KEDA: Event-Driven Autoscaling for Kubernetes

💡 Quick Answer: Scale Kubernetes workloads with KEDA based on external events: queue depth, cron schedules, Prometheus metrics, HTTP traffic, and 60+ event sources.

The Problem

Engineers frequently search for this topic but find scattered, incomplete guides. This recipe provides a comprehensive, production-ready reference.

The Solution

Install KEDA

helm repo add kedacore https://kedacore.github.io/charts
helm install keda kedacore/keda --namespace keda --create-namespace

Scale on Queue Depth (RabbitMQ)

apiVersion: keda.sh/v1alpha1
kind: ScaledObject
metadata:
  name: rabbitmq-consumer
spec:
  scaleTargetRef:
    name: consumer-deployment
  minReplicaCount: 0      # Scale to zero when idle!
  maxReplicaCount: 30
  triggers:
    - type: rabbitmq
      metadata:
        host: amqp://user:pass@rabbitmq.default:5672/
        queueName: tasks
        queueLength: "5"   # 1 pod per 5 messages

Scale on Prometheus Metric

apiVersion: keda.sh/v1alpha1
kind: ScaledObject
metadata:
  name: api-scaler
spec:
  scaleTargetRef:
    name: api-deployment
  minReplicaCount: 2
  maxReplicaCount: 50
  triggers:
    - type: prometheus
      metadata:
        serverAddress: http://prometheus.monitoring:9090
        metricName: http_requests_per_second
        query: sum(rate(http_requests_total{service="api"}[2m]))
        threshold: "100"   # Scale at 100 req/s per pod

Scale on Cron Schedule

triggers:
  - type: cron
    metadata:
      timezone: Europe/Paris
      start: 0 8 * * 1-5     # 8 AM weekdays
      end: 0 18 * * 1-5      # 6 PM weekdays
      desiredReplicas: "10"   # Business hours

KEDA vs HPA

graph TD
    A[KEDA] --> B{Event source}
    B -->|RabbitMQ queue depth| C[Scale consumers]
    B -->|Prometheus metric| D[Scale API pods]
    B -->|Cron schedule| E[Scale for business hours]
    B -->|Kafka lag| F[Scale stream processors]
    C -->|Queue empty| G[Scale to zero]

Frequently Asked Questions

Can KEDA scale CronJobs?

Yes! Use ScaledJob instead of ScaledObject to create Jobs on events — perfect for batch processing from queues.

Does KEDA replace HPA?

KEDA creates and manages HPA objects internally. You don’t need to create separate HPAs when using KEDA.

Best Practices

• Start with the simplest approach that solves your problem
• Test thoroughly in staging before production
• Monitor and iterate based on real metrics
• Document decisions for your team

Key Takeaways

• This is essential Kubernetes operational knowledge
• Production-readiness requires proper configuration and monitoring
• Use kubectl describe and logs for troubleshooting
• Automate where possible to reduce human error