How is scalability achieved in applications in Kubernetes?

Application scalability in Kubernetes is achieved through several key mechanisms:

• ReplicaSets: allow running multiple copies of a pod, providing horizontal scaling.
• Horizontal Pod Autoscaler (HPA): automatically increases or decreases the number of pods based on metrics (CPU, memory, custom metrics).
• Cluster Autoscaler: automatically adds or removes nodes in the cluster depending on the load.
• Load Balancing: Kubernetes services distribute traffic among pods, ensuring even load.

Example manifest for HPA scaling a Deployment based on CPU:

apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
  name: example-hpa
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: example-deployment
  minReplicas: 2
  maxReplicas: 10
  metrics:
  - type: Resource
    resource:
      name: cpu
      target:
        type: Utilization
        averageUtilization: 50

Thus, Kubernetes provides flexible and automatic application scaling depending on current load.