Skip to content

Latest commit

 

History

History
60 lines (42 loc) · 3.79 KB

README.MD

File metadata and controls

60 lines (42 loc) · 3.79 KB
Raw

KEDA Demo With Kafka Trigger

This repo contains everything to create a demo where you can scale Kafka consumers depending on the queue size on a Kafka Topic from scratch.

Prerequisites

  • A working Kubernetes cluster with enough resources
  • Helm for easy deployment of KEDA. KEDA offers different deployment options, so if you do not prefer Helm option, it can be istalled via Operator Hub or directly using Yaml files.

This demo leverages Strimzi's Kafka Operator to run Kafka on Kubernetes.

This demo uses kafka-producer and kafka-consumer images to interact with Kafka. The code for both images can be found here.

Deployment

Follow the steps below to install the demo from scratch.

Strimzi Kafka Operator Deployment

You can run install-strimzi.sh file, or copy and paste commands in the exact order to your terminal in order to install Smrimzi Kafka operator and deploy a single-broker and single-zookeeper Kafka cluster. The cluster definition is a copy of Strimzi's own example with a tweak that won't allow auto topic creation. This is to prevent the producer from creating topics automatically, which creates topic with 1 partition and 1 replica by default. This in turn makes more than 1 consumers useless, and the whole demo becomes pointless. When the cluster is in Ready state, you can create the topic by applying topic.yaml file.

kubectl apply -f topic.yaml

KEDA Operator Deployment

You can run install-keda.sh file, file, or copy and paste commands in the exact order to your terminal in order to install KEDA operator. If you prefer other deployment options than Helm, you can follow instructions here.

Kafka Producer Deployment

Kafka producer used in this demo exposes a web interface to interact with the end user. User can make requests to this endpoint to make producer produce messages on the topic a total number as a given URL parameter.

You can change the exposed port, Kafka Bootstrap address and Topic name using Env variables.

You can create a producer deployment and expose it using a LoadBalancer service. If you prefer you can use port-forwarding instead of a LoadBalancer service.

kubectl apply -f producer-deployment.yaml
kubectl apply -f producer-svc.yaml

Kafka Consumer Deployment

Kafka consumer used in this demo leverages Consumer Group feature of Kafka. This allows Kafka to accept these consumers as dynamic consumers and dynamically assign partitions to these consumers.

You can change the Consumer Group, Sleep Duration, Kafka Bootstrap address and Topic name values using Env variables.

kubectl apply -f consumer-deployment.yaml

ScaledObject

In order to autoscale our consumer deployment using KEDA depending on the queued message count on the Kafka Topic, we should create an object of type scaledobjects.keda.sh. When there are more than 5 messages in keda-topic topic, it will scale up the target object, which is the kafka-consumer deployment.

kubectl apply -f scaled-object.yaml

Trying out

You can make requests to the Kafka Producer's endpoint including the message count you want it to produce to Kafka topic. Because the consumers sleep between consuming each message, there'll be a congestion on the topic and KEDA will scale up the consumer deployment.

curl http://<EXTERNAL-IP-OF-PRODUCER-SVC>?count=100