Vertical Pod Autoscaler concept in Kubernetes - Step-by-Step Execution

Process Flow - Vertical Pod Autoscaler concept

Pod runs with initial resources

↓

VPA monitors pod resource usage

↓

VPA analyzes CPU and memory usage

↓

VPA recommends new resource requests

↓

If pod restarts, new resources applied

↓

Pod runs with updated resources

The Vertical Pod Autoscaler watches pod resource use, suggests better CPU/memory settings, and applies them when pods restart.

Execution Sample

Kubernetes

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

This YAML defines a Vertical Pod Autoscaler that automatically adjusts resource requests for a specific pod.

Process Table

Step	Action	Pod CPU Usage	Pod Memory Usage	VPA Recommendation	Pod Resource Update
1	Pod starts with 200m CPU, 256Mi memory	150m	200Mi	No recommendation yet	Pod runs with initial resources
2	VPA monitors usage over time	180m	220Mi	Analyzing usage	No change yet
3	VPA detects sustained higher usage	210m	300Mi	Recommend CPU=250m, Memory=350Mi	Waiting for pod restart
4	Pod restarts with new resource requests	N/A	N/A	Resources updated	Pod runs with CPU=250m, Memory=350Mi
5	VPA continues monitoring	230m	340Mi	No further change	Pod runs stably with updated resources
Exit	No further resource changes needed	230m	340Mi	Stable	Execution stops

💡 Pod resources are stable and match usage; no further updates needed

Status Tracker

Variable	Start	After 1	After 2	After 3	After 4	Final
Pod CPU Request	200m	200m	200m	250m	250m	250m
Pod Memory Request	256Mi	256Mi	256Mi	350Mi	350Mi	350Mi
VPA Recommendation	None	None	Analyzing	Recommend 250m/350Mi	Applied	Stable

Key Moments - 3 Insights

Why doesn't the pod resource update immediately when VPA recommends new values?

The pod resource update happens only when the pod restarts, as shown in step 3 and 4 of the execution_table.

What does VPA monitor to decide resource recommendations?

VPA monitors actual CPU and memory usage over time, as seen in the Pod CPU Usage and Pod Memory Usage columns in the execution_table.

Can VPA reduce resources if usage drops?

Yes, VPA can recommend lower resources if usage drops, but changes apply only after pod restarts, similar to how it updates in step 4.

Visual Quiz - 3 Questions

Look at the execution_table at step 3, what resource values does VPA recommend?

A CPU=180m, Memory=220Mi

B CPU=200m, Memory=256Mi

C CPU=250m, Memory=350Mi

D CPU=300m, Memory=400Mi

💡 Hint

Check the 'VPA Recommendation' column at step 3 in the execution_table.

At which step does the pod actually get updated with new resource requests?

A Step 3

B Step 4

C Step 2

D Step 5

💡 Hint

Look for 'Pod restarts with new resource requests' in the 'Action' column.

If the pod never restarts, what happens to the resource requests?

A They never change

B They update after a delay

C They update immediately

D They update only if usage drops

💡 Hint

Refer to the explanation in key_moments about when resource updates apply.

Concept Snapshot

Vertical Pod Autoscaler (VPA) watches pod CPU and memory use.
It suggests better resource requests based on usage.
Changes apply only when pods restart.
VPA helps pods get enough resources without manual tuning.
Useful for workloads with changing resource needs.

Full Transcript

The Vertical Pod Autoscaler (VPA) in Kubernetes helps pods adjust their CPU and memory requests automatically. It watches how much CPU and memory a pod uses over time. When it sees the pod needs more or less resources, it recommends new values. However, these new resource requests only take effect when the pod restarts. This means VPA monitors usage, suggests changes, and waits for the pod to restart before applying updates. This process helps keep pods running efficiently without manual resource tuning.

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