Designing Scalable APIs with Stateful Architecture

Clean APIs don't happen by accident, they're designed. A solid REST API is built on clear principles: stateless architecture, structured endpoints, proper HTTP methods, and security-first thinking. Get these right, and everything else scales. Design smart. Build once. Scale endlessly. 🚀 #API #softwaredevelopment #webdevelopment #technology #programming #coding

Every engineering team has encountered that one piece of code. It works - technically. It passes tests (most of the time), delivers value, and quietly sits in production like a ticking time bomb wrapped in good intentions. Ask a developer about it, and the response is often the same: “It’s a bit messy, but it’s fine… for now.” Multiply that sentiment across an entire codebase, and suddenly “fine” becomes fragile. Technical debt accumulates silently. Maintainability erodes gradually. And before long, even small changes feel like navigating a maze with invisible walls. The problem is not just the existence of technical debt - it is the inability to quantify and communicate it effectively. Without visibility, teams struggle to prioritize refactoring, and stakeholders struggle to understand why it matters. To read this whole article click here: https://sbox.bz/qibmdnl95 ScreamingBox #engineering #softwareengineering #code #coding #codebase #technialdebt #maintainability #quantify #communicateeffectively #prioritizerefactoring

“This might be overengineering.” A sentence I’ve started to find very… interesting. In one of the design discussions, I suggested using the Adapter pattern. The context was a classic microservices puzzle: shared libraries, multiple services, and a few “outlier” services with their own models that didn’t quite fit the shared contract. My suggestion was simple in intent. Isolate the mismatch, adapt where needed, and delegate transformations to a dedicated layer. The response? “It feels a bit complicated and an overkill.” Fair point. Also, a familiar one XD We went ahead with a simpler approach using a common interface. It helped us move faster, kept things easy to follow, and honestly got us unblocked quickly. No complaints there. But as things progressed, the system started teaching us a few lessons: 1. We initially ran into deserialization issues, where default interface methods interfered with actual values. We caught it early and fixed it. A small win for testing and awareness. 2. Later in higher environments, we noticed debugging wasn’t as straightforward as expected. Since transformations weren’t delegated to a dedicated service, which already had structured logging and error handling, tracing issues became slightly adventurous. 3. And then came a miss during a redesign change. One transformation, implemented outside a centralized flow, quietly escaped updates and came back as rework in later stories. Nothing catastrophic. But enough to make us pause and reflect. For me, the takeaway wasn’t that we should always use one specific pattern. It was this: - What we often call “complex” is just something we’re less familiar with. - And what we call “simple” sometimes just shifts complexity into places we don’t immediately see. Good design, I’m learning, is less about picking the “right” pattern and more about placing responsibilities where they age well as the system evolves. Still exploring, still experimenting, and yes, still occasionally losing design debates. But definitely learning what to bring to the next one :) #SystemDesign #SoftwareEngineering #Microservices #Java #SpringBoot #DesignPatterns #BackendDevelopment #DistributedSystems #CleanArchitecture #TechLeadership #ScalableSystems #DeveloperLife #EngineeringMindset #TechLessons #ContinuousLearning #Coding #Developers #Tech #Programming #LearnInPublic

"If you're only using REST APIs… you're leaving performance on the table." ⚡ Modern systems demand more than just a "one size fits all" approach. From the raw speed of gRPC to the real-time persistence of WebSockets and the lightweight efficiency of MQTT , the right architecture is a game changer. The difference between an average system and a scalable one? 👉 Choosing the right tool for the right job. I’m currently diving deep into these API styles as part of my learning journey focusing on building systems that are fast, scalable, and production-ready. 💡 What’s your go-to API architecture and why? #SystemDesign #BackendDevelopment #FullStackDeveloper #APIs #Tech #Scalability #Programming #SoftwareEngineering #LearningInPublic

Many delivery issues look complex on the surface. Often, they come down to simple coordination gaps. Code review ownership is one of the most common gaps. #DevOpsPractices #EngineeringInsights #CodeReview #SoftwareTeams

Anyone can be the hero once. Authority comes from building repeatable systems that keep working. If you can run it locally, you can put it in a shell script. If you can put it in a shell script, you can put it in a pipeline. And once it is in a pipeline, you can do far more than build and test. You can enforce quality. You can run security checks. You can standardize delivery. You can create confidence at every stage. That is how you move from coding to building real engineering systems. #coding #softwareegineering

Topic: Writing Reusable Code Good code works. Reusable code scales across projects. In many applications, similar logic gets rewritten multiple times. This leads to: • Code duplication • Increased maintenance effort • Higher chances of bugs Reusable code focuses on: • Modular design • Clear abstraction • Separation of concerns • Generic and configurable components The goal is not just to solve one problem —but to solve it in a way that can be reused. Because writing code once and using it many times saves effort in the long run. What’s one example of reusable code you’ve built? #CleanCode #SoftwareEngineering #JavaDeveloper #BackendDevelopment #Coding

SOLID principles are the foundation of writing clean and maintainable code. A great reference to keep handy, especially for developers looking to level up their software design skills.

SOLID Principles Explained for Developers If you want to write clean, scalable, and maintainable code, you must understand the SOLID Principles. 🔹 S — Single Responsibility 🔹 O — Open / Closed 🔹 L — Liskov Substitution 🔹 I — Interface Segregation 🔹 D — Dependency Inversion These principles help you build better software architecture and cleaner code. #programming #coding #developers #softwareengineering #solidprinciples

These principles are ingrained in how we operate. We just don't know how to attribute the behavior to the specific acronym.