Kafka Tutorial - Comprehensive Guide 2025

🚀 Kafka Tutorial 2025 - What’s New

Major Updates in This Edition

• KRaft Mode Complete - No more ZooKeeper dependency
• Cloud-Native First - Kubernetes and managed services focus
• AI/ML Integration - Streaming data for machine learning
• Real-Time Analytics - Modern streaming architectures
• Enhanced Security - Zero-trust and encryption by default
• Production Ready - Battle-tested patterns and practices

Kafka Evolution Since 2017

• ✅ Simplified Operations - KRaft eliminates ZooKeeper complexity
• ✅ Better Performance - 10x improvement in metadata operations
• ✅ Cloud Integration - Native support for cloud services
• ✅ Developer Experience - Modern APIs and tooling

Complete Kafka Tutorial Series

This comprehensive Kafka tutorial covers Kafka 4.0 architecture and design with modern best practices. The tutorial includes production-ready Java examples for Kafka producers and consumers, advanced streaming patterns, and cloud-native deployments.

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Kafka Broker Startup Scripts and Configuration - 2025 Edition

🚀 What’s New in This 2025 Update

Major Updates and Changes

• KRaft Mode by Default - No ZooKeeper required
• Container-First Approach - Docker and Kubernetes native
• Dynamic Configuration - Minimal restarts needed
• Automated Management - Operators handle lifecycle
• Enhanced Monitoring - Built-in observability
• Cloud-Native Patterns - Auto-scaling and self-healing

Broker Startup Evolution Since 2017

• ✅ No ZooKeeper - KRaft provides native consensus
• ✅ Declarative Config - GitOps and Infrastructure as Code
• ✅ Container Ready - Optimized for Kubernetes
• ✅ Zero-Downtime - Rolling updates standard

Running a Kafka Broker in 2025

Starting Kafka brokers has evolved significantly with KRaft mode and cloud-native practices. This guide covers modern approaches from simple local development to production Kubernetes deployments.

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Kafka vs. JMS, RabbitMQ, SQS, and Modern Messaging - 2025 Edition

🚀 What’s New in This 2025 Update

Major Updates and Changes

• Kafka Beyond Messaging - Complete event streaming platform
• Cloud-Native First - Managed services dominate deployments
• KRaft Mode - ZooKeeper completely eliminated
• Performance Gap Widened - Kafka processes millions/sec
• Cost Models Evolved - Consumption-based pricing prevalent
• New Competitors - Pulsar, Redpanda, WarpStream emerging

Industry Shifts Since 2017

• ✅ Event Streaming Standard - Kafka dominates real-time data
• ✅ Serverless Integration - Native cloud functions support
• ✅ Multi-Protocol Support - Beyond just publish-subscribe
• ✅ Managed Services - Self-hosting becoming rare

Ready to understand how Kafka compares to modern messaging systems? Let’s explore when to use each technology in today’s architectures.

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Introduction to Apache Kafka - 2025 Edition

🚀 What’s New in This 2025 Update

Major Updates and Changes

• Kafka 4.0 with KRaft - ZooKeeper completely eliminated
• Cloud-Native Default - Managed services dominate deployments
• 200+ Connectors - Massive ecosystem expansion
• AI/ML Integration - Direct streaming to ML pipelines
• Simplified Operations - Automated scaling and management
• Enterprise Adoption - Used across all industries

Industry Evolution

• ✅ Event Streaming Standard - De facto platform for real-time data
• ✅ Managed Services - AWS MSK, Confluent Cloud mainstream
• ✅ Kubernetes Native - Operators and serverless integration
• ✅ Global Scale - Petabyte deployments common

Ready to understand why Kafka powers the world’s data infrastructure? Let’s explore the streaming platform that processes trillions of events daily.

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The Kafka Ecosystem - Kafka Core, Streams, Connect, ksqlDB, and Schema Registry - 2025 Edition

🚀 What’s New in This 2025 Update

Major Updates and Changes

• Cloud-Native First - Fully integrated with Kubernetes and serverless
• AI/ML Integration - Direct pipelines to machine learning frameworks
• 200+ Connectors - Massive expansion of Kafka Connect ecosystem
• ksqlDB Maturity - Production-ready SQL streaming at scale
• Automated Operations - Self-healing, auto-scaling ecosystem
• Enhanced Security - Zero-trust architecture support

Deprecated Features

• ❌ Standalone REST Proxy - Replaced by API gateways
• ❌ Manual deployments - Cloud-native automation standard
• ❌ Legacy monitoring - Unified observability platforms
• ❌ Custom integration scripts - Managed connectors preferred

Ready to explore the complete Kafka ecosystem? Let’s discover how each component transforms streaming data into business value.

