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This repo is a production ready seed project. The app shows a list of users.

Structure

The client contain an Angular app, built with Angular-Cli, and ngrx to handle state, Angular Material as a design library, and have service worker, and AOT compiled. The app shows the users from the Sanic api.
The server contain a simple Sanic app that expose an api of users. The Python serve through a gunicorn server installed in the container.
There is a postgres service for the database. The database directory contains the automatic backup script.
All the logs are going to stdout and can be collected through any service.
There are built in test that configured to run on travis-ci, and a code coverage analysis via codecov. =======

An opinionated Angular - Django cluster

[][donate-url]

The server directory contain a simple Django app that expose an api of Django users with Django REST framework. The client directory contain an Angular simple app, built with Angular-Cli, ngrx to handle state, Angular Material as a design library, have service worker, and ready to AOT compilation. The simple Angular app show the users from the Django api.

The repo is a production ready app, that uses nginx to serve static files (the client app and static files from the server), and gunicorn for the server (python) stuff. All the parts are in a separate Docker containers and we use kubernetes to manage them.

Pre Requirements

install docker.
Don't know yet.

Installation

Automatic installation of the project with docker, for development.

Run $ docker-compose up to build the docker images and run them.
Open the browser at http://localhost:8000 to see your Django (server) app.
Open the browser at http://localhost:4200 to see your Angular (client) app.

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The client app is built via the cloud build CI on GCP and deployed to the GCP storage. The server app is built via the cloud build CI as a docker image and deployed to a GKE cluster on GCP (managed by Kubernetes). The PostgreSQL database is built via the cloud build CI as a docker image and deployed to a GKE cluster on GCP (managed by Kubernetes).

Production Installation

Deploy the client app:

Create a storage bucket with the name of the Domain you have.
Create a cloud build trigger with the parameters in the screenshot (change the _REGION_NAME to the location of the bucket you created in the previous step).
Now you can deploy your client app by creating a new tag in the v0.0.1/prod/prod format and push it to github (git push --tags).

Deploy the server app:

Create a GKE cluster on GCP.
Create a cloud build trigger with the parameters in the screenshot (change the _REGION_NAME to the location of the GKE cluster you created in step 1).
Connect to the GKE cluster using gcloud container clusters get-credentials prod and then create a tiler using the commands:
kubectl create serviceaccount --namespace kube-system tiller
kubectl create clusterrolebinding tiller-cluster-rule --clusterrole=cluster-admin --serviceaccount=kube-system:tiller
kubectl patch deploy --namespace kube-system tiller-deploy -p '{"spec":{"template":{"spec":{"serviceAccount":"tiller"}}}}'
helm init --service-account tiller --upgrade
Then change the helm permissions by navigate to server/kubernetes in the command line and then write kubectl apply -f helm-permissions.yaml.
Now you can deploy your server app by create a new tag in the v0.0.1/prod/prod format and push it to github (git push --tags).

Create a Cloud DNS record:

Create a Cloud DNS record on GCP. In this record you should add an A record to the kubernetes cluster (the server) and place there your load balancer ip address you get in the "Deploy the server app", and a CNAME record to our Storage bucket (client app) screenshot.

Our Stack

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Docker

Tools we use

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Tests

There is already tests for the server and the client, we currently at +90 percent coverage.

To run the client tests and lint run the commands below in the client directory.

npm run lint
npm run test

To run the server tests and lint run the commands below in the server directory.

pycodestyle --show-source --max-line-length=120 --show-pep8 .
python manage.py test

Load Tests

We also write some tests for doing load test with locust, you can find it under server/locustfile.py.

To do a load test just install locust (it's in the requirements.txt file) go to server directory and run

locust --host=http://localhost

Then open up Locust’s web interface http://localhost:8089.

Rolling Updates

To update any of the containers that are in a service with a new image just create a new image, for example

docker build -t server:v2 .

And then update the service with the new image

docker service update --image server:v2 prod_server

Database Backups

Each day a backup of the PostgreSQL database will be created. The daily backups are rotated weekly, so maximum 7 backup files will be at the daily directory at once.

Each Saturday morning a weekly backup will be created at the weekly directory. The weekly backups are rotated on a 5 week cycle.

Each month at the 1st of the month a monthly backup will be created at the monthly directory. Monthly backups are NOT rotated

The backups are saved at `/var/backups/postgres` at the host machine via a shared volume. It can be configured in the `docker-compose.yml` at `volumes` section of the `database` service.

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Contribute

Just fork and do a pull request (;

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b72a69f (Update dependencies (#20)) [donate-url]: https://www.paypal.me/nirgn/2

License

nirgn975/angular-sanic-seed-project

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