# Igentify assignment

> Goal: Build a CI/CD pipeline.

## Description

I forked the Platform.sh example Django2 project. I then replaced the
platform.sh specifics with a docker-compose setup (for local usage).
Afterwards I added a Kubernetes deployment and a GitLab CI/CD pipeline.

## Relevant files

`Dockerfile`
`docker-compose.yml`
`.gitlab-ci.yml`
`myapp-deployment.yaml`
`myapp-migrate.yaml`

## Pipeline

The pipeline has 3 steps, build (and upload), test and deploy. The build step
builds the image, tagged as the build run number and uploads it to the registry.
The test step uses the image from the registry, runs it in a Docker network
along side the services described in the step (postgres), runs the migration and
then the tests (no tests so far). This way you always run with a clean database,
test the migrations as well and you can run several such tests simultaneously,
even on the same machine. The last step is deployment, which is run manually.
The step downloads from an S3 bucket the kubectl config then runs the database
migration job, waits for it to finish successfully and finally deploys the
relevant version.

## Assumptions

- An S3 bucket with the `kubectl` config file for the Kubernetes cluster.
- AWS key ID and secret for the IAM user that's allowed access to the S3 bucket
  (key ID in `.gitlab-ci.yml` and the secret in the secret variables through the
webui).
- PostgresQL database deployed to the Kubernetes cluster.
- Kubernetes secret for the postgres password.
- GitLab Docker image registry.
- GitLab runner with access to the Docker daemon.
- Connectivity with Kubernetes cluster.

## Further work

- Running as a limited user insided the container.
- Smaller image size.
- Resource limits.
- Spliting the upload for the `latest` from the build and upload, not uploading
  if the test failed.
- Use seperate Postgres accounts for migrations and the application.