CKAD Certified Kubernetes Application Developer (CKAD) Program Questions and Answers

ssh ckad00034c

You’re debugging an Ingress → Service → Deployment chain. The fastest way is:

reproduce the error with the right Host header

check Ingress rules (host/path/backend)

check Service (selector/port/targetPort)

check Endpoints (do we have ready pods?)

fix the manifest(s) under /home/candidate/content-marlin/

apply + re-test

Below are the exact commands + the most common fixes for this exact symptom.

1) Reproduce the failing request correctly

Even if DNS isn’t set up, you can test with a Host header:

curl -i -H "Host: content-marlin.local" http://127.0.0.1/content-marlin

If your ingress controller is not on localhost, find the NodePort/LoadBalancer IP. In these labs it’s often localhost via a local proxy, but if needed:

kubectl get svc -A | egrep -i 'ingress|nginx'

kubectl get nodes -o wide

(But start with the localhost curl above.)

2) Inspect the provided manifests (this is what you must edit)

cd /home/candidate/content-marlin/

ls -l

sed -n '1,200p' *.yaml

Also view what’s currently live in the cluster:

kubectl -n content-marlin get deploy,svc,ingress

kubectl -n content-marlin describe ingress content-marlin-ingress

kubectl -n content-marlin get ingress content-marlin-ingress -o yaml

What to look for in the Ingress:

spec.rules.host should be content-marlin.local

spec.rules.http.paths[].path should match /content-marlin

Backend service name must be your service

Backend service port must match the service port (name or number)

pathType should be Prefix (usually safest)

3) Validate Service → Pod wiring (most common real cause)

3.1 Check service selector and ports

kubectl -n content-marlin get svc -o wide

kubectl -n content-marlin describe svc content-marlin-deployment 2>/dev/null || true

kubectl -n content-marlin describe svc

Identify the service that the Ingress points to (from describe ingress).

Check if the Service selector matches pod labels:

kubectl -n content-marlin get pods --show-labels

kubectl -n content-marlin get svc -o jsonpath='{.spec.selector}{"\n"}'

3.2 Check endpoints (this tells you instantly if traffic can reach pods)

kubectl -n content-marlin get endpoints

kubectl -n content-marlin get endpoints -o wide

If ENDPOINTS is empty → Service selector doesn’t match Pods OR Pods aren’t Ready.

3.3 If endpoints empty, check pod readiness and labels

kubectl -n content-marlin get pods -o wide

kubectl -n content-marlin describe pod

4) Apply the most likely fix patterns

Fix pattern A: Ingress path needs rewrite

If your app serves / but you route /content-marlin, you often need rewrite.

Edit content-marlin-ingress manifest (in /home/candidate/content-marlin/) to include:

path: /content-marlin

pathType: Prefix

annotation: rewrite to / (common for nginx ingress)

Example (typical nginx-ingress):

metadata:

annotations:

nginx.ingress.kubernetes.io/rewrite-target: /

spec:

rules:

- host: content-marlin.local

http:

paths:

- path: /content-marlin

pathType: Prefix

backend:

service:

name:

port:

number: 80

If your ingress controller is not nginx, rewrite annotation may differ. But in CKAD labs, it’s very often nginx.

Fix pattern B: Ingress points to wrong Service port

If the Ingress backend says port 80 but your Service exposes 8080 (or uses a named port), align them:

Either change Ingress backend port.number

Or change Service spec.ports[].port / targetPort

Fix pattern C: Service selector mismatch (endpoints empty)

If pods have label app=content-marlin but service selector is app=content-marlin-deployment (or vice versa), fix the Service selector to match pod labels.

Service should have:

spec:

selector:

app:

Fix pattern D: Service targetPort wrong

If container listens on 8080 but service targetPort is 80, fix it:

spec:

ports:

- port: 80

targetPort: 8080

5) Apply the corrected manifests

After editing the YAMLs under /home/candidate/content-marlin/:

kubectl apply -f /home/candidate/content-marlin/

Wait for readiness:

kubectl -n content-marlin rollout status deploy content-marlin-deployment

kubectl -n content-marlin get endpoints

kubectl -n content-marlin describe ingress content-marlin-ingress

6) Re-test the URL

curl -i -H "Host: content-marlin.local" http://127.0.0.1/content-marlin

If you still get errors, also check ingress controller logs/events quickly:

kubectl -n content-marlin get events --sort-by=.lastTimestamp | tail -n 30

kubectl get pods -A | egrep -i 'ingress|nginx'

The fastest way for you to finish in 1 shot

Run these and paste the output (I’ll tell you exactly which line to change and what to change it to):

kubectl -n content-marlin describe ingress content-marlin-ingress

kubectl -n content-marlin get svc -o wide

kubectl -n content-marlin get endpoints -o wide

kubectl -n content-marlin get pods --show-labels

sed -n '1,200p' /home/candidate/content-marlin/*.yaml

But even without pasting, if you follow steps 2–4 above, you’ll find the broken link (Ingress rule, Service port, selector, or rewrite) and fix it cleanly.