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Kafka Architecture: Low Level - 2025 Edition

🚀 What’s New in This 2025 Update

Major Updates and Changes

• KRaft-Only Architecture - ZooKeeper completely eliminated
• Raft Consensus Replication - Native leadership election
• Java 17 Requirement - Modern JVM optimizations
• Protocol Cleanup - Removed pre-0.10.x formats
• Dynamic KRaft Quorums - Add/remove controllers without downtime
• Improved Atomic Writes - Enhanced exactly-once semantics

Deprecated Features

• ❌ ZooKeeper coordination - Fully removed
• ❌ Java 8 support - Minimum Java 11/17
• ❌ Legacy wire protocols - Pre-0.10.x formats gone
• ❌ Old replication mechanisms - Replaced by Raft

Ready to understand how Kafka achieves its legendary performance? Let’s dive deep into the engineering decisions that make Kafka the backbone of modern data infrastructure.

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Kafka Architecture: Log Compaction - 2025 Edition

🚀 What’s New in This 2025 Update

Major Updates and Changes

• KRaft-Managed Compaction - All compaction under KRaft control
• Tiered Storage Integration - Compaction across local and remote tiers
• Diskless Topics - Object storage compaction (KIP-1165)
• Performance Optimizations - Reduced I/O with cloud-native design
• Simplified Operations - No ZooKeeper coordination needed
• Enhanced Monitoring - Better visibility into compaction progress

Deprecated Features

• ❌ ZooKeeper-based coordination - Fully removed
• ❌ Legacy message formats - v0 and v1 no longer supported
• ❌ Old compaction metrics - Updated for KRaft

Ready to master Kafka’s powerful state management feature? Let’s explore how log compaction enables event sourcing and stateful processing at scale.

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Kafka Topic Architecture - 2025 Edition

🚀 What’s New in This 2025 Update

Major Updates and Changes

• KRaft-Based Metadata Management - Direct partition control without ZooKeeper
• Raft Consensus for Leader Election - Deterministic, fast failover
• Enhanced ISR Management - Real-time replica state tracking
• Faster Topic Operations - Reduced metadata propagation delays
• Improved Partition Assignment - Efficient rebalancing strategies
• Centralized Controller - Single source of truth for metadata

Deprecated Features

• ❌ ZooKeeper-based leader election - Replaced by Raft
• ❌ Legacy metadata management - KRaft is mandatory
• ❌ Old partition reassignment tools - Updated for KRaft

Ready to master the backbone of Kafka’s scalability? Let’s explore how topics and partitions power distributed streaming.

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Kafka Architecture: Producers - 2025 Edition

🚀 What’s New in This 2025 Update

Major Updates and Changes

• Metadata Bootstrapping - KIP-1102 enables automatic metadata recovery
• Enhanced Protocol Resilience - Improved error handling and recovery
• Mandatory Modern Protocols - Requires broker 2.1+ for Java clients
• KRaft Performance Benefits - Reduced latency with ZooKeeper removal
• Strengthened Best Practices - Focus on idempotency and transactions
• Clear Upgrade Path - KIP-1124 migration guidance

Deprecated Features

• ❌ Pre-2.1 protocol versions - Old client protocols removed
• ❌ Legacy compatibility modes - Modern protocols required
• ❌ ZooKeeper-based metadata - Replaced by KRaft

Ready to build high-performance, resilient producers? Let’s master Kafka producer architecture in the modern era.

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Kafka Architecture: Consumers - 2025 Edition

🚀 What’s New in This 2025 Update

Major Updates and Changes

• KIP-848 Protocol - Revolutionary consumer rebalancing without global pauses
• Elimination of Rebalance Downtime - Consumers continue processing during rebalances
• Queue Semantics - Native point-to-point messaging (early access)
• KRaft-Based Coordination - Simplified group management without ZooKeeper
• Metadata Rebootstrap - Automatic recovery from metadata failures
• Enhanced Scalability - Support for larger consumer groups

Deprecated Features

• ❌ ZooKeeper-based coordination - Completely removed
• ❌ Legacy rebalance protocols - Replaced by KIP-848
• ❌ Pre-2.1 client protocols - No longer supported
• ❌ Old consumer group management tools - Updated for KRaft

Ready to build resilient, high-performance consumer applications? Let’s explore how Kafka 4.0 revolutionizes consumer architecture.

