Mastering Data Consistency Across Microservices

Microservices architecture is a software design pattern where an application is built as a collection of small, independent services, each responsible for a specific function. 

These services communicate with each other using APIs (Application Programming Interfaces) and operate independently, allowing for greater flexibility, scalability, and ease of maintenance. Think of a food delivery app with the following services:

• The order service manages customer orders.

• The payment service handles transactions.

• The restaurant service updates menu availability.

• The delivery service assigns and tracks deliveries.

Each service operates independently, allowing teams to update or scale them separately. 

However, due to this separation, a major challenge with microservices is maintaining data consistency. In a monolithic system, all functionalities share a single database, resulting in consistent updates. On the other hand, microservices architecture advocates that each service should manage its database. While this is a good practice, it can lead to some scenarios such as:

• Duplicate or Lost Data

• Network Delays

• Concurrency Issues

Understanding these scenarios is key to building robust, scalable applications using microservices. In this article, we will understand how data inconsistency can arise in a microservices architecture and various strategies to deal with it.

Understanding Data Consistency in Microservices