Getting Started with KEDA Autoscaling

Prerequisites

You can confirm your cluster version with kubectl version, and check whether KEDA is already present with kubectl get pods -n keda.

Install KEDA (if needed)

If KEDA is not already running in the cluster, install it with the official Helm chart:

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

This deploys the KEDA operator and metrics adapter into the keda namespace. The KubeMQ scaler is independent of this install — it registers with KEDA through the ScaledObject you create later.

Deploy the Scaler via Helm

Install the KubeMQ KEDA scaler from the chart bundled in the repository:

helm install kubemq-keda-scaler deploy/helm/kubemq-keda-scaler/

This deploys the scaler workload (image kubemq/kubemq-keda-scaler:1.0.0) and a ClusterIP Service that exposes its gRPC server on port 9090. The chart runs the container as a non-root user with a read-only root filesystem by default.

To install with custom values — for example, debug logging:

helm install kubemq-keda-scaler deploy/helm/kubemq-keda-scaler/ \
  --set env.logLevel=debug \
  --set resources.requests.cpu=100m

Verify the Scaler Service

Confirm the scaler's Kubernetes Service is up:

kubectl get svc kubemq-keda-scaler

You should see a ClusterIP Service exposing the gRPC port 9090:

NAME                 TYPE        CLUSTER-IP      EXTERNAL-IP   PORT(S)    AGE
kubemq-keda-scaler   ClusterIP   10.96.142.10    <none>        9090/TCP   30s

The Service forwards port 9090 to the container's named grpc target port. KEDA connects to this Service when it polls the scaler for metrics.

Determine the Scaler Service FQDN

KEDA reaches the scaler through its in-cluster DNS name. The FQDN format is:

<release-name>-kubemq-keda-scaler.<namespace>.svc.cluster.local:9090

For the default install above (release name kubemq-keda-scaler, namespace default), the chart's Service name resolves to:

kubemq-keda-scaler.default.svc.cluster.local:9090

For a Helm install with release name my-release in namespace keda, it would be my-release-kubemq-keda-scaler.keda.svc.cluster.local:9090. You will use this value as the scalerAddress in the next step.

Create a ScaledObject

Define a ScaledObject that targets your queue-consuming Deployment and points the external trigger at both the scaler Service and your KubeMQ broker. This basic example scales my-queue-consumer based on the Waiting count of my-queue, targeting 10 waiting messages per replica:

apiVersion: keda.sh/v1alpha1
kind: ScaledObject
metadata:
  name: kubemq-queue-scaler
spec:
  scaleTargetRef:
    name: my-queue-consumer
  pollingInterval: 15
  cooldownPeriod: 60
  minReplicaCount: 1
  maxReplicaCount: 10
  triggers:
    - type: external
      metadata:
        scalerAddress: kubemq-keda-scaler.default.svc.cluster.local:9090
        kubemqAddress: kubemq.default.svc.cluster.local:50000
        queueName: my-queue
        targetWaiting: "10"

Apply it:

kubectl apply -f scaled-object-basic.yaml

The three required metadata fields are scalerAddress (the scaler Service FQDN from the previous step), kubemqAddress (your broker's host:port), and queueName (the queue channel to monitor). targetWaiting is the target number of waiting messages per replica — KEDA divides the live Waiting count by this value to compute the desired replica count.

Watch It Scale

Send messages to my-queue from any KubeMQ producer and watch KEDA scale the target Deployment up as the Waiting count climbs:

kubectl get hpa -w

KEDA creates a Horizontal Pod Autoscaler behind the scenes; the -w flag streams replica changes live. As the consumer drains the queue and Waiting drops, the deployment scales back down once the cooldownPeriod (60 seconds in this example) has elapsed.

Verify Scaler Health

The scaler exposes a standard gRPC Health service on the same port 9090. Both liveness and readiness probes check the gRPC server's health only — not KubeMQ broker connectivity. To test it manually, port-forward the Service and call the health endpoint with grpcurl:

kubectl port-forward svc/kubemq-keda-scaler 9090:9090

In a second terminal:

grpcurl -plaintext localhost:9090 grpc.health.v1.Health/Check

A healthy scaler responds:

{
  "status": "SERVING"
}