Solution:

Solution:

To update the nginxsvc service to serve on port 5050, you will need to edit the service's definition yaml file. You can use the kubectl edit command to edit the service in place.

kubectl edit svc nginxsvc

This will open the service definition yaml file in your default editor. Change the targetPort of the service to 5050 and save the file.

To add an HAproxy container named haproxy bound to port 90 to the poller pod, you will need to edit the pod's definition yaml file located at /opt/KDMC00101/poller.yaml.

You can add a new container to the pod's definition yaml file, with the following configuration:

containers:

- name: haproxy

image: haproxy

ports:

- containerPort: 90

volumeMounts:

- name: haproxy-config

mountPath: /usr/local/etc/haproxy/haproxy.cfg

subPath: haproxy.cfg

args: ["haproxy", "-f", "/usr/local/etc/haproxy/haproxy.cfg"]

This will add the HAproxy container to the pod and configure it to listen on port 90. It will also mount the ConfigMap haproxy-config to the container, so that haproxy.cfg is available at /usr/local/etc/haproxy/haproxy.cfg.

To inject the configuration located at /opt/KDMC00101/haproxy.cfg to the container, you will need to create a ConfigMap using the following command:

kubectl create configmap haproxy-config --from-file=/opt/KDMC00101/haproxy.cfg

You will also need to update the args of the poller container so that it connects to localhost instead of nginxsvc. You can do this by editing the pod's definition yaml file and changing the args field to args: ["poller","--host=localhost"].

Once you have made these changes, you can deploy the updated pod to the cluster by running the following command:

kubectl apply -f /opt/KDMC00101/poller.yaml

This will deploy the enhanced pod with the HAproxy container to the cluster. The HAproxy container will listen on port 90 and proxy connections to the nginxsvc service on port 5050. The poller container will connect to localhost instead of nginxsvc, so that the connection is correctly proxied to the new service endpoint.

Please note that, this is a basic example and you may need to tweak the haproxy.cfg file and the args based on your use case.

Solution:

ssh ckad00023

You need two outcomes in moose:

At most 10 Pods total (across both Deployments).

About 20% of chipmunk-service traffic goes to canary-chipmunk-deployment.

In Kubernetes Services, traffic distribution is (roughly) proportional to the number of ready endpoints behind the Service. So the standard canary trick is:

total endpoints = 10

canary endpoints = 2

current endpoints = 8That gives ~20% to canary.

1) Inspect what exists

kubectl -n moose get deploy

kubectl -n moose get svc chipmunk-service -o wide

kubectl -n moose describe svc chipmunk-service

Get the Service selector (important):

kubectl -n moose get svc chipmunk-service -o jsonpath='{.spec.selector}{"\n"}'

Check current replicas:

kubectl -n moose get deploy current-chipmunk-deployment -o jsonpath='{.spec.replicas}{"\n"}'

kubectl -n moose get deploy canary-chipmunk-deployment -o jsonpath='{.spec.replicas}{"\n"}'

List pods + labels (to confirm both Deployments’ pods match the Service selector):

kubectl -n moose get pods --show-labels

2) Ensure both Deployments are behind the Service

This is the key: the pods from BOTH deployments must match the Service selector.

If the Service selector is something like app=chipmunk, then both Deployments’ pod templates must include app: chipmunk.

If one Deployment doesn’t match, patch its pod template labels to match the selector.

2A) Example: selector is app=chipmunk

(Only do this if you see the Service selector contains app=chipmunk and one of the deployments is missing it.)

kubectl -n moose patch deploy current-chipmunk-deployment \

-p '{"spec":{"template":{"metadata":{"labels":{"app":"chipmunk"}}}}}'

kubectl -n moose patch deploy canary-chipmunk-deployment \

-p '{"spec":{"template":{"metadata":{"labels":{"app":"chipmunk"}}}}}'

Wait for rollouts if patches triggered new ReplicaSets:

kubectl -n moose rollout status deploy current-chipmunk-deployment

kubectl -n moose rollout status deploy canary-chipmunk-deployment

Verify endpoints now include pods from both deployments:

kubectl -n moose get endpoints chipmunk-service -o wide

3) Set replicas to enforce “max 10 pods” and “20% canary”

