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Tag: ASP.NET Core

What is Modular Monolith?

Traditional Monolith

Firstly, let’s talk about Traditional Monolith approach. This approach focuses on layers. It includes three layers, UI, Business and Data. All features in a project are vertically separated into these layers. Among those three layers, the business layer is the one that contains business logics of all features. Each feature knows business logic of other features, which is a fact we call tightly coupled.

Traditional Monolith

ASP.NET Core Feature Management

Feature Management provides feature management in .NET Core applications. It allows the management and querying of the active / passive status of the features of the application. For example, you can ensure that a feature you have just developed is active in a certain date range. To give another example, you can ensure that a feature you have developed is active with a certain percentage. Like A/B testing.

Event Sourcing with ASP.NET Core – 02 Messaging

1. Introduction

Since this article is second part of the article below, I recommend you to read the following article before starting. We will continue with the sample project in the article below.

In the previous article, we made the example of Kanban Board. By creating a RESTful API, we wrote the create, assign, move and complete endpoints. We recorded the requests coming to these endpoints as an event in the Event Store. So we focused on the store part of the Event Store. In this article, we will focus on with the messaging part.

We will include the following endpoint in our RESTful API endpoints.

[GET] api/tasks/{id}

Event Sourcing with ASP.NET Core – 01 Store

1. Introduction

I recommend you to read the article below before applying this example tutorial.

In the article I have mentioned above, I had formed a sentence as follows.

There is a technology called “Event Store” in the .NET world for Event Sourcing. This technology offers solutions for “Aggregate” and “Projection”. In other words, in addition to providing the store where we can record the events, it also provides the “Messaging” and “Projection” services, which are necessary for us to record in “Query” databases.

In this article, we will deal with the store section of the Event Store. In other words, we will deal with the database feature where we can save events. In the next article, we will deal with the messaging part.

As an sample application, I chose the classic Kanban Board sample.

Our RESTful API endpoints will be as follows.

[POST] api/tasks/{id}/create
[PATCH] api/tasks/{id}/assign
[PATCH] api/tasks/{id}/move
[PATCH] api/tasks/{id}/complete

Couchbase GeoSearch with ASP.NET Core

The subject of this article will be about how to do “GeoSearch” by using Couchbase.

1. Installing the Couchbase

For this purpose, we create Couchbase cluster with the docker by running the command below.

docker run -d --name couchbase -p 8091-8094:8091-8094 -p 11210:11210 couchbase

When Couchbase is up, it will start broadcasting at the address below.


We create the cluster by clicking the “Setup New Cluster” button. We define the password as “123456”.

Create New Cluster
Create New Cluster

You can make adjustment according to your current memory status. You can turn off “Analytics”. We complete the cluster installation by clicking the “Save & Finish” button.

Publishing Docker Image as Serverless on GCP

1. Introduction

With the serverless approach, the problem about the server that the software developer confronts with has disappeared. Now we write our code and call the provider to run it. We are not dealing with server configurations, scalings etc. And pay as you go. This is a great opportunity.

AWS’s Lambda, GCP’s Cloud Function, Azure’s Azure Function etc., these services provide us this service. But this time, different kind of problem appears. These services do not support all languages. Even if it supports the language we want, it may not support the version we want. For example, AWS Lambda does not support the upper versions of .NET Core 2.1 yet. This is a problem. Nobody can restrict us 🙂

The Cloud Run service that Google built on Knative completely solves this problem. We give Cloud Run a docker image and Cloud Run runs our serverless service from this image. So whether we develop in PHP or .NET Core, it doesn’t matter. There is no limit as long as we can make dockerize. This is awesome.

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.

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