DotNet Full Stack Dev

  In the world of software development, one of the classic architectural dilemmas revolves around the choice between static classes and the singleton pattern . Both provide a way to ensure that there’s only one point of access to functionality or resources in your application, but does that mean they’re interchangeable? Let’s dive deep into these two approaches and uncover why a static class is not the same as a singleton—and why understanding the difference is critical for crafting maintainable, scalable applications. The Temptation of Static Classes Let’s face it: static classes are simple . You don’t need to worry about constructors, instance management, or multithreading. All you need is a class with static members, and you’re good to go. That’s why they’re often the go-to choice for developers who want to expose global behavior or utility methods quickly. Never miss new posts by subscribe Subscribe Powered by For instance, say you need a utility to format dates ac...

  The Polly retry pattern is a powerful mechanism for handling transient faults in applications by retrying failed operations. Polly is a .NET library that provides resilience strategies like retries, circuit breakers, timeouts, and fallback mechanisms. The retry pattern is particularly useful when dealing with unreliable external services, such as APIs or databases, that may occasionally fail but succeed on subsequent attempts. In this blog, we will explore how to implement the Polly retry pattern in .NET Core, particularly in the context of using HttpClient with IHttpClientFactory . We'll also see how to configure retry policies to make your HTTP requests more resilient. Why Use the Retry Pattern? Transient Failures : Network failures or intermittent connectivity issues may cause operations to fail temporarily. Rate Limiting : External services may apply rate limits and reject requests, but retrying after a delay can succeed. Load Balancing : Sometimes, servers are temporarily o...

  In today's applications, delivering real-time updates to users is crucial for creating engaging experiences. One efficient way to achieve this in a .NET environment is by using Server-Sent Events (SSE). This blog will guide you through implementing SSE using an Item API to push real-time updates to clients. What are Server-Sent Events? Server-Sent Events (SSE) allow a server to push updates to clients over HTTP. Unlike WebSockets, which provide full-duplex communication, SSE is a simpler protocol suited for scenarios where updates flow from the server to the client, such as notifications or live content updates. Why Use Server-Sent Events? Simplicity : SSE is built on standard HTTP protocols, making it easier to implement compared to WebSockets. Automatic Reconnection : The client automatically reconnects if the connection is lost. Text-Based : SSE sends data in plain text, making it easy to parse. Setting Up the Item API Let's assume you have a simple Item API with basic CRU...

In a microservice architecture, applications are divided into smaller, independent services that communicate with each other. The CQRS (Command Query Responsibility Segregation) pattern further improves this architecture by separating the read and write operations for better scalability and performance. In this blog, we will explore how to implement a microservice architecture using CQRS with Product and Order services as examples. 1. Understanding Microservice Architecture Microservices decompose a large application into independent, self-contained services. Each service performs a specific business function, such as managing products or handling orders, and communicates with other services over lightweight protocols such as HTTP or messaging systems like Kafka. Key benefits include: Scalability : Individual services can be scaled based on their own resource demands. Resilience : Failure in one service doesn't bring down the entire system. Autonomy : Each service can be develop...

  When developing multithreaded or parallel applications, managing shared data across multiple threads becomes challenging. In scenarios where multiple threads are accessing and modifying the same collection simultaneously, traditional collections like List<T> , Dictionary<TKey, TValue> , or Queue<T> are not thread-safe. This can lead to race conditions , data corruption , or even application crashes. To address this issue, Concurrent Collections were introduced in the .NET Framework , specifically designed for scenarios where multiple threads need to work with collections concurrently. In this blog, we'll explore what concurrent collections are , how they differ from standard collections and generic collections , and provide examples to illustrate their usage. What are Concurrent Collections? Concurrent collections in .NET are a set of collection classes specifically designed to handle concurrent operations in multithreaded environments. They are optimized for...