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Kafka Architecture - 2025 Edition

🚀 What’s New in This 2025 Update

Major Updates and Changes

• Kafka 4.0.0 Architecture - Complete removal of ZooKeeper dependency
• KRaft Mode - Kafka’s native consensus protocol now mandatory
• Performance Enhancements - Faster rebalancing and failover
• New Consumer Group Protocol - KIP-848 as default
• Cloud-Native Features - Docker images and BYOC support
• Java Requirements - Java 17 for brokers, Java 11+ for clients

Deprecated Features

• ❌ ZooKeeper - Completely removed in Kafka 4.0.0
• ❌ Legacy Wire Formats - Pre-0.10.x formats no longer supported
• ❌ Java 8 - No longer supported
• ❌ –zookeeper CLI flags - Removed from all admin tools

Ready to master Apache Kafka’s revolutionary architecture? Let’s dive into the distributed streaming platform that powers real-time data at scale.

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Kafka Tutorial

Kafka Tutorial

This comprehensive Kafka tutorial covers Kafka architecture and design. The Kafka tutorial has example Java Kafka producers and Kafka consumers. The Kafka tutorial also covers Avro and Schema Registry.

• Kafka Tutorial Part 1: What is Kafka?
• [Kafka Tutorial Part 2: Kafka Architecture](https://cloudurable.com/blog/kafka-architecture/index.html “This Kafka tutorial discusses the structure of Kafka. Kafka consists of Records, Topics, Consumers, Producers, Brokers, Logs, Partitions, and Clusters. Records can have key, value and timestamp. Kafka Records are immutable. A Kafka Topic is a stream of records - “/orders”, “/user-signups”. You can think of a Topic as a feed name. It covers the structure of and purpose of topics, log, partition, segments, brokers, producers, and consumers”)
• Kafka Tutorial Part 3: Kafka Topic Architecture
• Kafka Tutorial Part 4: Kafka Consumer Architecture
• Kafka Tutorial Part 5: Kafka Producer Architecture
• Kafka Tutorial Part 6: Using Kafka from the command line
• Kafka Tutorial Part 7: Kafka Broker Failover and Consumer Failover
• Kafka Tutorial Part 8: Kafka Ecosystem
• Kafka Tutorial Part 9: Kafka Low-Level Design
• Kafka Tutorial Part 10: Kafka Log Compaction Architecture
• Kafka Tutorial Part 11: Writing a Kafka Producer example in Java
• Kafka Tutorial Part 12: Writing a Kafka Consumer example in Java
• Kafka Tutorial Part 13: Writing Advanced Kafka Producer with Java examples
• Kafka Tutorial Part 14: Writing Advanced Kafka Consumer with Java examples
• Kafka Tutorial Part 15: Kafka and Avro
• Kafka Tutorial Part 16: Kafka and Schema Registry
• Kafka Tutorial

Kafka Training - Onsite, Instructor-led

Training for DevOps, Architects and Developers

This Kafka course teaches the basics of the Apache Kafka distributed streaming platform. The Apache Kafka distributed streaming platform is one of the most powerful and widely used reliable streaming platforms. Kafka is a fault tolerant, highly scalable and used for log aggregation, stream processing, event sources and commit logs. Kafka is used by LinkedIn, Yahoo, Twitter, Square, Uber, Box, PayPal, Etsy and more to enable stream processing, online messaging, facilitate in-memory computing by providing a distributed commit log, data collection for big data and so much more.

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Kafka Architecture: Log Compaction

Kafka Architecture: Log Compaction

This post really picks off from our series on Kafka architecture which includes Kafka topics architecture, Kafka producer architecture, Kafka consumer architecture and Kafka ecosystem architecture.

This article is heavily inspired by the Kafka section on design around log compaction. You can think of it as the cliff notes about Kafka design around log compaction.

Kafka can delete older records based on time or size of a log. Kafka also supports log compaction for record key compaction. Log compaction means that Kafka will keep the latest version of a record and delete the older versions during a log compaction.

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Kafka Architecture: Low Level

If you are not sure what Kafka is, see What is Kafka?.

