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Kubetools is a tool and processes for developing and deploying microservices to Kubernetes.

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Kubetools

Kubetools is a tool and processes for developing and deploying microservices to Kubernetes. Say that:

  • You have a bunch of repositories, each containing one or more microservices
  • You want to deploy each of these microservices into one or more Kubernetes clusters
  • You want a single configuration file per project (repository)

And you would like:

  • Development setup should be near-instant - and not require specific K8s knowledge
  • Deployment to production can be automated - and integrated with existing CI tooling

Kubetools provides the tooling required to achieve this, by way of two CLI tools:

  • ktd: generates 100% local development environments using Docker/docker-compose
  • kubetools: deploys projects to Kubernetes, handling any changes/jobs as required

Both of these use a single configuration file, kubetools.yml, for example a basic django app:

name: my-app

containerContexts:
  django_app:
    build:
      registry: my-registry.net
      dockerfile: Dockerfile
    dev:
      volumes:
        - ./:/opt/django_app

upgrades:
  - name: Upgrade database
    containerContext: django_app
    command: [./manage.py, migrate, --noinput]

tests:
  - name: Nosetests
    containerContext: django_app
    command: [./manage.py, test]

deployments:
  my-app-webserver:
    containers:
      uwsgi:
        command: [uwsgi, --ini, /etc/uwsgi.conf]
        containerContext: django_app
        ports:
          - 80
        dev:
          command: [./manage.py, runserver, '0.0.0.0:80']

dependencies:
  mariadb:
    containers:
      mariadb:
        image: mariadb:v10.4.1

With this in your current directory, you can now:

# Bring up a local development environment using docker-compose
ktd up

# Deploy the project to a Kubernetes namespace
kubetools deploy my-namespace

Installing

pip install kubetools

Developing

Install the package in editable mode, with the dev extras:

pip install -e .[dev]

Releasing

  • Update CHANGELOG to add new version and document it
  • In GitHub, create a new release
    • Name the release v<version> (for example v1.2.3)
    • Title the release with a highlight of the changes
    • Copy changes in the release from CHANGELOG.md into the release description TravisCI will package the release and publish it to Pypi

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