Kafka Consumers

Consumers Overview

Consumers is a building block you will reach for often in Apache Kafka. It keeps related logic together and makes your intent obvious to reviewers and future maintainers.

When you learn consumers properly, you avoid the guesswork that leads to bugs and rework. The example below shows the shape you will use in most real Apache Kafka projects.

import { Kafka } from 'kafkajs';

const kafka = new Kafka({ clientId: 'orders', brokers: ['localhost:9092'] });
const consumer = kafka.consumer({ groupId: 'order-processors' });

await consumer.connect();
await consumer.subscribe({ topic: 'orders', fromBeginning: false });

await consumer.run({
  eachMessage: async ({ topic, partition, message }) => {
    const order = JSON.parse(message.value.toString());
    console.log({ partition, key: message.key?.toString(), order });
  },
});

A consumer joins a group and processes messages from the partitions it is assigned.

Consumers Example

import { Kafka } from 'kafkajs';

const kafka = new Kafka({ clientId: 'app', brokers: ['localhost:9092'] });
const producer = kafka.producer();
const consumer = kafka.consumer({ groupId: 'group' });

• Start from a minimal Consumers example and grow it only as needed.
• Keep configuration explicit so Consumers behaves the same in every environment.
• Name things clearly so teammates understand your Consumers at a glance.
• Add tests around Consumers early to lock in expected behaviour.

Apache Kafka Cheatsheet

Handy KafkaJS reference related to consumers.

How Consumers Works in Apache Kafka

Consumers builds on Kafka's log-based design, where producers append events to partitioned topics and consumer groups read them independently, tracking their own offsets.

A consumer joins a group and processes messages from the partitions it is assigned.

• Topics are split into partitions for parallelism and ordering per key.
• Producers choose a partition, usually by message key.
• Consumer groups share partitions so work scales horizontally.
• Offsets record how far each group has read.

Practical Guidance for Consumers

In production, consumers needs attention to delivery guarantees, retries, and observability. Make handlers idempotent and monitor consumer lag closely.

Common Mistakes

• Skipping error handling and edge cases when wiring up consumers.
• Leaving consumers untested, so regressions slip into production.
• Over-engineering consumers before you actually need the extra flexibility.
• Ignoring documentation, which makes consumers hard for the next developer to change.

Key Takeaways

• Consumers is a core part of working effectively with Apache Kafka.
• Start small and keep consumers focused on a single responsibility.
• Apply consistent patterns so consumers scales across your project.
• Test and document consumers to keep it maintainable over time.