Vertical Pod Autoscaler concept in Kubernetes - Commands & Configuration

Introduction

Sometimes your app needs more or less CPU and memory depending on how busy it is. Vertical Pod Autoscaler helps by automatically changing these resources for your app's pods so they run smoothly without wasting resources.

When your app's CPU or memory needs change over time and you want Kubernetes to adjust resources automatically.

When you notice pods crashing or slowing down because they don't have enough memory or CPU.

When you want to save money by not allocating too many resources to your pods all the time.

When you want to improve app performance by giving pods just the right amount of resources.

When you want to avoid manual updates to pod resource requests and limits as workload changes.

Config File - vpa.yaml

vpa.yaml

apiVersion: autoscaling.k8s.io/v1
kind: VerticalPodAutoscaler
metadata:
  name: my-app-vpa
  namespace: default
spec:
  targetRef:
    apiVersion: "apps/v1"
    kind: Deployment
    name: my-app
  updatePolicy:
    updateMode: "Auto"

This file tells Kubernetes to watch the Deployment named my-app in the default namespace.

The updateMode: Auto means Kubernetes will automatically adjust CPU and memory requests for pods in this deployment based on usage.

Commands

This command creates the Vertical Pod Autoscaler resource in Kubernetes to start monitoring and adjusting resources for the my-app deployment.

Terminal

kubectl apply -f vpa.yaml

Expected Output

verticalpodautoscaler.autoscaling.k8s.io/my-app-vpa created

This command shows the current state and recommendations of the Vertical Pod Autoscaler for the my-app deployment.

Terminal

kubectl get vpa my-app-vpa -o yaml

Expected Output

apiVersion: autoscaling.k8s.io/v1

kind: VerticalPodAutoscaler

metadata:

  name: my-app-vpa

  namespace: default

spec:

  targetRef:

    apiVersion: apps/v1

    kind: Deployment

    name: my-app

  updatePolicy:

    updateMode: Auto

status:

  recommendation:

    containerRecommendations:

    - containerName: my-app-container

      lowerBound:

        cpu: 100m

        memory: 128Mi

      target:

        cpu: 200m

        memory: 256Mi

      upperBound:

        cpu: 500m

        memory: 512Mi

→

-o yaml - Shows detailed information in YAML format

This command lists the pods of the my-app deployment to check their status after VPA adjusts resources.

Terminal

kubectl get pods -l app=my-app

Expected Output

NAME                       READY   STATUS    RESTARTS   AGE

my-app-5d7f9f7d9b-abc12   1/1     Running   0          3m

→

-l app=my-app - Filters pods by label app=my-app

Key Concept

If you remember nothing else from this pattern, remember: Vertical Pod Autoscaler automatically adjusts pod CPU and memory requests to match real usage, improving app stability and resource efficiency.

Common Mistakes

Not creating the Vertical Pod Autoscaler resource before expecting resource adjustments.

Without the VPA resource, Kubernetes does not know to monitor or adjust pod resources automatically.

Always apply the VPA configuration file with kubectl before expecting autoscaling to work.

Setting updateMode to "Off" or "Initial" and expecting automatic ongoing adjustments.

"Off" disables updates and "Initial" only sets resources at pod creation, so no continuous adjustment happens.

Use updateMode: "Auto" for continuous automatic resource updates.

Not labeling pods or deployments properly and then failing to see pods listed with kubectl get pods -l.

Without correct labels, filtering pods by label does not work and you cannot verify pod status easily.

Ensure your deployment and pods have consistent labels like app=my-app for easy management.

Summary

Create a Vertical Pod Autoscaler resource to monitor and adjust pod CPU and memory automatically.

Use kubectl apply to deploy the VPA configuration and kubectl get to check its recommendations and pod status.

Set updateMode to Auto for continuous automatic resource adjustments based on real usage.

Practice

1. What is the main purpose of the Vertical Pod Autoscaler in Kubernetes?

easy

A. Schedule pods to specific nodes manually

B. Scale the number of pod replicas up or down

C. Manage network policies between pods

D. Automatically adjust CPU and memory requests for pods based on usage

Solution

1. Step 1: Understand VPA's role

   The Vertical Pod Autoscaler changes resource requests (CPU, memory) for pods automatically based on their usage.

2. Step 2: Differentiate from other autoscalers

   Unlike Horizontal Pod Autoscaler, which changes pod count, VPA adjusts resource limits inside pods.

