KAFKA-NODE: manage multiple consumer groups - node.js

Question

I have a question about managing multiple CG's, created three consumer groups, every CG has its own kafka service, group Id and topic.
now i'm receiving messages as expected, but, i wondering if its possible to create next scenario:
create three consumer groups, but receive messages only from one,put others on pause/hold for now, if his kafka service will fall, consume messages from next consumer group, and same with the third.
Here's an example for my code:
function createConsumerGroup(topics){
const ConsumerGroup = kafka.ConsumerGroup;
//CREATE CONSUMER GROUPS FOR EVERY SERVICE
for(let i = 0; i < config.kafka_service.length ;i++){ //3
const options = {
groupId: config.kafka_service[i]['groupId'],
host: config.kafka_service[i]['zookeeperHost'],
kafkaHost: config.kafka_service[i]['kafkaHost'],
sessionTimeout: 15000,
protocol: ['roundrobin'],
fromOffset: 'latest'
}
//assign all services CG names and create [i] consumer groups!
let customConsumerGroupName = config.kafka_service[i]['consumerGroupName'];
customConsumerGroupName = new ConsumerGroup(options, topics);
customConsumerGroupName.on('connect', (resp) => {
console.log(`${config.kafka_service[i]['consumerGroupName']} is connected!`);
});
if(i > 0){
//pause consumers exept FIRST
customConsumerGroupName.pause();
}
customConsumerGroupName.on('message', (message) => {
console.log(message);
});
customConsumerGroupName.on('error', (error) => {
console.log('consumer group error: ', error);
//HERE I NEED TO CALL SECOND CONSUMER TO STEP UP
//MAYBE consumerGroup.resume(); ???
});
}
}
hopes its sound understandable, thanks :)

Answer 1

So it looks like the confusion arises because of the name of the Node package's 'ConsumerGroup'. In Kafka terms, the consumer group is controlled solely by the groupId used by each consumer. Consumers with the same groupId will not be given duplicate messages, each topic message is only read by a single consumer. If a consumer goes down, kafka detects this and gives it's partitions to a separate consumer.
The Node 'ConsumerGroup' is really just another Kafka consumer (the new Consumer with groups managed by Kafka rather than zookeeper as of Kafka >0.9).
So the way to leverage a kafka consumer group with the Node ConsumerGroup would be as follows:
function createConsumerGroup(topics){
const ConsumerGroup = kafka.ConsumerGroup;
//CREATE CONSUMER GROUPS FOR EVERY SERVICE
for(let i = 0; i < config.kafka_service.length ;i++){ //3
const options = {
groupId: 'SOME_GROUP_NAME',
host: config.kafka_service[i]['zookeeperHost'],
kafkaHost: config.kafka_service[i]['kafkaHost'],
sessionTimeout: 15000,
protocol: ['roundrobin'],
fromOffset: 'latest'
}
//assign all services CG names and create [i] consumer groups!
let customConsumerGroupName = config.kafka_service[i]['consumerGroupName'];
customConsumerGroupName = new ConsumerGroup(options, topics);
customConsumerGroupName.on('connect', (resp) => {
console.log(`${config.kafka_service[i]['consumerGroupName']} is connected!`);
});
customConsumerGroupName.on('message', (message) => {
console.log(message);
});
customConsumerGroupName.on('error', (error) => {
console.log('consumer group error: ', error);
//Error handling logic here, restart the consumer that failed perhaps?
//Depends on how you want to managed failed consumers.
});
}
}
Each instance of Nodes ConsumerGroup will be a member of the group 'SOME_GROUP_NAME', and any other consumers created with that same groupId will also act as members of the same kafka consumer group, regardless of server, etc.

Answer 2

Consumer groups solve two central scenarios:
1. Scaling
You can increase the number of consumers in a group to handle an increasing rate of messages being produced in the topic(s) the group is consuming (scaling out)
2. Failover
By having a group of consumers reading the same topic(s), they will automatically handle the situation where one or more consumer(s) go down.
So, instead of having "stand-by" consumer groups, where you have to handle which ones are active yourself, you just rely on Kafka's built-in failover. Consumers can run in several different containers (even in different data centers), and Kafka will automatically make sure that messages are delivered to the individual consumers, no matter where they are or how many of them are running at any given time.