Vertical Pod Autoscaler (VPA)

The Vertical Pod Autoscaler (VPA) automatically adjusts CPU and memory resource requests for containers based on historical and real-time usage. It makes pods "bigger" or "smaller" instead of adding more replicas.

How It Works

VPA consists of three components: the Recommender (monitors usage and computes optimal values), the Updater (evicts pods when recommendations diverge significantly), and the Admission Controller (mutates pod specs on creation with recommended values).

Update modes: Off (recommendations only), Initial (sets at creation only), Recreate (evicts and recreates pods), Auto (currently same as Recreate).

When to Use

• Databases, caches, stateful singletons
• You don't know the correct resource requests
• Right-sizing over-provisioned pods to save costs
• Workloads with varying resource needs over time

When NOT to Use

• Stateless apps that can scale horizontally (use HPA)
• Disruption-intolerant workloads
• Already using HPA on CPU/memory (they conflict)

Real-World Example

Step-by-Step Implementation

1. Install VPA

git clone https://github.com/kubernetes/autoscaler.git
cd autoscaler/vertical-pod-autoscaler
./hack/vpa-up.sh

# Verify
kubectl get pods -n kube-system | grep vpa

2. Start with recommendation-only mode

apiVersion: autoscaling.k8s.io/v1
kind: VerticalPodAutoscaler
metadata:
  name: postgres-vpa
spec:
  targetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: postgres
  updatePolicy:
    updateMode: "Off"   # Recommendation only

3. Enable auto-updates with bounds

apiVersion: autoscaling.k8s.io/v1
kind: VerticalPodAutoscaler
metadata:
  name: postgres-vpa
spec:
  targetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: postgres
  updatePolicy:
    updateMode: "Auto"
  resourcePolicy:
    containerPolicies:
    - containerName: postgres
      minAllowed:
        cpu: "250m"
        memory: "512Mi"
      maxAllowed:
        cpu: "4"
        memory: "8Gi"
      controlledResources: ["cpu", "memory"]

Common Pitfalls