&*()-=<>,.?;:|]+$')
  MYSQL_DATABASE (regex: '^[a-zA-Z0-9_]+$')
...output omitted...

Add the missing environment variables to the quotesdb deployment.

[student@workstation ~]$ oc set env deployment/quotesdb \
  MYSQL_USER=operator1  MYSQL_PASSWORD=redhat123 MYSQL_DATABASE=quotes
deployment.apps/quotesdb updated

Update the MySQL container image for the quotesdb deployment.

Retrieve the name of the container that is running inside the pod. You need the container name to update its image.

[student@workstation ~]$ oc get deployment/quotesdb -o wide
NAME       READY   UP-TO-DATE   AVAILABLE   AGE   CONTAINERS ...
quotesdb   1/1     1            1           59m   mysql-80   ...

Set the image to registry.ocp4.example.com:8443/rhel9/mysql-80:1-237.

[student@workstation ~]$ oc set image deployment/quotesdb \
  mysql-80=registry.ocp4.example.com:8443/rhel9/mysql-80:1-237
deployment.apps/quotesdb image updated

Verify your work.

[student@workstation ~]$ oc get deployment/quotesdb -o wide
NAME      ... CONTAINERS   IMAGES
quotesdb  ... mysql-80     registry.ocp4.example.com:8443/rhel9/mysql-80:1-237

Wait for the deployment to roll out. You might have to rerun the command several times for the pod to report a Running status. The name of the pod on your system probably differs.

[student@workstation ~]$ oc get pods
NAME                        READY   STATUS             RESTARTS         AGE
frontend-5fb85b4c75-5s7xr   0/1     CrashLoopBackOff   15 (3m39s ago)   56m
quotesdb-54d64749c4-chhq6   1/1     Running            0                106s

Add a readiness and a liveness probe to the quotesdb deployment that runs the mysqladmin ping command.

Use the oc set probe command with the --readiness option to add the readiness probe.

[student@workstation ~]$ oc set probe deployment/quotesdb \
  --readiness -- mysqladmin ping
deployment.apps/quotesdb probes updated

Use the oc set probe command with the --liveness option to add the liveness probe.

[student@workstation ~]$ oc set probe deployment/quotesdb \
  --liveness -- mysqladmin ping
deployment.apps/quotesdb probes updated

Define resource limits for the quotesdb deployment. Set the CPU request to 200 millicores and the memory request to 256 MiB. Set the CPU limit to 500 millicores and the memory limit to 1 GiB.
```
[student@workstation ~]$ oc set resources deployment/quotesdb \
  --requests cpu=200m,memory=256Mi --limits cpu=500m,memory=1Gi
deployment.apps/quotesdb resource requirements updated
```
Add a readiness and a liveness probe to the frontend deployment.
1. Use the oc set probe command with the --readiness option to add the readiness probe that tests the /status path on HTTP port 8000.
```
[student@workstation ~]$ oc set probe deployment/frontend --readiness \
  --get-url http://:8000/status
deployment.apps/frontend probes updated
```
2. Use the oc set probe command with the --liveness option to add the liveness probe that tests the /env path on HTTP port 8000.
```
[student@workstation ~]$ oc set probe deployment/frontend --liveness \
  --get-url http://:8000/env
deployment.apps/frontend probes updated
```
Define resource limits for the frontend deployment. Set the CPU request to 200 millicores and the memory request to 256 MiB. Set the CPU limit to 500 millicores and the memory limit to 512 MiB.
```
[student@workstation ~]$ oc set resources deployment/frontend \
  --requests cpu=200m,memory=256Mi --limits cpu=500m,memory=512Mi
deployment.apps/frontend resource requirements updated
```

Scale the frontend deployment to three pods.

Scale the deployment.

[student@workstation ~]$ oc scale deployment/frontend --replicas 3
deployment.apps/frontend scaled

Wait for the deployment to scale up. You might have to rerun the command several times for the pods to report a Running status. The names of the pods on your system probably differ.

[student@workstation ~]$ oc get pods
NAME                        READY   STATUS    RESTARTS   AGE
frontend-86cdd7c7bf-8vrrs   1/1     Running   0          3m10s
frontend-86cdd7c7bf-ds79w   1/1     Running   0          44s
frontend-86cdd7c7bf-hpnwz   1/1     Running   0          44s
quotesdb-66ff98b88c-fhwhs   1/1     Running   0          12m

Verify that the application responds to web requests.

