Book Image

ASP.NET Core and Vue.js

By : Devlin Basilan Duldulao
Book Image

ASP.NET Core and Vue.js

By: Devlin Basilan Duldulao

Overview of this book

Vue.js 3 is faster and smaller than the previous version, and TypeScript’s full support out of the box makes it a more maintainable and easier-to-use version of Vue.js. Then, there's ASP.NET Core 5, which is the fastest .NET web framework today. Together, Vue.js for the frontend and ASP.NET Core 5 for the backend make a powerful combination. This book follows a hands-on approach to implementing practical methodologies for building robust applications using ASP.NET Core 5 and Vue.js 3. The topics here are not deep dive and the book is intended for busy .NET developers who have limited time and want a quick implementation of a clean architecture with popular libraries. You’ll start by setting up your web app’s backend, guided by clean architecture, command query responsibility segregation (CQRS), mediator pattern, and Entity Framework Core 5. The book then shows you how to build the frontend application using best practices, state management with Vuex, Vuetify UI component libraries, Vuelidate for input validations, lazy loading with Vue Router, and JWT authentication. Later, you’ll focus on testing and deployment. All the tutorials in this book support Windows 10, macOS, and Linux users. By the end of this book, you’ll be able to build an enterprise full-stack web app, use the most common npm packages for Vue.js and NuGet packages for ASP.NET Core, and deploy Vue.js and ASP.NET Core to Azure App Service using GitHub Actions.
Table of Contents (25 chapters)
1
Section 1: Getting Started
4
Section 2: Backend Development
13
Section 3: Frontend Development
20
Section 4: Testing and Deployment

Distributed caching

A distributed cache or global cache is a single instance or a group of cache servers with a dedicated network. As the applications hit the distributed cache, if cached data related to the application's request does not exist, the request redirects to the database to query the data. Otherwise, the distributed cache will simply respond with the data needed by the applications.

Here's a diagram of two servers sharing the same Redis instance for distributed caching:

Figure 10.1 – Distributed caching

The preceding diagram shows the requests from two servers hitting a Redis cache first before deciding whether to query from the database or not.

What happens if one of your services crashes? Nothing really because everyone is going to be querying the distributed cache anyway. And because the cache is distributed, it's going to be maintaining the data consistency. We can offload all that information and all that headache...