What is Keda, and how can you use it within your cluster to scale your application?

Scaling with Kubernetes KEDA

Keda (Kubernetes Event-Driven Autoscaling) is a lightweight, single-purpose component that extends Kubernetes’ autoscaling capabilities. It allows you to scale applications based on events or metrics from external sources, such as Redis queues, message brokers, or databases. Keda integrates with standard Kubernetes components, like Horizontal Pod Autoscaler (HPA), without modifying or overriding them.

How to use Keda within your cluster to scale your application

Choose an event source: Identify the event source that triggers scaling, such as a Redis queue, message broker, or database. Keda supports various scalers, including Redis, Kafka, RabbitMQ, and more.
Create a ScaledObject: Define a ScaledObject YAML file, which specifies the event source, scaler configuration, and the application to scale (e.g., a Deployment or Job). The ScaledObject contains two main sections:
Triggers: Define the event source and scaler configuration.
ScaleTargetRef: Reference the application to scale (e.g., a Deployment).
Deploy Keda: Install Keda in your Kubernetes cluster using Helm or a similar package manager.
Apply the ScaledObject: Use kubectl apply to deploy the ScaledObject YAML file to your cluster.
Configure the event source: Set up the event source (e.g., Redis) to produce events that trigger scaling.
Verify scaling: Monitor your application’s pods and replicas as Keda scales them up or down based on the event source’s activity.
Example ScaledObject YAML file:

apiVersion: keda.sh/v1alpha1
kind: ScaledObject
metadata:
  name: redis-scaledobject
spec:
  scaleTargetRef:
    name: my-deployment
    namespace: default
  triggers:
  - type: redis
    metadata:
      address: redis:6379
      listName: jobs
      listLength: "20"
    authenticationRef:
      name: redis-auth-secret

In this example, the ScaledObject scales a Deployment named my-deployment based on the number of items in a Redis list named jobs. When the list length exceeds 20, Keda will scale up the deployment; when the list is empty, it will scale down to 0 replicas.

By using Keda, you can decouple your application’s scaling from traditional Kubernetes metrics (e.g., CPU utilization) and instead rely on events or metrics from external sources to drive scaling decisions. This approach enables more efficient and flexible autoscaling for event-driven applications.