Horizontal Pod Autoscaler vs Vertical Pod Autoscaler: Scaling Out vs Scaling Up

Mon, 03 Aug 2026 05:24:29 +0900

Overview

Both controllers watch metrics and adjust Kubernetes workloads automatically, but they scale in different dimensions. The Horizontal Pod Autoscaler adds or removes pod replicas to handle load, while the Vertical Pod Autoscaler resizes the CPU and memory requests/limits of existing pods.

Comparison Diagram

Comparison Table

Aspect	Horizontal Pod Autoscaler	Vertical Pod Autoscaler
What it adjusts	Number of pod replicas in a Deployment/ReplicaSet/StatefulSet	CPU and memory requests/limits on the pod’s containers
Metrics source	Metrics Server or custom/external metrics (CPU, memory, custom queries) via metrics.k8s.io API	Historical and current usage sampled by the VPA recommender component
Trigger condition	Observed metric crosses a target threshold averaged across pods	Recommender detects requests are consistently over- or under-provisioned
Action taken	Creates or deletes pod replicas to match target replica count	Evicts and recreates pods with new resource requests (or just recommends, depending on updateMode)
Disruption to running pods	None — existing pods are untouched, new ones are added or removed	Pod restart required to apply new resource values, causing brief downtime unless using in-place resize
Best fit for workload type	Stateless, horizontally scalable services behind a Service/load balancer	Single-instance or hard-to-replicate workloads, or right-sizing before enabling HPA
Conflict risk	Can fight with VPA if both manage CPU on the same workload	Should not manage CPU/memory targeted by HPA on the same workload simultaneously
Configuration object	HorizontalPodAutoscaler resource with min/max replicas and target metrics	VerticalPodAutoscaler resource with updateMode (Off, Initial, Recreate, Auto)

Key Differences

HPA changes replica count, VPA changes resource requests on existing pods.
VPA updates typically require a pod restart to take effect, while HPA scaling adds/removes pods without disrupting the rest.
Running both on the same metric (like CPU) causes conflicting decisions unless carefully scoped.
VPA is often used in recommendation-only mode to right-size requests before HPA takes over scaling.
HPA assumes the workload is stateless and replicable; VPA fits singleton or stateful workloads that can’t simply be duplicated.

When to Use Each

Horizontal Pod Autoscaler

Autoscaling on IT Comparison

Horizontal Pod Autoscaler vs Vertical Pod Autoscaler: Scaling Out vs Scaling Up

Overview

Comparison Diagram

Comparison Table

Key Differences

When to Use Each