Apache Kafka for Data Engineers Full Course 2026 | Basics to Advanced

Video Description

Apache Kafka sits at the center of almost every modern data platform — yet most people only learn how to use Kafka, not how Kafka actually behaves in production. This full-length Apache Kafka for Data Engineers masterclass (2026) is designed to fix that. This is not a surface-level tutorial. This is a complete, end-to-end Kafka course built specifically for real data engineering pipelines, operational systems, and production realities. You’ll learn Kafka from first principles — brokers, partitions, offsets, consumer groups — all the way to stream processing, data integration, monitoring, scaling, and security. Every concept is explained clearly, demonstrated practically, and connected to how Kafka is used in real-world data engineering architectures. 🚀 What You’ll Learn in This Kafka Masterclass In this complete Apache Kafka course, you’ll learn: • How Kafka actually works internally (brokers, partitions, leaders, offsets) • Producers, consumers, and consumer groups — deeply and correctly • Kafka CLI tools and why they matter in real debugging • Topic design, partitioning strategies, and ordering guarantees • Offset management and replay semantics • Kafka Streams — embedded stream processing inside applications • Kafka Connect — ingestion and egress without custom code • Change Data Capture (CDC) concepts and pipelines • Monitoring Kafka and interpreting consumer lag correctly • Scaling Kafka: partitions vs brokers (and common mistakes) • Handling backpressure and traffic spikes • Kafka security fundamentals (SSL, SASL, ACLs) • Kafka’s role in real data engineering pipelines • Kafka with Airflow, Spark, and data warehouses • Production rules, failure scenarios, and operational realities All concepts are demonstrated with labs, real commands, and real behavior — not slides or toy examples. 🧪 Hands-On Labs (Not Just Theory) Wherever Kafka concepts only make sense in action, we work through labs together: • Producing and consuming data manually • Observing offsets and consumer lag • Breaking things intentionally and fixing them • Understanding Kafka behavior under load • Watching how rebalancing, lag, and replay actually work You can run everything in parallel with the video. 📘 Structured Study Material: https://1drv.ms/w/c/528673ccd24bac3c/IQAWORQnuZtUTKnXQXxcHNyrAff2rUwM8Dpo0eF80gsIpdY?e=vC9J8s • Use for revision weeks or months later • Quickly reference specific Kafka concepts • Revisit operational rules and mental models • Use as long-term Kafka documentation This is designed to replace rewatching entire videos just to recall one concept. 🧰 Tech Stack & Tools Used Apache Kafka Kafka CLI Tools Docker (for local setups) 🎯 Who This Course Is For This course is ideal if you are: • A data engineer working with Kafka or about to • A backend engineer dealing with event-driven systems • Preparing for Kafka-related interviews • Tired of shallow Kafka explanations • Looking to understand Kafka beyond APIs and frameworks Beginner-friendly — but not dumbed down. 📌 Tools Links: Docker: https://www.docker.com/products/docker-desktop/ VS Code: https://code.visualstudio.com/ 📂 Resources & Code https://github.com/Jay61616/kafka-masterclass 🕒 Timestamps 0:00 intro 1:07 curriculum intro ​PHASE 0 — FOUNDATIONS 6:32 0.1 Event-Driven Architecture (EDA) 42:15 0.2 Streaming vs Batch Processing PHASE 1 — INSTALLATION 1:16:41 1.1 Why Docker for Kafka? 1:36:36 1.2 Why KRaft and not ZooKeeper? 2:05:24 1.3 Kafka Installation with Docker + KRaft PHASE 2 — KAFKA CORE CONCEPTS 2:56:55 2.1 What is Apache Kafka? 3:25:32 2.2 Kafka vs Traditional Message Queues 3:55:38 2.3 Topics 4:26:09 2.4 Partitions 4:56:46 2.5 Offsets 5:23:23 2.6 Producers 5:52:43 2.7 Consumers 6:12:41 2.8 Consumer Groups 6:36:32 2.9 Internal Components PHASE 3 — WORKING WITH KAFKA (CORE) 6:54:03 3.1 Kafka CLI Tools 7:03:07 3.2 Message Keys 7:21:56 3.3 Serialization PHASE 4 — RELIABILITY & GUARANTEES 7:37:59 4.1 Consumer Commits 7:54:34 4.2 Idempotent Producers 8:05:49 4.3 Delivery Semantics PHASE 5 — ADVANCED KAFKA 8:26:56 5.1 Retention Policies 8:38:16 5.2 Log Compaction 8:39:10 5.3 Kafka Streams (Intro) 8:42:09 5.4 Kafka Connect PHASE 6 — OPERATIONS & PRODUCTION 8:45:39 6.1 Scaling Kafka 8:48:45 6.2 Monitoring & Lag 8:51:48 6.3 Kafka in Real Data Engineering Pipelines 📣 Let’s Connect LinkedIn: https://linkedin.com/in/jayachandrakadiveti GitHub: https://github.com/Jay61616 Website: https://jay.unaux.com 🎯 Hashtags #ApacheKafka #KafkaForDataEngineers #DataEngineering #KafkaTutorial #KafkaCourse #EventStreaming #StreamingData #BigData #ETLPipelines #RealTimeData #KafkaStreams #KafkaConnect