Battling the imposter syndrome with code
Battling the imposter syndrome with code
An in-depth look at implementing message queuing in .NET Core using MassTransit and RabbitMQ. Covers key concepts including SSL configuration, host options, filters, and circuit breaker patterns. Includes practical examples for setting up message consumers, producers, and handling exceptions in distributed systems.
In this blog post, I’ll introduce NDepend, a static code analysis tool designed for .NET and .NET Core projects. NDepend offers features such as code metrics, dependency analysis, technical debt estimation, and code rule enforcement to help you assess and enhance your code quality. The post will guide you through using NDepend to analyze your code base, identify issues, and implement best practices. While we’ll touch on its comparison with SonarQube, the main focus will be on understanding NDepend’s product and features. If you’re a .NET developer, NDepend can be a valuable asset for code improvement.
In the ever-expanding realm of contemporary systems, where data storage is more abundant and cost-effective, our data repositories grow rapidly. From basic text files to content-rich multimedia documents, we accumulate a diverse range of data. The challenge arises when the need to search for specific data, words, or phrases—whether through a direct search or related terms—calls for thoughtful consideration and the right tools.
Among the tools available today, Elasticsearch stands out as a mature search engine, residing at the core of the Elastic Stack. With a robust foundation and widespread adoption across various fields, Elasticsearch has proven itself as a reliable and versatile solution. This blog post kicks off by explaining the fundamentals and concepts of Elasticsearch, shedding light on its workings. Later, it offers a practical, easily understandable implementation guide that addresses various aspects of text search and analytics. We’ll delve into working with Elasticsearch in .Net Core 8, using the new Elasticsearch C# client (version 8.0+), covering indexing, searching, and ultimately aggregating data.
Whether you’re new to navigating the world of Elasticsearch or a seasoned explorer aiming to deepen your understanding, I hope this two-part guide help get you up to speed easily in working in ElasticSearch for full text search and analysis in .net core.
In today’s world of complex applications and intricate distributed systems, efficient resource management is of great importance. This blog post offers an insightful exploration of distributed locks in .Net, emphasizing their significance and practical applications. Most importantly, this post aims to assist you in making an informed decision to choose the most suitable tool for your specific needs.
Distributed locks, at their core, serve a critical role: ensuring that in environments with numerous nodes, processes, or threads competing for access to a shared resource, only one entity gains access at any given moment. Whether it involves coordinating access to a centralized storage system, managing database records, executing resource-intensive computations, or facilitating API calls, distributed locks play a pivotal role. They contribute to system efficiency by eliminating redundant work, preserving data accuracy, and strengthening system stability by preventing issues like data anomalies. This blog post not only covers the fundamental aspects of distributed locks but also provides insights into their practical implementations, equipping decision-makers with valuable knowledge to select the most appropriate tool for their project.
In the world of web applications, speed is a critical factor. Caching, a fundamental concept, is pivotal in achieving faster response times and efficient resource utilization. It involves storing frequently accessed data in a cache, which significantly improves user experiences.
Redis, or Remote Dictionary Server, is a versatile tool for optimizing .NET Core applications. It functions as a high-speed, open-source, in-memory data structure store primarily designed as a key-value store. However, its utility extends to serving as a cache, database, message broker, and streaming engine. Redis excels in speed due to its in-memory operation, making it ideal for scenarios where low-latency responses are essential. It empowers developers to choose the most suitable data structure for their specific needs, whether it’s simple key-value pairs, complex data relationships, or real-time streaming data. Redis is the solution to enhance your .NET Core applications’ efficiency and responsiveness, providing a smoother user experience while efficiently managing high user loads.
Front-end developers often encounter situations where APIs are either unavailable or incomplete during the development phase. Mocking API server responses becomes a crucial technique in such scenarios, allowing developers to make progress without being blocked by API availability.
Discover how Json-Server, a user-friendly tool, simplifies the process of creating a mock API server. With minimal setup, you can simulate full-featured APIs for testing and development. This guide covers everything from installation to custom routing, offering an efficient way to streamline your frontend development workflow.
Explore Chaos Engineering’s benefits, uncover system weaknesses, boost resilience, and learn popular tools in our latest blog post.
Learn how to schedule background tasks easily and quickly in C#/.Net with Hangfire simple API.
Performance is affected by many factors – starting from the application design or architecture to the way the application code was implemented. […]
Modern applications often depend on resources and services from other services or systems, that may be hosted on the cloud, on a […]