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Keda External Scaler with ActiveMQ Artemis

This sample has been updated to use KEDA v2 and ActiveMQ Artemis 2.15.0

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This is a demonstration on how to use KEDA's external scaler to monitor ActiveMQ Artemis Queue.

The Keda external scaler calls metrics-provider GRPC server which will collect the metrics from ActiveMQ Artemis.

ActiveMQ Artemis is now included as part of the KEDA internal scaler

Note: use your own docker repository while building the project.

Pre-requisites:

Code organization

Building the metrics provider for external scaler

You can get the proto file from the Keda github.

This project already contains the externalscaler.proto

Use protoc to autogenerate the Proto codes.

protoc -I externalscaler/ externalscaler/proto/externalscaler.proto --go_out=plugins=grpc:externalscaler

Note: We use kaniko in-cluster builder

Setup kaniko registry access secret

kubectl -n artemis create secret generic regcred --from-file $HOME/.docker/config.json

$ skaffold run -p metrics-provider

External Scaler as ActiveMQ Artemis sidecar

The docker image used taken from vromero/activemq-artemis-docker uses the hostname as its broker name, in order to avoid hardcoding the broker name, the metrics provider is deployed as a sidecar to ActiveMQ Artemis.

Added to the file k8s-manifest/artemis/deployment.yaml

  containers:
  - name: artemis-activemq-metrics-provider
    image: docker.io/balchu/artemis-ext-scaler:1.0.0
    args: ["--port","5050","--broker","$(POD_NAME)", "--user", "$(ARTEMIS_USERNAME)","--password","${ARTEMIS_PASSWOORD)"]
    imagePullPolicy: Always
    resources:
      requests:
        cpu: 100m
        memory: 10Mi

Build and deploy the consumer.

Using skaffold and jib, simply execute the command below.

skaffold run -p consumer

Please make sure that you use your docker repository.

Deploy the External Scaler manifest

Now its time to setup the KEDA's external scaler.

kubectl apply -f k8s-manifest/externalscaler_scaledobject.yaml

The file looks like this.

apiVersion: keda.sh/v1alpha1
kind: ScaledObject
metadata:
  name: artemis-scaledobject
  namespace: artemis
spec:
  pollingInterval: 5   # Optional. Default: 30 seconds
  cooldownPeriod: 5  # Optional. Default: 300 seconds
  minReplicaCount: 0   # Optional. Default: 0
  maxReplicaCount: 30  # Optional. Default: 100  
  scaleTargetRef:
    name: artemis-consumer
  triggers:
  - type: external
    metadata:
      scalerAddress: artemis-activemq.artemis:5050
      queueLength: "10"
      brokerAddress: "test"
      queueName: "test"

Where:

Before pumping in messages, check the HPA.

Check the HPA


kubectl -n artemis get hpa
NAME                        REFERENCE                     TARGETS              MINPODS   MAXPODS   REPLICAS   AGE
keda-hpa-artemis-consumer   Deployment/artemis-consumer   <unknown>/20 (avg)   1         30        0          58m

At this point,HPA doesn't have the TargetAverageValue to scale up or down the pods. This can be observed by the <unknown>/20(avg)

Start the producer

The producer is a simple Springboot application.

If you are going to run the Springboot application using your IDE, make sure that you point to the host and port of the ActiveMQ Artemis.

Check the file application.yml

As an example:

spring:
  artemis:
    mode: native
    host: ${ARTEMIS_SERVER_HOST:10.152.183.227}
    port: ${ARTEMIS_SERVER_PORT:61616}
    user: ${ARTEMIS_USERNAME:artemis}
    password: ${ARTEMIS_PASSWORD:artemis}

In the Class App.java

You can modify how much messages you want to send to the broker. In the example below, the program is pushing 10000 messages to the broker, with a delay of 200 milliseonds.

public void run(String... args) throws Exception {
	for (int i = 0; i < 10000; i++){
		producer.send("Message is: " + System.currentTimeMillis());
		sleep(200);
   }
}

Checking the scaling up of the pods.


$ kubectl -n artemis get pods
NAME                                READY   STATUS              RESTARTS   AGE
artemis-activemq-66c66ffdcc-9f7hq   2/2     Running             0          15m
artemis-consumer-589c9b87f7-mldrx   0/1     ContainerCreating   0          4s
artemis-consumer-589c9b87f7-mltqx   1/1     Running             0          14s

Scale to zero

Once you stop the producer program, KEDA will determine that messages are no longer coming and will scale down the pods to zero.

$kubectl -n artemis get pods -w
NAME                                READY   STATUS    RESTARTS   AGE
artemis-activemq-66c66ffdcc-9f7hq   2/2     Running   0          16m
artemis-consumer-589c9b87f7-8xwq6   1/1     Running   0          43s
artemis-consumer-589c9b87f7-k2bf5   1/1     Running   0          12s
artemis-consumer-589c9b87f7-mldrx   1/1     Running   0          58s
artemis-consumer-589c9b87f7-mltqx   1/1     Running   0          68s
artemis-consumer-589c9b87f7-mltqx   1/1     Terminating   0          81s
artemis-consumer-589c9b87f7-8xwq6   1/1     Terminating   0          56s
artemis-consumer-589c9b87f7-mldrx   1/1     Terminating   0          71s
artemis-consumer-589c9b87f7-k2bf5   1/1     Terminating   0          25s
artemis-consumer-589c9b87f7-8xwq6   0/1     Terminating   0          57s
artemis-consumer-589c9b87f7-mldrx   0/1     Terminating   0          72s
artemis-consumer-589c9b87f7-k2bf5   0/1     Terminating   0          27s
artemis-consumer-589c9b87f7-mldrx   0/1     Terminating   0          73s
artemis-consumer-589c9b87f7-mldrx   0/1     Terminating   0          73s
artemis-consumer-589c9b87f7-mltqx   0/1     Terminating   0          83s

Clean up

Delete the consumer

skaffold delete -p consumer

Delete ActiveMQ Artemis and the metrics provider

skaffold delete -p metrics-provider

Delete the External Scaler object

kubectl delete -f k8s-manifest/externalscaler_scaledobject.yaml

Verify that the HPA is successfully deleted

kubectl -n artemis get hpa

License

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