This documentation outlines the CI/CD deployment strategy for the Kubernetes-client/python project. As of now, CI/CD is not yet set up for this project. The following sections provide details on potential next steps and code snippets that can be utilized for implementing a CI/CD workflow.

Next Steps for Setting Up CI/CD

1. Choose a CI/CD Platform:

   • Evaluate CI/CD tools such as GitHub Actions, GitLab CI/CD, Jenkins, or CircleCI, among others.

2. Define CI/CD Pipelines:

   • Outline the stages of your CI/CD pipeline, such as:
     • Build
     • Test
     • Deploy

3. Create a Docker Image:

   • Use the provided Dockerfile to build a container image for your application.

   Example Dockerfile:

   FROM nbgallery/jupyter-alpine:latest 
   
   RUN pip install git+https://github.com/kubernetes-client/python.git
   
   ENTRYPOINT ["/sbin/tini", "--"]
   CMD ["jupyter", "notebook", "--ip=0.0.0.0"]
   

4. Automate Deployment with Scripts:

   • Create scripts that will automate the deployment process. For instance, you can use a shell script to handle the release lifecycle.

   Example script (scripts/release.sh):

   #!/bin/bash
   
   # Read user inputs or values locally.
   KUBERNETES_BRANCH=${KUBERNETES_BRANCH:-$(python3 "scripts/constants.py" KUBERNETES_BRANCH)}
   CLIENT_VERSION=${CLIENT_VERSION:-$(python3 "scripts/constants.py" CLIENT_VERSION)}
   DEVELOPMENT_STATUS=${DEVELOPMENT_STATUS:-$(python3 "scripts/constants.py" DEVELOPMENT_STATUS)}
   
   # Simple check if version is compliant with https://peps.python.org/pep-0440/
   if [[ ! "$CLIENT_VERSION" =~ ^[0-9A-Za-z+.]+$ ]]; then
       echo "!!! Invalid client version $CLIENT_VERSION"
       exit 1
   fi
   

5. Version Management:

   • Define versioning strategies in your CI/CD pipeline to handle releases effectively. Use the commands listed in the release documentation to create various types of releases (stable, beta, snapshot).

   Example to create a stable release:

   $ KUBERNETES_BRANCH=release-1.${MINOR_VERSION} CLIENT_VERSION=${MINOR_VERSION}.${PATCH_VERSION}.0 DEVELOPMENT_STATUS="5 - Production/Stable" scripts/release.sh
   

6. Integrate Testing:

   • Implement automated testing into your CI/CD workflow. This includes unit tests, integration tests, and performance tests as required by your application.

7. Continuous Monitoring:

   • Set up monitoring for your deployed applications to ensure they are running as expected. Use tools compatible with Kubernetes for alerts and visualizations (e.g., Prometheus, Grafana).

8. Documentation and Communication:

   • Maintain documentation for all CI/CD processes and ensure team members are educated about the processes in place.

Example for Deployment in Python

To create a new deployment within your Kubernetes cluster, you can follow the example in examples/deployment_create.py:

from kubernetes import client, config

def main():
    # Load kube config
    config.load_kube_config()

    # Define the container spec
    container = client.V1Container(
        name="nginx",
        image="nginx:1.14.2",
        ports=[client.V1ContainerPort(container_port=80)]
    )

    # Define the pod template spec
    template = client.V1PodTemplateSpec(
        metadata=client.V1ObjectMeta(labels={"app": "nginx"}),
        spec=client.V1PodSpec(containers=[container])
    )

    # Define the deployment spec
    spec = client.V1DeploymentSpec(
        replicas=3,
        template=template,
        selector={'matchLabels': {"app": "nginx"}}
    )

    # Create the deployment
    dep = client.V1Deployment(
        api_version="apps/v1",
        kind="Deployment",
        metadata=client.V1ObjectMeta(name="nginx-deployment"),
        spec=spec
    )

    # Connect to the API
    api = client.AppsV1Api()
    
    # Create the deployment
    api.create_namespaced_deployment(namespace="default", body=dep)

if __name__ == '__main__':
    main()

By following the guidance here, you can establish a robust CI/CD pipeline that supports the development and deployment of your Kubernetes-client/python configurations.