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.
Category: Web Applications
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.
- 1. Introduction
- 2. Installing the Event Store
- 3. Creating the API Project
- 4. Aggregate Base Class and Aggregate Repository
- 5. Defining Task and Use Cases
- 6. Preparing API Endpoints
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.
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”.
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.
Previously, our services would be as follows.
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.