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First, start the database. Either install and run Mongo or run it using docker:
docker run -d -p 27017:27017 --name=my-mongo mongo:latest
You can also use services like Mongo Altas for running a Mongo database in the cloud.
Now, launch the auth, user and gateway services. Just go to each directory and run npm install followed by npm start.
Lastly, go to the webapp directory and launch this component with npm install followed by npm start.
After all the components are launched, the app should be available in localhost in port 3000.
Deployment
For the deployment, we have several options.
The first and more flexible is to deploy to a virtual machine using SSH. This will work with any cloud service (or with our own server).
Other options include using the container services that most cloud services provide. This means, deploying our Docker containers directly.
We are going to use the first approach, creating a virtual machine in a cloud service and after installing docker and docker-compose, deploy our containers there using GitHub Actions and SSH.
Machine requirements for deployment
The machine for deployment can be created in services like Microsoft Azure or Amazon AWS. These are in general the settings that it must have:
Linux machine with Ubuntu > 20.04.
Docker and docker-compose installed.
Open ports for the applications installed (in this case, ports 3000 for the webapp and 8000 for the gateway service).
Once you have the virtual machine created, you can install docker and docker-compose using the following instructions:
Once we have our machine ready, we could deploy by hand the application, taking our docker-compose file and executing it in the remote machine.
In this repository, this process is done automatically using GitHub Actions. The idea is to trigger a series of actions when some condition is met in the repository.
As you can see, unitary tests of each module and e2e tests are executed before pushing the docker images and deploying them. Using this approach we avoid deploying versions that do not pass the tests.
The deploy action is the following:
deploy:
name: Deploy over SSHruns-on: ubuntu-latestneeds: [docker-push-userservice,docker-push-authservice,docker-push-gatewayservice,docker-push-webapp]steps:
- name: Deploy over SSHuses: fifsky/ssh-action@masterwith:
host: ${{ secrets.DEPLOY_HOST }}user: ${{ secrets.DEPLOY_USER }}key: ${{ secrets.DEPLOY_KEY }}command: | wget https://raw.githubusercontent.com/arquisoft/wiq_en1b/master/docker-compose.yml -O docker-compose.yml wget https://raw.githubusercontent.com/arquisoft/wiq_en1b/master/.env docker compose down docker compose --profile prod up -d
This action uses three secrets that must be configured in the repository:
DEPLOY_HOST: IP of the remote machine.
DEPLOY_USER: user with permission to execute the commands in the remote machine.
DEPLOY_KEY: key to authenticate the user in the remote machine.
Note that this action logs in the remote machine and downloads the docker-compose file from the repository and launches it. Obviously, previous actions have been executed which have uploaded the docker images to the GitHub Packages repository.
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OLD READ ME:
wiq_en1b
This is a base repo for the Software Architecture course in 2023/2024 edition.
The project can be seing here
This repo is a basic application composed of several components.
Both the user and auth service share a Mongo database that is accessed with mongoose.
Quick start guide
Using docker
The fastest way for launching this sample project is using docker. Just clone the project:
and launch it with docker compose:
Starting Component by component
First, start the database. Either install and run Mongo or run it using docker:
docker run -d -p 27017:27017 --name=my-mongo mongo:latest
You can also use services like Mongo Altas for running a Mongo database in the cloud.
Now, launch the auth, user and gateway services. Just go to each directory and run
npm install
followed bynpm start
.Lastly, go to the webapp directory and launch this component with
npm install
followed bynpm start
.After all the components are launched, the app should be available in localhost in port 3000.
Deployment
For the deployment, we have several options.
The first and more flexible is to deploy to a virtual machine using SSH. This will work with any cloud service (or with our own server).
Other options include using the container services that most cloud services provide. This means, deploying our Docker containers directly.
We are going to use the first approach, creating a virtual machine in a cloud service and after installing docker and docker-compose, deploy our containers there using GitHub Actions and SSH.
Machine requirements for deployment
The machine for deployment can be created in services like Microsoft Azure or Amazon AWS. These are in general the settings that it must have:
Once you have the virtual machine created, you can install docker and docker-compose using the following instructions:
Continuous delivery (GitHub Actions)
Once we have our machine ready, we could deploy by hand the application, taking our docker-compose file and executing it in the remote machine.
In this repository, this process is done automatically using GitHub Actions. The idea is to trigger a series of actions when some condition is met in the repository.
As you can see, unitary tests of each module and e2e tests are executed before pushing the docker images and deploying them. Using this approach we avoid deploying versions that do not pass the tests.
The deploy action is the following:
This action uses three secrets that must be configured in the repository:
Note that this action logs in the remote machine and downloads the docker-compose file from the repository and launches it. Obviously, previous actions have been executed which have uploaded the docker images to the GitHub Packages repository.
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