10 Organizing a Kafka Project

 

This chapter covers

  • Defining project requirements across environment setup, non-functional requirements, infrastructure sizing, and resource quotas.
  • Maintaining Kafka cluster using tools, GitOps, and the Kafka Admin API.
  • Testing Kafka applications.

Adopting Kafka succeeds or fails as much on process as on code. Teams often prototype and size infrastructure, yet overlook how Kafka fits the organization’s workflow—who owns events, how changes are approved, how reliability is proven. This chapter focuses on that gap. You’ll learn how to capture requirements and data contracts, how to maintain the cluster structure across environments, and how to test applications effectively. These practices reduce risk, prevent costly rework, and make performance, cost, and compliance predictable—turning a promising prototype into an operable, supportable system.

10.1 Defining Kafka Project Requirements

Projects start with requirements gathering. What should we analyze to make a Kafka—and event-driven—project successful? Are there Kafka-specific requirements we need to capture?

10.1.1 Field notes: Use-Case Intake and Requirements

Max sighed as he sat down, shaking his head.

Max: Alright, team. Our project is starting to attract a lot of attention. Every time I go for lunch, someone stops me and asks if they can also use Kafka for their use case. It’s like we’ve created a new buzzword in the company.

10.1.2 Identifying event-driven workflows

10.1.3 Turning business workflows into events

10.1.4 Gathering functional requirements for Kafka topics

10.1.5 Identifying non-functional requirements

10.2 Maintaining Cluster Structure

10.2.1 Using tools

10.2.2 Using GitOps for Kafka configurations

10.2.3 Using the Kafka Admin API

10.2.4 Setting up environments

10.2.5 Field notes: Choosing a solution for Customer360 project

10.3 Testing Kafka applications

10.3.1 Unit testing

10.3.2 Integration testing

10.3.3 Performance tests

10.4 Online Resources

10.5 Summary