Terminal.skills
Skills/kafka
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kafka

Build event-driven systems with Apache Kafka. Use when a user asks to set up message streaming, implement event sourcing, build pub/sub systems, process real-time data streams, or connect microservices with async messaging.

#kafka#streaming#events#messaging#microservices
terminal-skillsv1.0.0
Works with:claude-codeopenai-codexgemini-clicursor
Source

Usage

$
✓ Installed kafka v1.0.0

Getting Started

  1. Install the skill using the command above
  2. Open your AI coding agent (Claude Code, Codex, Gemini CLI, or Cursor)
  3. Reference the skill in your prompt
  4. The AI will use the skill's capabilities automatically

Example Prompts

  • "Analyze the sales data in revenue.csv and identify trends"
  • "Create a visualization comparing Q1 vs Q2 performance metrics"

Documentation

Overview

Kafka is a distributed event streaming platform for high-throughput, fault-tolerant messaging. It's the backbone of event-driven architectures — used for real-time data pipelines, event sourcing, log aggregation, and microservice communication.

Instructions

Step 1: Local Setup

yaml
# docker-compose.yml — Kafka with KRaft (no ZooKeeper)
services:
  kafka:
    image: bitnami/kafka:latest
    ports:
      - "9092:9092"
    environment:
      KAFKA_CFG_NODE_ID: 1
      KAFKA_CFG_PROCESS_ROLES: broker,controller
      KAFKA_CFG_LISTENERS: PLAINTEXT://:9092,CONTROLLER://:9093
      KAFKA_CFG_ADVERTISED_LISTENERS: PLAINTEXT://localhost:9092
      KAFKA_CFG_CONTROLLER_QUORUM_VOTERS: 1@kafka:9093
      KAFKA_CFG_CONTROLLER_LISTENER_NAMES: CONTROLLER

Step 2: Node.js Producer

typescript
// producer.ts — Send events to Kafka
import { Kafka, Partitioners } from 'kafkajs'

const kafka = new Kafka({ brokers: ['localhost:9092'] })
const producer = kafka.producer({ createPartitioner: Partitioners.DefaultPartitioner })

await producer.connect()

// Send single event
await producer.send({
  topic: 'orders',
  messages: [
    {
      key: 'order-123',                    // partition key (orders for same user go to same partition)
      value: JSON.stringify({
        orderId: 'order-123',
        userId: 'user-456',
        items: [{ sku: 'WIDGET-1', quantity: 2, price: 29.99 }],
        total: 59.98,
        createdAt: new Date().toISOString(),
      }),
    },
  ],
})

// Batch send
await producer.sendBatch({
  topicMessages: [
    { topic: 'orders', messages: events.map(e => ({ key: e.id, value: JSON.stringify(e) })) },
  ],
})

await producer.disconnect()

Step 3: Consumer

typescript
// consumer.ts — Process events from Kafka
const consumer = kafka.consumer({ groupId: 'order-service' })

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(`Processing order ${order.orderId} from partition ${partition}`)

    // Process the order (idempotently — messages can be redelivered)
    await processOrder(order)
  },
})

// Graceful shutdown
process.on('SIGTERM', async () => {
  await consumer.disconnect()
})

Step 4: Python Consumer

python
# consumer.py — Kafka consumer with confluent-kafka
from confluent_kafka import Consumer

conf = {
    'bootstrap.servers': 'localhost:9092',
    'group.id': 'analytics-service',
    'auto.offset.reset': 'earliest',
}

consumer = Consumer(conf)
consumer.subscribe(['orders'])

while True:
    msg = consumer.poll(1.0)
    if msg is None:
        continue
    if msg.error():
        print(f"Error: {msg.error()}")
        continue

    order = json.loads(msg.value().decode('utf-8'))
    print(f"Processing: {order['orderId']}")

Guidelines

  • Use partition keys to ensure related events go to the same partition (ordering guarantee).
  • Consumer groups enable parallel processing — each partition is consumed by one consumer in the group.
  • Make consumers idempotent — Kafka guarantees at-least-once delivery by default.
  • For managed Kafka: Confluent Cloud, AWS MSK, or Redpanda (Kafka-compatible, simpler).
  • KRaft mode (no ZooKeeper) is production-ready since Kafka 3.3+.

Information

Version
1.0.0
Author
terminal-skills
Category
Data & AI
License
Apache-2.0