Kafka Architecture: Low-Level Design

This post really picks off from our series on Kafka architecture which includes Kafka topics architecture, Kafka producer architecture, Kafka consumer architecture and Kafka ecosystem architecture.

This article is heavily inspired by the Kafka section on design. You can think of it as the cliff notes.

Kafka Design Motivation

LinkedIn engineering built Kafka to support real-time analytics. Kafka was designed to feed analytics system that did real-time processing of streams. LinkedIn developed Kafka as a unified platform for real-time handling of streaming data feeds. The goal behind Kafka, build a high-throughput streaming data platform that supports high-volume event streams like log aggregation, user activity, etc.

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Kafka Architecture: Consumers

Kafka Consumer Architecture - Consumer Groups and subscriptions

This article covers some lower level details of Kafka consumer architecture. It is a continuation of the Kafka Architecture, Kafka Topic Architecture, and Kafka Producer Architecture articles.

This article covers Kafka Consumer Architecture with a discussion consumer groups and how record processing is shared among a consumer group as well as failover for Kafka consumers.

Cloudurable provides Kafka training, Kafka consulting, Kafka support and helps setting up Kafka clusters in AWS.

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Kafka Architecture: Producers

Kafka Producer Architecture - Picking the partition of records

This article covers some lower level details of Kafka producer architecture. It is a continuation of the Kafka Architecture and Kafka Topic Architecture articles.

This article covers Kafka Producer Architecture with a discussion of how a partition is chosen, producer cadence, and partitioning strategies.

Kafka Producers

Kafka producers send records to topics. The records are sometimes referred to as messages.
The producer picks which partition to send a record to per topic. The producer can send records round-robin. The producer could implement priority systems based on sending records to certain partitions based on the priority of the record.

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Kafka Topic Architecture

Kafka Topic Architecture - Replication, Failover and Parallel Processing

This article covers some lower level details of Kafka topic architecture. It is a continuation of the Kafka Architecture article.

This article covers Kafka Topic’s Architecture with a discussion of how partitions are used for fail-over and parallel processing.

Kafka Topics, Logs, Partitions

Recall that a Kafka topic is a named stream of records. Kafka stores topics in logs. A topic log is broken up into partitions. Kafka spreads log’s partitions across multiple servers or disks. Think of a topic as a category, stream name or feed.

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Kafka vs. JMS

Kafka vs JMS, SQS, RabbitMQ Messaging

Is Kafka a queue or a publish and subscribe system? Yes. It can be both.

Kafka is like a queue for consumer groups, which we cover later. Basically, Kafka is a queue system per consumer group so it can do load balancing like JMS, RabbitMQ, etc.

Kafka is like topics in JMS, RabbitMQ, and other MOM systems for multiple consumer groups. Kafka has topics and producers publish to the topics and the subscribers (Consumer Groups) read from the topics.

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Kafka Architecture

If you are not sure what Kafka is, see What is Kafka?.

Kafka Architecture

Kafka consists of Records, Topics, Consumers, Producers, Brokers, Logs, Partitions, and Clusters. Records can have key (optional), value and timestamp. Kafka Records are immutable. A Kafka Topic is a stream of records ("/orders", "/user-signups"). You can think of a Topic as a feed name. A topic has a Log which is the topic’s storage on disk. A Topic Log is broken up into partitions and segments. The Kafka Producer API is used to produce streams of data records. The Kafka Consumer API is used to consume a stream of records from Kafka. A Broker is a Kafka server that runs in a Kafka Cluster. Kafka Brokers form a cluster. The Kafka Cluster consists of many Kafka Brokers on many servers. Broker sometimes refer to more of a logical system or as Kafka as a whole.

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The Kafka Ecosystem - Kafka Core, Kafka Streams, Kafka Connect, Kafka REST Proxy, and the Schema Registry

The Kafka Ecosystem - Kafka Core, Kafka Streams, Kafka Connect, Kafka REST Proxy, and the Schema Registry

The core of Kafka is the brokers, topics, logs, partitions, and cluster. The core also consists of related tools like MirrorMaker. The aforementioned is Kafka as it exists in Apache.

The Kafka ecosystem consists of Kafka Core, Kafka Streams, Kafka Connect, Kafka REST Proxy, and the Schema Registry. Most of the additional pieces of the Kafka ecosystem comes from Confluent and is not part of Apache.

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