Lab 6 summary
This lab teaches how to scale an OpenShift application up and down from the web console, specifically from the Topology view. The learner first deploys the Parksmap application from a container image, then uses the application Details panel to increase or decrease the number of running pods.
What the learner needs to know
The PDF says learners should already understand:
| Topic | Why it matters |
|---|---|
| OpenShift and Kubernetes relationship | OpenShift runs Kubernetes workloads |
| Kubernetes pods | Scaling means changing the number of pods |
| Developer Sandbox access | The lab is done in OpenShift Developer Sandbox |
What the learner will learn
| Skill | Meaning |
|---|---|
| Access application details | Open app details from the Topology view |
| Scale up | Increase the number of running pods |
| Scale down | Decrease the number of running pods |
| Understand pod-based scaling | More pods means more identical app instances available to handle traffic |
The PDF explains that scaling means increasing or decreasing the number of an application’s pods. A pod contains one or more containers that run the application logic.
Application used
| Item | Value |
|---|---|
| App name | Parksmap |
| Image source | External container image repository |
| Registry | Quay.io |
| Image used in Lab 6 | quay.io/openshiftroadshow/parksmap |
| Resource type | Deployment |
| Tool used | OpenShift web console |
Main lab flow
| Step | Action |
|---|---|
| 1 | Open Developer Sandbox |
| 2 | Log in with Red Hat account |
| 3 | Go to OpenShift web console |
| 4 | Click +Add |
| 5 | Select Container images |
| 6 | In Deploy Image, enter quay.io/openshiftroadshow/parksmap |
| 7 | Scroll to Deploy |
| 8 | Set Resource type to Deployment |
| 9 | Click Create |
| 10 | Open Topology view |
| 11 | Click the center of the Parksmap circular graphic |
| 12 | Open the Details tab |
| 13 | Use the up arrow beside the pod graphic to scale up |
| 14 | Use the down arrow beside the pod graphic to scale down |
The PDF specifically says the pod count changes in the circular graphic as you click the up/down arrows.
What this lab teaches conceptually
| Concept | Explanation |
|---|---|
| Pod | The unit where the application container runs |
| Service | Sends traffic to the application pods |
| Scaling up | Adding more identical pods |
| Scaling down | Reducing the number of pods |
| Topology view | Visual OpenShift console view for app resources |
| Details pane | UI panel where pod count can be changed |
CLI equivalent of Lab 6
The PDF uses the web console, but the matching oc CLI flow would be:
# Create a project for the lab
oc new-project parksmap-scale-demo
# Deploy Parksmap from the container image
oc new-app quay.io/openshiftroadshow/parksmap --name=parksmap
# Check created resources
oc get all
# Watch the first pod start
oc get pods --watch
# Scale up to 3 pods
oc scale deployment/parksmap --replicas=3
# Verify 3 pods are running
oc get pods -l app=parksmap
# Scale down to 1 pod
oc scale deployment/parksmap --replicas=1
# Verify only 1 pod remains
oc get pods -l app=parksmap
# Optional cleanup
oc delete all -l app=parksmap
Code language: PHP (php)Expected output after scaling up:
deployment.apps/parksmap scaled
Then:
NAME READY STATUS RESTARTS AGE
parksmap-xxxxxxxxx-aaaaa 1/1 Running 0 2m
parksmap-xxxxxxxxx-bbbbb 1/1 Running 0 20s
parksmap-xxxxxxxxx-ccccc 1/1 Running 0 20s
Difference from earlier labs
| Lab | Topic | Tool |
|---|---|---|
| Lab 3 | Deploy app from container image | Web console |
| Lab 4 | Deploy app from container image | oc CLI |
| Lab 6 | Deploy app from container image, then scale pods | Web console |
So Lab 6 is basically: Lab 3 + scaling practice using the Topology Details panel.
I’m Rajesh Kumar, a DevOps, SRE, DevSecOps, Cloud, and Platform Engineering expert passionate about sharing practical knowledge, real-world experiences, and industry best practices. I have worked at Cotocus and regularly write about technology, travel, investing, health, product reviews, and digital marketing through my various platforms.
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The tutorial provides a clear overview of scaling applications through the OpenShift web console, but it would be beneficial to emphasize that effective scaling requires understanding application characteristics and workload patterns. Increasing replicas alone may not resolve performance bottlenecks if limitations exist in databases, external services, or application startup times. Discussing Horizontal Pod Autoscalers, resource optimization, and monitoring techniques would give readers a more complete picture of managing scalable and cost-efficient deployments in production environments.