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Kafka Real-World Use Cases

This is a concept-oriented course where you learn 'when and why to stream events' rather than just memorizing Kafka syntax. Using a single shopping mall project, 'On-Market,' as a comprehensive case study, you will master the event flows and principles of 10 real-world scenarios—including orders, inventory, notifications, search, and analytics. You will develop the ability to see the entire system, covering everything from topics, partitions, and consumer groups to event sourcing, CQRS, and idempotency.

33 learners are taking this course

Level Intermediate

Course period Unlimited

Spring Boot
Spring Boot
Reactive Programming
Reactive Programming
Kafka
Kafka
MSA
MSA
Celery
Celery
Spring Boot
Spring Boot
Reactive Programming
Reactive Programming
Kafka
Kafka
MSA
MSA
Celery
Celery

What you will gain after the course

  • Explain core Kafka concepts (Topics, Partitions, Offsets, Consumer Groups) using diagrams and understand the operating principles of event-driven architecture.

  • The ability to design event flows and determine application strategies for practical cases across 10 domains, including ordering, inventory, notifications, search, and analytics.

  • Establishing reliability strategies for the operational phase, including event sourcing, CQRS, idempotency, DLT, and schema management.

🤔 Has this ever happened to you?

You just pressed a single order button, but behind the scenes, payment, inventory, shipping, points, and notifications all need to wake up one after another. The familiar way is for the order service to directly call these six things in sequence. However, if the notification service slows down, the entire order grinds to a halt, and if the point service briefly goes down, an order that has already completed payment ends up as a failure. Every time a new feature is added, that method grows one line longer and becomes one line more precarious.

"They say you should use Kafka..." but when you actually open an example, you're flooded with terms like topics, partitions, offsets, and consumer groups, and where and why you should use it in your own system remains a mystery. This course was created specifically to clear that fog.

📌 First, let's clarify the nature of this course

This course is a lecture that explains concepts and principles. It is not a hands-on practice style where you follow along with code line by line.

Now that AI coding has become commonplace, understanding the concepts that penetrate the entire system and technology has become much more important than detailed coding methods. A true skill is the 'sense to judge when and how to use it' rather than just 'knowing how to use' Kafka.

Therefore, this course provides course materials and explains concepts step-by-step using slide images based on those materials. Code examples are presented together as a basis for understanding "why this code is structured this way."

✨ Why this course is special

🗺️ 1. Covering 10 different cases through a single comprehensive project, 'OnMarket'

This is not a collection of scattered examples. Starting from a typical monolithic shopping mall, OnMarket, we will add one case study per lecture to grow it into an event-driven system. From ordering and payment to inventory event sourcing, asynchronous communication, notifications, search indexing, behavioral analysis, log collection, data pipelines, financial anomaly detection, and IoT—the domains are all different, but if you peel back one layer, the same patterns repeat every time. That big picture will naturally stay with you.

🎯 2. Covers the entire lifecycle, from concept to operation

It doesn't end at just "how to build." From reliability design such as idempotency, retries, DLT (Dead Letter Topic), and outbox, to performance and scaling by increasing throughput with JSON/Avro, schema compatibility, partitions, and consumer groups, and even testing using EmbeddedKafka and Testcontainers — we organize the operational sense you must have before heading into practice at a conceptual level.

🃏 3. We even tell you "when not to use it"

This is the real cheat code of this lecture. There are many Kafka courses, but few honestly point out at the end that "Kafka is overkill for this." For simple request-responses, small message volumes, or small services, lighter tools are actually better. The criterion for a good engineer is not 'can I use it,' but 'is the benefit greater than the operational cost?' — I will provide you with this balanced perspective to prevent over-engineering.

🧭 4. All cases converge into a single principle

There is one sentence that runs through all 20 lectures.

"Don't call it directly; let the events flow."

Even with ten different cases, there is only one principle — 'Publish the fact that something happened, and let those who need it subscribe and take it.' Once this mindset becomes second nature, you won't be shaken even when facing an unfamiliar domain.

🎓 What you will be able to do after completing this course

  • You can explain why Kafka is a 'central event highway' rather than a simple message queue through log retention and multiple subscriptions.

  • You can explain the relationships between topics, partitions, offsets, producers, consumers, and consumer groups by drawing them in a diagram.

  • You can draw the event flows for 10 different cases by yourself, including orders, inventory, notifications, search, analytics, finance, and IoT.

  • You can distinguish why event sourcing, CQRS, projection, and replay are necessary and when to use them.

  • Establish a big picture of operational reliability, including idempotency, retries, DLT, schema compatibility, and scaling.

  • Above all, you will be able to judge whether "Kafka is overkill or appropriate for this situation" based on solid reasoning.

👥 Recommended for these people

⭐ This is best suited for these people

  • Backend developers who have the basics of Java and Spring Boot but feel uncertain about where and why to use Kafka

  • Developers who want to establish a conceptual roadmap first before moving on to Event-Driven Architecture (EDA) or MSA

This is also useful for these people

  • Practitioners who have used Kafka fragmentarily but feel they lack the overall picture and operational perspective

  • Tech leads and architects who need to decide whether to adopt it or not

Prerequisite Knowledge

  • A basic understanding of Java syntax and Spring Boot application structure is sufficient.

  • Prior knowledge of Kafka is not required. We will build the concepts together from the ground up.

🚀 In Closing

Kafka is a tool that is as demanding in operational costs as it is powerful. That is why, even more than syntax, you first need judgment. By the end of this course, you will possess not just a few Kafka commands, but a single question that you can pose to any system.

"What happened here,
and who needs to be notified of that fact?"

The sense of answering that question with events — come and build that sense with OnMarket.

Recommended for
these people

Who is this course right for?

  • A backend developer who has the basics of Java and Spring Boot but feels lost on where and why to apply Kafka.

  • Junior and mid-level developers who want to grasp the conceptual map before transitioning to EDA and MSA

  • Tech leads, senior developers, and architects who need to decide on Kafka adoption and design its architecture.

Need to know before starting?

  • Understanding Java programming language basic syntax and object-oriented concepts

  • Experience in basic use of the Spring Boot framework and experience in REST API development

  • Basic concepts of Relational Database Management Systems (RDBMS) and the ability to write SQL queries

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This is oncoding

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22 lectures ∙ (7hr 26min)

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