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Module 5

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Message Queues & Streaming

Decouple services and handle async workloads: message queues, pub/sub, Kafka, stream processing, and retry patterns.

7 lessons~94 min

What you'll learn

  • •Explain when to use a message queue vs direct service calls
  • •Compare point-to-point queues with pub/sub patterns
  • •Design systems using Kafka for event streaming
  • •Handle message failures with dead letter queues and retry strategies
  • •Choose between stream processing frameworks for real-time analytics
1

Message Queue Fundamentals

What message queues are, why they exist, and core concepts: producers, consumers, brokers, acknowledgments, and delivery guarantees.

12m
High
2

Publish/Subscribe Pattern

The pub/sub messaging model: topics, subscriptions, fan-out, filtering, and how it enables event-driven architectures.

10m
High
3

Apache Kafka Deep Dive

Kafka architecture: brokers, topics, partitions, consumer groups, offsets, exactly-once semantics, and when Kafka is the right choice.

20m
High
4

RabbitMQ & Traditional Message Brokers

RabbitMQ architecture: exchanges, queues, bindings, routing keys. How it differs from Kafka and when to choose it.

12m
Medium
5

Event-Driven Architecture

Designing systems around events: event producers, consumers, event buses, event schemas, and avoiding common pitfalls.

15m
High
6

Stream Processing

Real-time data processing: Kafka Streams, Apache Flink, windowing, stateful processing, and stream-table duality.

15m
Medium
7

Dead Letter Queues & Retry Patterns

Handling message failures gracefully: retry with exponential backoff, dead letter queues, poison message handling, and idempotency.

10m
High
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