Python + FastAPI + Microservices

How to Run the Project

Prerequisites

You need to have Docker installed on your machine. Follow this guide to install Docker for your operating system: https://docs.docker.com/get-started/get-docker/.

It is also necessary to have an account on Docker Hub. If you don't have an account, you can create one at https://hub.docker.com/signup.

It is also necessary to have a Google Cloud account. If you don’t have one, you can create it here: https://cloud.google.com/

Running in Development Environment

To run the project in a development environment, follow these steps:

1. Clone this repository:

git clone https://github.com/hernique33comiitei/to-do-list-microservice-python.git

2. Navigate to the directory and rename .env.example to .env.

3. After doing that, simply run the command docker compose up --build. If you prefer not to keep your terminal busy, use docker compose up --build -d instead, and then check the created containers with docker compose ps.

4. To check if everything is working, open your browser and go to: http://localhost:5000/docs.

5. If something doesn’t work as expected, check the port settings in the newly renamed .env file. There may be a conflict with another project or service running on your machine.

Running on Kubernetes

Note: If you prefer to use the provided default image, you can skip to item 5 of this section. If you wish to build and use your own image, make sure to update the Deployments.yaml file by replacing the image field with the name of your custom image.

1. Let's build the image. Within the directory you cloned, use the following command:

   docker build -t your_user/to-do-list-microservice-python:v0.0.1 .

2. Verify if your image was built successfully using the command docker images.

3. Now enter docker login and log in to your Docker Hub account.

4. Now push your image to Docker Hub using:

   docker push your_user/to-do-list-microservice-python:v0.0.1

5. Once logged into your Google account, go to the home page and create a project with a name of your choice at https://console.cloud.google.com/projectcreate.

6. After creating the project, enter it by clicking on the notification that will appear on your screen.

7. Now search for Kubernetes Engine API and enable it.

8. After enabling your API, search for Kubernetes clusters and click on the Clusters option. On this page, click on Create.

9. In the upper-right corner, next to the Learn button, click on Switch to Standard cluster and confirm.

10. Now you can click Create with all the default settings. The creation of the cluster takes approximately 5 minutes.

11. After creating the instance, click on it, and at the top center of the screen, click on Connect. There are two ways to connect using gcloud: you can either download and configure the gcloud CLI, or connect through the integrated Google Cloud Shell. We will use the second option: RUN IN CLOUD SHELL. Wait for it to load, and when the terminal opens, press Enter on your keyboard to execute the command on your command line.

Note: If you chose to build and use your own image, run the following commands using nano Deployments.yaml and update the image fields with the address of the image you built. If you skipped this step and went directly to step 5 of this tutorial, simply run the commands below.

12. Execute the following commands in the cloud shell:

curl -L -o ConfigMap.yaml https://raw.githubusercontent.com/hernique33comiitei/to-do-list-microservice-python/main/ConfigMap.yaml
curl -L -o Deployments.yaml https://raw.githubusercontent.com/hernique33comiitei/to-do-list-microservice-python/main/Deployments.yaml
curl -L -o PersistentVolumeClaim.yaml https://raw.githubusercontent.com/hernique33comiitei/to-do-list-microservice-python/main/PersistentVolumeClaim.yaml
curl -L -o Secret.yaml https://raw.githubusercontent.com/hernique33comiitei/to-do-list-microservice-python/main/Secret.yaml
curl -L -o Services.yaml https://raw.githubusercontent.com/hernique33comiitei/to-do-list-microservice-python/main/Services.yaml

13. Execute the following commands in the cloud shell:

kubectl apply -f ConfigMap.yaml
kubectl apply -f Deployments.yaml
kubectl apply -f PersistentVolumeClaim.yaml
kubectl apply -f Secret.yaml
kubectl apply -f Services.yaml

14. After running these commands, execute kubectl get services. All services with an EXTERNAL-IP are the load balancers for each module. Each IP address corresponds to a module of the microservice, with a total of 5 modules. To access any module, simply use the IP address on port 80.