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Building Scalable E-commerce Order Processing Microservice with a Serverless Fan-Out Architecture

Tame fluctuating order volume with a powerful serverless architecture. Learn how to build a scalable e-commerce order processing system using AWS.

serverlesssqssnsapi-gatewayecommerce
abhishek jhingran
Published Apr 1, 2024
Link to the architecture:
https://gist.github.com/abhishekjkrsna/acbf2c9899710e9f01789fb38d4ed37c
In the fast-paced world of e-commerce, a robust and scalable order processing system is crucial for success. Serverless architectures on AWS provide the power and flexibility to handle fluctuating demands while minimizing operational overhead. In this post, we'll explore how to design a serverless fan-out architecture using SNS, SQS, and Lambda to achieve efficient e-commerce order handling.

The Fan-Out Pattern: Why It Matters for E-commerce

The fan-out pattern allows a single event or message to be processed by multiple downstream services simultaneously. For order processing, this is a potent strategy. When an order is placed, parallel processes need to occur:
  • Customer Notifications: Emails, SMS updates, etc., must be sent.
  • Inventory Updates: Deducting stock to avoid overselling.
  • Shipment Initiation: Communicating with logistics providers.
  • Analytics Data Storage: Storing data for analytics.

Architecture Breakdown

Let's dissect the services that orchestrate this serverless magic:
  • API Gateway: The entry point for your e-commerce system, receiving order data as HTTP requests.
  • AWS Lambda: Serverless functions for processing requests.
  • Amazon SNS: A highly-scalable pub/sub messaging service.
  • Amazon SQS: SQS queues act as buffers, ensuring message persistence and distributed processing:
  • Amazon DynamoDB: A fast NoSQL database to store order details and related information.

Advantages of This Design

  • True Scalability: Handles surges in order volume without manual infrastructure adjustments.
  • Loose Coupling: Modify or update components (e.g., introduce a loyalty point system) without disrupting the entire system.
  • Cost-Efficiency: Pay-as-you-go serverless model minimizes expenses during low activity periods.
  • Independent Processing: Order notifications and shipment operations can be developed, deployed, and scaled individually.

In Action: An Order's Journey

  1. Customer places an order on your website or app.
  2. API Gateway invokes the Lambda for order processing.
  3. The Order Processing Lambda function Processes the order and pushes the order to SNS for further processing.
  4. SNS fans out the message to SQS queues. This ensures scalability during peak periods.
  5. Lambda functions for each queue pick up messages and perform their tasks.

Important Note:

I've assumed a general e-commerce scenario and presented a simple solution for the use-case.
 

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