Tag : ASP.NET Core (13)

Developing AWS Serverless Messaging System

1. Introduction

This article will be about how to develop the messaging system with the serverless approach. We will use AWS as a cloud provider. We will prefer .NET Core as the language.

In this part, I will set up the scenario and give preliminary information about what will be the result.

Our RESTful API endpoints will be as follows.

[POST] api/comments
[GET] api/comments

We will use the AWS services below.

Publishing the ASP.NET Core Application in GCP Kubernetes

1. Introduction

The subject of this article series is about how to publish API, which we developed with ASP:NET Core, in Kubernetes. We will use GCP(Google Cloud Platform) as a cloud provider.

In this part, i will show the scenario and give preliminary information about what will be the result. Also i will mention briefly some concepts in Kubernetes.

We will develop an API containing single endpoint.
We will dockerize that API. For this, we will create a dockerfile.
We will send the image we have created with the dockerfile to GCR(Google Cloud Container Registry).
We will start three containers from this image.
We will create "Load Balancer" service, which will distribute the requests coming to the application to the containers.

I want to mention five concepts in Kubernetes.

How to publish ASP.NET Core application by using Jenkins

In this article, i will describe how to publish ASP.NET Core application by using Jenkins. Since the subject of the article is about preparing pipeline, you can benefit the link below for the installation of Jenkins.

How to Install Jenkins on Windows | BlazeMeter

Learn to install Jenkins with this easy guide. This tutorial will take you step by step to installing the Jenkins CI server on Windows. Start automating today.

Because the target machine on which we will make deployment in our scenerio and the machine in which Jenkins has been installed will be different , we need to arrange a dedicated server for Jenkins. The reason is that the Jobs could deplete your resources while they are working.

The pipeline is made of the following 4 steps.

Checkout: Pull the source code from the Github
Build: Build the source code
Deploy: Deployment to the target machine