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Author: ahmetkucukoglu

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.

http://localhost:8091/

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.

What is Event Sourcing?

Previously, our services would be as follows.

Application Services 01
Application Services 01

This service consisted of hundreds of lines of code. To get rid of this confusion, we split our services into two parts as “Command” and “Query” with CQRS. We performed our CRUD operations with “Command” services and our query operations with “Query” services. Two separate services appeared as follows.

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.