Ordering and Inventoring Management

August 16, 2024 7:00 PM PDT

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This meeting focused on the design of a distributed inventory management system, similar to eBay and Amazon. The discussion included requirements gathering, functional specifications, and high-level system architecture. Key topics included database design, caching strategies, and handling order processing.

Key Discussion Points

System Design

• Design Requirements:
  • Create an inventory system similar to Amazon.
  • Functional requirements were outlined, focusing on the need for both purchase ID and order ID, with a preference for using only order ID.

Database Design

• Database Selection:

  • MySQL was chosen for strong consistency.
  • Initially, all data (products, users, orders) will reside in a single database.

• Schema Design:

  • Product and order tables will be in the same database.
  • Considerations for sharding the order table based on product ID were discussed, with the conclusion that orders containing multiple products would require a fan-out approach for reading.

Performance Optimization

• High-Level Architecture:

  • An API gateway will handle throttling and routing.
  • To manage high throughput (100k QPS), optimizations for the write path were proposed, including the addition of a queue and a cache.

• Caching Strategy:

  • The system will first read from cache; if a cache miss occurs, it will then read from the database.
  • Trade-offs between cache and database reads were discussed, emphasizing the speed of cache reads.

Order Processing

• Order ID Generation:

  • A unique number generator service was suggested for generating order IDs.

• Handling Order Success/Failure:

  • A message queue will be implemented to inform users of order success or failure.

• SAGA Pattern:

  • The SAGA pattern was introduced for managing distributed transactions, outlining the steps for reserving inventory and processing payments.

Implementation Details

• Inventory Management:

  • Two implementations were proposed for inventory management:
    1. Write results to the database and commit.
    2. Lock rows during the reservation process to ensure data integrity.

• Cache Structure:

  • Cache will store inventory details, including available, reserved, and shipped counts.

• Application Layer Code:

  • The application will write to the cache first, then attempt to update the database, handling exceptions as necessary.

Conclusion

The design discussion highlighted the complexities involved in creating a robust ordering and inventory management system. Key takeaways include the importance of choosing the right database, optimizing for performance, and ensuring data integrity through effective transaction management strategies. Further exploration of trade-offs and justifications for design choices will be necessary for future iterations.