📝 Worked decision walkthroughs: four use cases and a 2026 cost check

Learning Objectives

By the end of this lesson you can:

  • Run the same six-question checklist against any candidate workload.
  • Defend a broker pick for payments, event sourcing, task distribution and IoT telemetry using delivery, ordering, operational and licensing arguments.
  • Build a first-order monthly cost estimate for both brokers from message rate, message size and retention.
  • Name the dominant cost driver in each architecture and the one number that most often surprises teams.

Quick Review

Last lesson split ecosystem fit into three questions: which client library your code imports, whether you need a connector platform, and whether you need stateful stream processing.

We also established that operations and retention behave very differently: Kafka keeps bytes on disk for a configured window, RabbitMQ deletes a message the moment it is acknowledged. Hold those two facts close, because every walkthrough below leans on them.

Theory: The Six-Question Checklist

Before you argue about products, answer these in order. Stop at the first question that decides the case.

# Question Points to Kafka Points to RabbitMQ
1 Must anyone replay old data later? Yes, replay is the point No, once processed it is gone
2 What ordering unit matters? Per key, achieved by partition key Per queue, single active consumer
3 What does failure recovery look like? Offset rewind, reprocess a range Per-message nack, retry, DLQ
4 What is the message rate? Sustained high fan-in Moderate, bursty, uneven task times
5 How complex is routing? Simple topic fan-out Exchanges, bindings, headers, priorities
6 What dominates cost? Bytes retained × replication In-flight backlog + node count

[!IMPORTANT] Question 1 is the one people skip. If nobody can name who replays the data and why, you probably do not need a log. If somebody can, you almost certainly do.

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