Recurring Mail notification using Hangfire
Hangfire is an open-source software for task scheduling in ASP .NET and ASP .NET core. It uses RDBMS / No SQL storage for storing background processing job details. So, Storage connectivity is the only configuration required to implement hangfire in ASP .NET applications. This framework includes hangfire server which queries the storage to process the […]
Introduction to GraphQL in .Net Core
Explore the seamless integration of GraphQL in .NET Core for efficient and flexible API development.
Boosting Performance in .NET Web API 6 with Redis Cache
Enhance .NET Web API 6 performance by implementing Redis caching for efficient data storage and retrieval.
Clean architecture for a Web API in ASP.NET Core
Implementing a clean architecture for a Web API in ASP.NET Core ensures modular, testable, and maintainable code by separating concerns into distinct layers such as presentation, application, domain, and infrastructure.
Boxing and Unboxing in C#
understanding the concept of boxing and unboxing in c#
Uploading Files to SharePoint using ASP.NET Core
Learn how to seamlessly upload files to SharePoint in ASP.NET Core using Microsoft Graph and the PnP Framework with our step-by-step guide.
Fresh service API Integration in .NET Web API
Integrating Freshservice API into your .NET Web API allows you to seamlessly connect and interact with Freshservice’s powerful customer support and IT service management platform within your .NET applications.
Serilog in Asp.Net Core WebApi
Serilog is a popular logging library for ASP.NET Core WebAPI applications. It offers powerful and flexible logging capabilities, enabling you to easily capture and manage log data in your web API project.
Pagination using HAL API schema approach using .Net Framework
In .NET Framework, HAL API schema facilitates user-friendly pagination with standardized response structures that include navigation links, streamlining the process of moving between data pages.
Implementation of Conversation Language Understanding (CLU)
Implementation of Conversation Language Understanding (CLU) involves creating a robust system that can comprehend and respond to natural language conversations effectively, enabling seamless communication between humans and machines.