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https://github.com/briancaffey/django-postgres-vue-gitlab-ecs
An example project that demonstrates local development, CI/CD and production setup for a full stack web application using Django, Django REST Framework, Django Channels, Postgres, VueJS, Redis, Celery, GitLab CI, CloudFormation and AWS ECS.
https://github.com/briancaffey/django-postgres-vue-gitlab-ecs
celery celerybeat cicd cloudformation cypress-tests darkmode django docker docker-compose ecs gitlab-ci internationalization minikube nginx postgres postgresql pytest quasar-framework redis vue
Last synced: about 1 month ago
JSON representation
An example project that demonstrates local development, CI/CD and production setup for a full stack web application using Django, Django REST Framework, Django Channels, Postgres, VueJS, Redis, Celery, GitLab CI, CloudFormation and AWS ECS.
- Host: GitHub
- URL: https://github.com/briancaffey/django-postgres-vue-gitlab-ecs
- Owner: briancaffey
- License: mit
- Created: 2019-08-06T22:29:50.000Z (over 5 years ago)
- Default Branch: develop
- Last Pushed: 2021-05-10T06:22:23.000Z (over 3 years ago)
- Last Synced: 2023-03-06T05:56:31.666Z (over 1 year ago)
- Topics: celery, celerybeat, cicd, cloudformation, cypress-tests, darkmode, django, docker, docker-compose, ecs, gitlab-ci, internationalization, minikube, nginx, postgres, postgresql, pytest, quasar-framework, redis, vue
- Language: Python
- Size: 5.73 MB
- Stars: 55
- Watchers: 3
- Forks: 29
- Open Issues: 16
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
## Project Documentation
Documentation for this project can be found here:
[https://verbose-equals-true.gitlab.io/django-postgres-vue-gitlab-ecs/](https://verbose-equals-true.gitlab.io/django-postgres-vue-gitlab-ecs/)
## Project Architecture Overview
Here is an overview of the project architecture, including the CI/CD pipeline and the AWS infrastructure that will be automatically provisioned through the AWS Cloud Development Kit:
![png](/architecture.png)
(This diagram was created with [draw.io](https://draw.io). Here's the link to the a read-only version of the diagram on draw.io: [https://drive.google.com/file/d/1gU61zjoW80fCusUcswU1zhEE5VFB1Z5U/view?usp=sharing](https://drive.google.com/file/d/1gU61zjoW80fCusUcswU1zhEE5VFB1Z5U/view?usp=sharing)
### Legend
1 - GitLab is used to host the source code, test the source code and deploy the application to AWS.
2 - Unit testing (see `.gitlab-ci.yml`)
2a - Pytest
2b - Jest
2c - Cypress
3 - Deployment phase (see `/gitlab-ci/aws/cdk.yml`)
3a - Quasar PWA assets are built if there are changes in the `quasar` directory
3b - AWS Cloud Development Kit (CDK) defines all infrastructure in AWS (4a - 12)
3c - AWS CLI is used to run Fargate tasks through manual GitLab CI jobs
4 - CDK Assets (ECR and S3 buckets that CDK uses internally to manage build assets and artifacts)
4a - Elastic Container Repository is used to manage the Django docker image used in various parts of the application
4b - S3 bucket used to store files associated with CDK and CloudFormation
5 - Route53 is used to route traffic to the CloudFront distribution
6 - CloudFront distribution that serves as the "front desk" of the application. It routes requests to to the correct CloudFront Origin
7 - CloudFront Origin Configurations
7a - S3 bucket for Quasar PWA assets
7b - Application Load Balancer for Django application (`/api/`, `/admin/`, `/flower/`, `/ws/`, `/graphql/`)
7c - S3 bucket for Django assets (static files, public media and private media)
8 - Web server and websocket servers
8a - Fargate service running uvicorn process (REST, GraphQL, Django Channels)
8b - Autoscaling Group for Fargate Service that serves Django API
9 - Celery and celery worker autoscaling
9a - Fargate service that is autoscaled between 0 and `N` Fargate tasks for a given celery queue
9b - Scheduled Event that triggers a Lambda to make a request to Django backend which collects celery queue metrics and published metrics to CloudWatch using boto3
9c - Lambda event the makes a request to `/api/celery-metrics/`
9d - CloudWatch alarm that is used to scale the Fargate service for a celery queue
9e - Autoscaling group for celery Fargate service
10 - Fargate tasks that run Django management commands such as `migrate` and `collectstatic`. These are triggered from manual GitLab CI jobs using the AWS CLI (3c)
11 - ElastiCache for Redis, used for Caching, Celery Broker, Channels Layer, etc.
12 - Aurora Postgres Serverless
## Local Development
First, copy `.env.template` to a new file in the project's root directory called `.env`. This file will be read by `docker-compose` in the next step. Adjust any of the values in this file if needed, or add new variables for any secret information you need to pass to docker-compose (or to docker containers).
```sh
docker-compose up
```Open `http://localhost` in your browser.
You can specify environment variables for docker-compose by adding an `.env` file to the root of the project based on `.env.template`.
### Social Authentication Keys
To use social sign on in local development, you will need to create an application with the given provider such as GitHub, Google, Facebook, etc.
#### GitHub
Go to [https://github.com/settings/applications/new](https://github.com/settings/applications/new), and add the following:
- Application Name: A name for the development application, such as `My App Dev`
- Homepage URL: `http://localhost`
- Application description: (optional)
- Authorization callback URL `http://localhost/auth/github/callback` (this route is defined in `quasar/src/router/routes.js`)In the `.env` file, add the `Client ID` of your GitHub OAuth App as the `GITHUB_KEY` variable, and add the `Client Secret` as the `GITHUB_SECRET` variable.
## VuePress Documentation
This project uses VuePress for documentation. To view the documentation site locally, run the following command:
```bash
docker-compose -f compose/docs.yml up --build
```This will make the docs available at `http://localhost:8082/docs/`. Hot-reloading through websockets is supported, so changes will show up as they are saved in your code editor.
### Access Django Shell in Jupyter Notebook
With all containers running, run the following commands:
```
docker exec -it backend bash
# cd notebooks/
# ../manage.py shell_plus --notebook
```or use this single command:
```
docker exec -it backend bash -c 'cd notebooks && ../manage.py shell_plus --notebook'
```