Set:

current = 8

canary = 2Total = 10.

kubectl -n moose scale deploy current-chipmunk-deployment --replicas=8

kubectl -n moose scale deploy canary-chipmunk-deployment --replicas=2

Wait until ready:

kubectl -n moose rollout status deploy current-chipmunk-deployment

kubectl -n moose rollout status deploy canary-chipmunk-deployment

Confirm total pods is 10 (or less) and all are Running/Ready:

kubectl -n moose get pods

kubectl -n moose get pods | tail -n +2 | wc -l

Confirm endpoints count matches 10:

kubectl -n moose get endpoints chipmunk-service -o jsonpath='{.subsets[*].addresses[*].ip}' | wc -w

4) Test load balancing via NodePort 30000

Run several times:

for i in $(seq 1 30); do curl -s http://localhost:30000/; echo; done

You should see canary responses appear roughly ~20% of the time (not exact every run).

If you want a clearer signal, check which pods are endpoints and ensure 2 belong to canary and 8 to current:

kubectl -n moose get pods -l app=chipmunk -o wide

kubectl -n moose get endpoints chipmunk-service -o wide

Goal: fix nosql Deployment in haddock so the container stops OOM’ing by setting:

memory request = 128Mi

memory limit = half of the namespace’s maximum memory constraint

You must do this on the correct host.

0) Connect to the correct host

ssh ckad00032

1) Confirm the failing Deployment / Pods

kubectl -n haddock get deploy nosql

kubectl -n haddock get pods -l app=nosql 2>/dev/null || kubectl -n haddock get pods

If pods are crashing, check why (you’ll likely see OOMKilled):

kubectl -n haddock describe pod

2) Find the maximum memory constraint set for the haddock namespace

In CKAD labs, this is commonly enforced by a LimitRange (max memory per container). Sometimes it can also be a ResourceQuota.

2A) Check LimitRange (most likely)

kubectl -n haddock get limitrange

kubectl -n haddock get limitrange -o yaml

Extract the max memory value quickly:

MAX_MEM=$(kubectl -n haddock get limitrange -o jsonpath='{.items[0].spec.limits[0].max.memory}')

echo "Namespace max memory constraint: $MAX_MEM"

2B) If no LimitRange exists, check ResourceQuota

kubectl -n haddock get resourcequota

kubectl -n haddock describe resourcequota

If quota is used, you’re looking for something like limits.memory (but the question wording “maximum memory constraint” usually points to LimitRange max.memory).

3) Compute “half of the max memory constraint”

Run this small snippet to compute HALF in Mi (handles Mi and Gi):

HALF_MEM=$(python3 - <<'PY'

import os, re

q = os.environ.get("MAX_MEM","").strip()

m = re.fullmatch(r"(\d+)(Mi|Gi)", q)

if not m:

raise SystemExit(f"Cannot parse MAX_MEM='{q}'. Expected like 512Mi or 1Gi.")

val = int(m.group(1))

unit = m.group(2)

# convert to Mi

mi = val if unit == "Mi" else val * 1024

half_mi = mi // 2

print(f"{half_mi}Mi")

PY

)

echo "Half of max: $HALF_MEM"

Example: if MAX_MEM=512Mi → HALF_MEM=256Mi

Example: if MAX_MEM=1Gi → HALF_MEM=512Mi

4) Update the nosql Deployment (DO NOT delete it)

First, get the container name (Deployment may have a custom container name):

kubectl -n haddock get deploy nosql -o jsonpath='{.spec.template.spec.containers[*].name}{"\n"}'

Now set resources (this updates the Deployment in-place):

kubectl -n haddock set resources deploy nosql \

--requests=memory=128Mi \

--limits=memory=$HALF_MEM

5) Ensure the update rolls out successfully

kubectl -n haddock rollout status deploy nosql

6) Verify the pod has the right requests/limits

kubectl -n haddock get deploy nosql -o jsonpath='{.spec.template.spec.containers[0].resources}{"\n"}'

kubectl -n haddock get pods

Pick the new pod and confirm:

kubectl -n haddock describe pod | sed -n '/Requests:/,/Limits:/p'

You should see:

Requests: memory 128Mi

Limits: memory

If rollout fails (common cause)

If you accidentally set a limit above the namespace max, pods won’t start. Check events:

kubectl -n haddock describe deploy nosql

kubectl -n haddock get events --sort-by=.lastTimestamp | tail -n 20

Solution:

Solution:

Below is an exam-style, step-by-step solution (commands + verification). Follow exactly on host ckad000.

