Hany Ouf

Caching in a Typical Architecture Caching in a Typical Architecture: A Multi-Layered Approach Data is cached at multiple levels across a system, from the front end to the back end , to improve performance, scalability, and reliability . This guide explains the different caching layers in a standard architecture. Multiple Layers of Caching 1. Client Apps HTTP responses can be cached locally by the browser , reducing unnecessary network requests. When a request is made for the first time, the server responds with data and an expiry policy in the HTTP headers. Future requests for the same data are served from the browser cache , improving response times. Service Workers enable offline caching and background synchronization. 2. Content Delivery Network (CDN) CDNs cache static web resources like images, JavaScript files, and CSS in geographically distributed servers. ...

Mastering Data Consistency Across Microservices 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. Challenges of Data Consistency Due to the separation of services, a major challen...

Event Sourcing: Choosing the Right Approach Event Sourcing: Choosing the Right Approach for Scalability and Consistency Introduction Event Sourcing (ES) is a powerful architectural pattern where system state changes are captured as a sequence of immutable events rather than directly modifying database records. This approach offers benefits such as auditability, replayability, and improved system resilience. However, implementing ES effectively depends on business requirements, scalability needs, and consistency considerations. Direct Database Writes: When ACID Works (and When It Doesn't) A simple way to implement ES is to write events directly to a database, ensuring transactional consistency ( ACID compliance ). This approach is feasible if: Events occur infrequently. Data must be strongly consistent. Scalability is not a primary concern. Why ACID Doesn't Scale for ES ...