Retrieve the URL of the application.

[student@workstation ~]$ oc get route
NAME       HOST/PORT                                         PATH   SERVICES ...
frontend   frontend-compreview-scale.apps.ocp4.example.com          frontend ...

Use the curl command to test the application.

[student@workstation ~]$ curl \
  http://frontend-compreview-scale.apps.ocp4.example.com
<html>
	<head>
        <title>Quotes</title>
    </head>
    <body>

        <h1>Quote List</h1>

            <ul>

                    <li>1: When words fail, music speaks.
- William Shakespeare
</li>
...output omitted...

Evaluation

As the student user on the workstation machine, use the lab command to grade your work. Correct any reported failures and rerun the command until successful.

[student@workstation ~]$ lab grade compreview-scale

Finish

As the student user on the workstation machine, use the lab command to complete this exercise. This step is important to ensure that resources from previous exercises do not impact upcoming exercises.

[student@workstation ~]$ lab finish compreview-scale

Discuss Red Hat OpenShift Administration I: Operating a Production Cluster

Go to community

Version 4.12.2 versus 4.12 of DO180 course?

DRobitaille

21 lis 2023

I just noticed that there is now a version 4.12.2 of the DO180. Currently without any new updated videos. Do we have access to some sort of changelog to judge how different the new version is compared to 4.12. I'm currently in the process of reviewing the content of DO180/DO280 in preparation for my upcoming EX280 exam (based on "4.12"), so I'm wondering if it's worth studying the 4.12.2 version instead of 4.12.

470

Red Hat OpenShift Administration I: Containers & Kubernetes (DO180)

Haley_Ruccio

20 lip 2023

Deploy, manage, and troubleshoot containerized applications running as Kubernetes workloads in OpenShift clusters.Course DescriptionRed Hat OpenShift Administration I: Managing Containers and Kubernetes (DO180) prepares OpenShift cluster administrators to manage Kubernetes workloads and to collaborate with developers, DevOps engineers, system administrators, and SREs to ensure the availability of application workloads. This course focuses on managing typical end-user applications that are often accessible from a web or mobile UI and that represent most cloud-native and containerized workloads. Managing applications also includes deploying and updating their dependencies, such as databases, messaging, and authentication systems.The skills that you learn in this course apply to all versions of OpenShift, including Red Hat OpenShift on AWS (ROSA), Azure Red Hat OpenShift, and OpenShift Container Platform.This course is based on Red Hat OpenShift 4.12.Course Content SummaryManaging OpenShift clusters from the command-line interface and from the web console.Troubleshooting network connectivity between applications inside and outside an OpenShift cluster.Connecting Kubernetes workloads to storage for application data.Configuring Kubernetes workloads for high availability and reliability.Managing updates to container images, settings, and Kubernetes manifests of an application.Target AudienceSystem administrators and platform operators who are interested in managing OpenShift clusters and containerized applications.Site Reliability Engineers who are interested in maintaining and troubleshooting containerized applications on Kubernetes.System and software architects who are interested in learning and using the features and functions of an OpenShift cluster.Developers and Site Reliability Engineers that are new to container technology should enroll in Red Hat OpenShift Development I: Introduction to Containers with Podman (DO188).Recommended trainingTake our free assessment to gauge whether this offering is the best fit for your skills.Prerequisite: Containers, Kubernetes and Red Hat OpenShift Technical Overview or equivalent knowledge of Linux containers.Technology considerationsThis course requires internet access to access the cloud-based classroom environment that provides an OpenShift cluster and a remote administrator’s workstation.

Welcome to the Red Hat OpenShift Administration (DO180) group in the Red Hat Learning Community!

Deanna

18 lip 2023

We are excited to launch a space dedicated to the Red Hat Training course Red Hat OpenShift Administration I - Containers & Kubernetes! To gain the most value from this group - click the "Join Group" button in the upper right hand corner of the group home screen.We encourage group members to collaborate in this group to discuss topics, ask questions, share best practices and tips, provide course feedback, and share their accomplishments as it relates to DO180.Read more about Red Hat OpenShift Administration I here.

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Revision: do180-4.14-b6cd706