0) Connect to the right host

ssh ckad000

(Optional but good sanity check)

kubectl config current-context

kubectl get ns

1) Inspect the existing Deployment (to know its labels/ports)

kubectl -n prod get deploy nginx-deployment

kubectl -n prod get deploy nginx-deployment -o wide

Check what labels the Pod template already has (important for the Service selector):

kubectl -n prod get deploy nginx-deployment -o jsonpath='{.spec.template.metadata.labels}{"\n"}'

Check container ports (so we expose the correct targetPort):

kubectl -n prod get deploy nginx-deployment -o jsonpath='{.spec.template.spec.containers[0].ports}{"\n"}'

If ports output is empty, it’s still often nginx on 80, but the safest is to confirm by describing a pod later.

2) Update Deployment to 2 replicas

Fastest:

kubectl -n prod scale deploy nginx-deployment --replicas=2

Verify:

kubectl -n prod get deploy nginx-deployment

3) Add label role=webFrontEnd to the Pod (Pod template label)

You must add it under:

spec.template.metadata.labels

Use a patch (quick + safe):

kubectl -n prod patch deploy nginx-deployment \

-p '{"spec":{"template":{"metadata":{"labels":{"role":"webFrontEnd"}}}}}'

Verify the Deployment template now includes it:

kubectl -n prod get deploy nginx-deployment -o jsonpath='{.spec.template.metadata.labels}{"\n"}'

Now verify the running Pods have the label (important!):

kubectl -n prod get pods --show-labels

If the label doesn’t show on pods immediately, wait for rollout:

kubectl -n prod rollout status deploy nginx-deployment

kubectl -n prod get pods --show-labels

4) Create a NodePort Service rover exposing the Deployment’s Pods

4.1 Get a reliable target port

Try to read containerPort:

kubectl -n prod get deploy nginx-deployment -o jsonpath='{.spec.template.spec.containers[0].ports[0].containerPort}{"\n"}'

If this prints a number (commonly 80), use it as --target-port.

If it prints nothing/empty, check a pod:

POD=$(kubectl -n prod get pod -l role=webFrontEnd -o jsonpath='{.items[0].metadata.name}')

kubectl -n prod describe pod "$POD" | sed -n '/Containers:/,/Conditions:/p' | sed -n '/Ports:/,/Environment:/p'

Assuming nginx is on 80 (most common), create the service:

kubectl -n prod expose deploy nginx-deployment \

--name=rover \

--type=NodePort \

--port=80 \

--target-port=80

If your nginx container port is different (e.g., 8080), change --target-port=8080 accordingly.

5) Verify Service + endpoints (critical)

kubectl -n prod get svc rover -o wide

kubectl -n prod describe svc rover

kubectl -n prod get endpoints rover -o wide

You should see 2 endpoints (matching 2 pods).

Also confirm the pods are Ready:

kubectl -n prod get pods -l role=webFrontEnd -o wide

Quick “CKAD checkpoints”

Deployment in prod has replicas=2

Pod template has label role=webFrontEnd

Service rover in prod is NodePort

Service endpoints point to the nginx pods

Solution:

Do this on ckad00027 and edit the given manifest file (that’s what the task expects).

0) Connect to correct host

ssh ckad00027

1) Open the manifest and identify the container + port

cd /home/candidate/spicy-pikachu

ls -l

sed -n '1,200p' app-deployment.yaml

Confirm the container port is 8081 in the YAML (usually under ports:).

2) Edit the YAML to add a readinessProbe

Edit the file:

vi app-deployment.yaml

Inside the Deployment, locate:

spec:

template:

spec:

containers:

- name: ...

image: ...

Add this under the container (same indentation level as image, ports, etc.):

readinessProbe:

httpGet:

path: /healthz

port: 8081

initialDelaySeconds: 6

periodSeconds: 3

Notes:

Use port: 8081 (because the app runs on 8081).

Ensure indentation is correct (2 spaces per level commonly).

Save and exit.

3) Apply the updated manifest

kubectl apply -f /home/candidate/spicy-pikachu/app-deployment.yaml

4) Ensure the Deployment rolls out successfully

kubectl -n prod rollout status deploy app-deployment

5) Verify the readiness probe is set

Check the probe from the live object:

kubectl -n prod get deploy app-deployment -o jsonpath='{.spec.template.spec.containers[0].readinessProbe}{"\n"}'

And confirm pods are becoming Ready:

kubectl -n prod get pods -l app=app-deployment

If the label selector differs, just:

kubectl -n prod get pods

kubectl -n prod describe pod | sed -n '/Readiness:/,/Conditions:/p'

That completes the task: readiness probe on /healthz, initialDelaySeconds: 6, periodSeconds: 3.