Welcome to the articles section.
Here you’ll find practical, experience-based content about real-world software engineering — focusing on what actually works in production and what often goes wrong.
The main topics include:
The goal is to share clear, actionable insights based on real enterprise and production systems — not just theoretical concepts.
In microservice architectures, REST calls between services are unavoidable.
However, one of the most common and dangerous production mistakes is forgetting to configure proper timeouts for REST clients.
Exception handling is a fundamental part of application design, yet many systems — especially legacy enterprise codebases — still rely heavily on checked exceptions and extensive try-catch blocks across every layer.
In modern microservices architectures, this approach often causes more harm than good.
In distributed systems, logging and exception handling are not just debugging tools — they are core parts of system reliability and observability.
Poor logging makes production issues hard to diagnose, while improper exception handling often leads to hidden failures, inconsistent states, and frustrated users.
In a microservices environment, classic ACID transactions across multiple services are not feasible.
Each service typically owns its own database, making distributed transactions complex, slow, and fragile.
Transaction handling is straightforward in monolithic applications.
A single database, a single transaction boundary, and frameworks like Spring make it almost effortless with the @Transactional annotation.
In the previous article, we explored why transaction management becomes problematic in microservices — especially when services are poorly split and rely on synchronous REST calls.
Now let’s look at how transactions can be handled correctly in a Spring Boot-based microservice architecture.
