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Improving API Reliability: A Retrospective

Working on ProvidenceAPI-Back, we've recently focused on enhancing the reliability and maintainability of our backend API. This post reflects on key areas of improvement and the lessons learned.

The Challenge

Initially, our API faced challenges related to request handling and data processing. We observed occasional inconsistencies in data and slow response times under certain load conditions.

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Streamlining API Interactions: When to Refactor Service Classes

We've all been there: a growing service class that handles API interactions, starting simple but gradually accumulating responsibilities. The initial design seemed reasonable, but now it's a sprawling monolith. When do you step back and refactor?

The Problem: Feature Creep

Imagine a DataService class initially designed to fetch data. Over time, it gains methods for caching, error handling,

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API backend

Understanding API Backends

Introduction

Working on the backend of an API involves various considerations, from data handling to ensuring smooth communication between different parts of the system. This post provides a broad overview of common tasks and concepts when developing or maintaining an API backend.

Core Responsibilities

The primary responsibility of an API backend is to handle requests from client

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API backend

Enhancing API Interactions: A Focus on Backend Improvements

Introduction

In the evolving landscape of software development, maintaining a robust and efficient backend is crucial. Recent activities around the ProvidenceAPI/ProvidenceAPI-Back project highlight ongoing efforts to refine and optimize the API's performance and reliability.

The Focus

The primary focus revolves around improving how the backend handles requests and processes data.

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Refactoring for Readability: When to Simplify Your Architecture

Have you ever felt lost in your own codebase? We've all been there, staring at a complex system, wondering how it ballooned out of control. In the ProvidenceAPI/ProvidenceAPI-Back project, we recently faced a similar challenge. While no specific language or framework was apparent from the source data, we found opportunities to improve readability and maintainability through architectural

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