Apache Kafka: Real-Time Distributed Streaming Platform

Programming & Development / April 12, 2025

Apache Kafka: Real-Time Distributed Streaming Platform

Apache Kafka real-time data streaming distributed systems event streaming publish-subscribe Kafka architecture Kafka components Kafka ecosystem stream processing Kafka Connect Kafka Streams Zookeeper message broker high throughput fault tolerance scalability microservices log aggregation event sourcing IoT data big data pipelines Kafka tutorial

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📊 Slide 1: Introduction

What is Apache Kafka?

A distributed streaming platform.
Designed for high-throughput, fault-tolerant, real-time data feeds.
Works on a publish-subscribe messaging model.

🔑 Slide 2: Key Features

High Throughput: Handle millions of messages/sec.
Fault Tolerant: Data replication for high availability.
Durable: Persist data on disk with configurable retention.
Scalable: Horizontally scalable with minimal effort.
Distributed: Built for distributed, multi-node deployments.

🏗️ Slide 3: Kafka Architecture

Core Components:

Producer: Sends messages to Kafka.
Topics: Logical channels to organize messages.
Broker: Kafka server that stores messages.
Consumer: Reads messages from topics.
Zookeeper: Coordinates brokers and clusters.

🧩 Slide 4: Kafka Ecosystem

Kafka Connect: Integrate Kafka with external systems (DBs, APIs, etc.).
Kafka Streams: Lightweight library for processing Kafka data.
Kafka REST Proxy: Enables HTTP access to Kafka.
Schema Registry: Manages Avro schema versioning and evolution.

⚙️ Slide 5: Common Use Cases

Real-time Analytics: Stream processing and dashboards.
Log Aggregation: Collect logs across systems.
Event Sourcing: Track all changes as events.
IoT Data Pipelines: Handle real-time sensor data.
Messaging Backbone: Microservices communication.

🚀 Slide 6: Getting Started with Kafka

Install Kafka: Download from kafka.apache.org.
Start Zookeeper (required for coordination).
Start Kafka Broker.
Create Topics: kafka-topics.sh command.
Produce/Consume: Use CLI or write producer & consumer apps.

✅ Slide 7: Advantages

Open-source and community-driven.
Integrates with big data tools: Hadoop, Spark, Flink, etc.
Robust for mission-critical production environments.
Flexible: Supports Java, Python, Go, and more.

🧠 Slide 8: Conclusion

Apache Kafka is a powerful platform for building real-time data pipelines and streaming apps.

It plays a vital role in modern event-driven architectures and large-scale data systems.

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