3. Final Answer:

   Automatically adjust CPU and memory requests for pods based on usage -> Option D

4. Quick Check:

   VPA adjusts resources, not pod count [OK]

Hint: VPA changes pod resources, not pod numbers [OK]

Common Mistakes:

• Confusing VPA with Horizontal Pod Autoscaler
• Thinking VPA manages pod replicas
• Assuming VPA controls networking

2. Which of the following is the correct YAML snippet to create a Vertical Pod Autoscaler targeting a deployment named my-app?

easy

A. apiVersion: autoscaling/v1
kind: HorizontalPodAutoscaler
metadata:
name: my-app-hpa
spec:
scaleTargetRef:
apiVersion: apps/v1
kind: Deployment
name: my-app

B. apiVersion: autoscaling.k8s.io/v1
kind: VerticalPodAutoscaler
metadata:
name: my-app-vpa
spec:
targetRef:
apiVersion: apps/v1
kind: Deployment
name: my-app

C. apiVersion: v1
kind: Pod
metadata:
name: my-app-pod
spec:
containers:
- name: my-app
image: my-app-image

D. apiVersion: autoscaling.k8s.io/v2
kind: VerticalPodAutoscaler
metadata:
name: my-app-vpa
spec:
target:
apiVersion: apps/v1
kind: Deployment
name: my-app

Solution

1. Step 1: Check apiVersion and kind

   Correct VPA uses apiVersion: autoscaling.k8s.io/v1 and kind: VerticalPodAutoscaler.

2. Step 2: Verify targetRef structure

   The targetRef field must specify the deployment with apiVersion, kind, and name correctly.

3. Final Answer:

   YAML with apiVersion autoscaling.k8s.io/v1, kind VerticalPodAutoscaler, and targetRef for my-app deployment -> Option B

4. Quick Check:

   VPA YAML uses targetRef, autoscaling.k8s.io/v1 [OK]

Hint: VPA uses targetRef, not scaleTargetRef [OK]

Common Mistakes:

• Using HorizontalPodAutoscaler instead of VerticalPodAutoscaler
• Wrong apiVersion like autoscaling/v1
• Incorrect field name target instead of targetRef

3. Given this VPA configuration snippet, what will happen when the pod's CPU usage increases beyond the current request?

apiVersion: autoscaling.k8s.io/v1
kind: VerticalPodAutoscaler
metadata:
  name: example-vpa
spec:
  targetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: example-app
  updatePolicy:
    updateMode: "Auto"

medium

A. The VPA will automatically update the pod's CPU requests to match usage

B. The pod replicas will increase to handle the load

C. The pod will restart immediately to apply new resources

D. Nothing happens until manual intervention

Solution

1. Step 1: Understand updateMode Auto

   When updateMode is Auto, VPA automatically adjusts resource requests without manual steps.

2. Step 2: Effect on pod resources

   VPA changes CPU and memory requests to match observed usage, improving stability and efficiency.

3. Final Answer:

   The VPA will automatically update the pod's CPU requests to match usage -> Option A

4. Quick Check:

   updateMode Auto means automatic resource adjustment [OK]

Hint: Auto updateMode means VPA adjusts resources automatically [OK]

Common Mistakes:

• Confusing VPA with Horizontal Pod Autoscaler scaling pods
• Thinking pods restart immediately on resource change
• Assuming manual approval is needed with Auto mode

4. You applied a Vertical Pod Autoscaler with updateMode: Auto, but pod resource requests did not change after high CPU usage. What is a likely cause?

medium

A. The Horizontal Pod Autoscaler is overriding VPA settings

B. The pod replicas are too few to trigger scaling

C. The VPA targetRef is incorrect or does not match the pods

D. The pod image version is outdated

Solution

1. Step 1: Check VPA targetRef correctness

   If targetRef does not correctly point to the pods or deployment, VPA cannot adjust resources.

2. Step 2: Understand VPA scope

   VPA only adjusts resources for pods matching targetRef; replicas count or pod image do not affect resource updates directly.

3. Final Answer:

   The VPA targetRef is incorrect or does not match the pods -> Option C

4. Quick Check:

   Incorrect targetRef means no resource updates [OK]

Hint: Verify targetRef matches pods exactly [OK]

Common Mistakes:

• Blaming pod replicas count for resource update failure
• Assuming HPA conflicts with VPA resource updates
• Thinking pod image version affects VPA behavior

5. You want to use Vertical Pod Autoscaler but avoid pod restarts during resource updates. Which updateMode should you choose and why?

hard

A. "Initial" to set resources only at pod creation without restarts later

B. "Auto" to update resources and restart pods automatically

C. "Off" to disable updates and avoid restarts

D. "Manual" to require manual approval before updates

Solution

1. Step 1: Understand updateMode options

   "Off" disables updates, "Auto" updates and restarts pods, "Initial" sets resources only at pod start, "Manual" requires manual approval.

2. Step 2: Choose mode to avoid restarts

   "Initial" mode applies resource recommendations only when pods start, so no restarts happen later.

3. Final Answer:

   "Initial" to set resources only at pod creation without restarts later -> Option A

4. Quick Check:

   Initial mode avoids restarts by updating only at pod start [OK]

Hint: Use Initial mode to avoid pod restarts on resource changes [OK]

Common Mistakes:

• Choosing Off disables VPA completely
• Assuming Manual mode avoids restarts automatically
• Confusing Auto mode with no restarts