Copyright (c) 2025 MindMesh Academy. All rights reserved. This content is proprietary and may not be reproduced or distributed without permission.

3.2.3.1. Event-Driven, Asynchronous Design Patterns (S3 Events, EventBridge to SNS/Lambda)

First Principle: Event-Driven Architectures (EDA) enable systems to communicate asynchronously via events, allowing independent evolution, fault isolation, and efficient resource utilization.

EDA embodies the principles of automation, scalability, and loose coupling. This design builds highly scalable, resilient, and flexible systems.

Key EDA Patterns:
  • Fan Out: One event triggers multiple parallel actions. Practical for processing data uploads or automating workflows.
  • Event Streaming: Continuous flow of events for real-time processing and analytics.
  • Queuing: Decouples producers from consumers, buffering messages for reliable delivery.
    • AWS Example: Amazon SQS queues handle incoming requests, allowing backend services to process them at their own pace, integrating disparate systems.
Key Event-Driven Design Patterns:
  • Fan Out: One-to-many event distribution (S3, SNS, Lambda).
  • Event Streaming: Continuous flow for real-time processing (Kinesis).
  • Queuing: Decouples components, buffers messages (SQS).

Scenario: A DevOps team needs to design a system where an image upload to an Amazon S3 bucket triggers multiple independent processing steps (e.g., resizing, tagging, virus scanning). The system should be scalable and resilient, avoiding tight coupling between these steps.

Reflection Question: How would you use Amazon S3 Event Notifications (to trigger an Amazon SNS topic) and then AWS Lambda functions (subscribed to SNS) to implement a "fan out" event-driven, asynchronous design pattern, ensuring independent evolution and fault isolation for each processing step?

šŸ’” Tip: Consider how EDA improves system responsiveness and reduces tight coupling by allowing components to react to events without direct dependencies.