/ KUBERNETES, PYTHON

Interacting with Kubernetes Deployments and Services using Python SDK

Interacting with Kubernetes Deployments and Services using Python SDK

Kubernetes has become the de facto choice for a container orchestration platform that automates containerized applications’ deployment, scaling, and management. This article will demonstrate how to interact with Kubernetes Deployments and Services using Python and the official Kubernetes Python client.

Prerequisites

To follow this guide, you will need:

  1. A Kubernetes cluster is up and running.
  2. kubectl is installed and configured to access your cluster.
  3. Python 3.x installed.
  4. Kubernetes Python client.

You can install the Kubernetes Python client library using pip:

pip install kubernetes

We will cover the following topics:

Table of Contents

Listing Kubernetes Deployments

Let’s create a script to list all existing Deployments in the default namespace:

from kubernetes import client, config

def list_deployments(api_instance, namespace):
    # List Deployments
    deployments = api_instance.list_namespaced_deployment(namespace)
    for deployment in deployments.items:
        print("Name: %s, Replicas: %s" % (deployment.metadata.name, deployment.spec.replicas))

def main():
    config.load_kube_config()
    apps_v1 = client.AppsV1Api()
    namespace = "default"
    list_deployments(apps_v1, namespace)

if __name__ == '__main__':
    main()

Run the script using the following:

python list_deployments.py

Listing Kubernetes Services

Now, let’s create a script to list all existing Services in the default namespace:

from kubernetes import client, config

def list_services(api_instance, namespace):
    # List Services
    services = api_instance.list_namespaced_service(namespace)
    for service in services.items:
        print("Name: %s, Cluster IP: %s" % (service.metadata.name, service.spec.cluster_ip))

def main():
    config.load_kube_config()
    namespace = "default"
    core_v1 = client.CoreV1Api()
    list_services(core_v1, namespace)

if __name__ == '__main__':
    main()

Run the script using the following:

python list_services.py

Updating a Kubernetes Deployment

To update a Deployment, you can patch it with the desired changes. In this example, we will update the number of replicas for an existing Deployment:

from kubernetes import client, config

def update_deployment_replicas(api_instance, deployment_name, new_replicas, namespace):
    # Update Deployment replicas
    body = {
        "spec": {
            "replicas": new_replicas
        }
    }
    api_response = api_instance.patch_namespaced_deployment(
        name=deployment_name,
        namespace=namespace,
        body=body
    )
    print("Deployment updated")

def main():
    config.load_kube_config()
    apps_v1 = client.AppsV1Api()

    namespace = "default"
    deployment_name = "nginx-deployment"
    new_replicas = 5
    update_deployment_replicas(apps_v1, deployment_name, new_replicas, namespace)

if __name__ == '__main__':
    main()

Run the script using the following:

python update_deployment.py

Verify updates to the Deployment using the following command:

kubectl get deployments

Updating a Kubernetes Service

To update a Service, you can patch it with the desired changes. In this example, we will update the type of an existing Service:

from kubernetes import client, config

def update_service_type(api_instance, service_name, new_type, namespace):
    # Update Service type
    body = {
        "spec": {
            "type": new_type
        }
    }
    api_response = api_instance.patch_namespaced_service(
        name=service_name,
        namespace=namespace,
        body=body
    )
    print("Service updated")

def main():
    config.load_kube_config()
    core_v1 = client.CoreV1Api()

    namespace = "default"
    service_name = "nginx-service"
    new_type = "NodePort"
    update_service_type(core_v1, service_name, new_type, namespace)

if __name__ == '__main__':
    main()

Run the script using the following:

python update_service.py

Verify updates to the Service using the following command:

kubectl get services

Deleting a Kubernetes Deployment

To delete a Deployment, use the following script:

from kubernetes import client, config

def delete_deployment(api_instance, deployment_name, namespace):
    # Delete Deployment
    api_response = api_instance.delete_namespaced_deployment(
        name=deployment_name,
        namespace=namespace,
        body=client.V1DeleteOptions(propagation_policy="Foreground", grace_period_seconds=5)
    )
    print("Deployment deleted")

def main():
    config.load_kube_config()
    apps_v1 = client.AppsV1Api()

    namespace = "default"
    deployment_name = "nginx-deployment"
    delete_deployment(apps_v1, deployment_name, namespace)

if __name__ == '__main__':
    main()

Run the script using the following:

python delete_deployment.py

Deleting a Kubernetes Service

To delete a Service, use the following script:

from kubernetes import client, config

def delete_service(api_instance, service_name, namespace):
    # Delete Service
    api_response = api_instance.delete_namespaced_service(
        name=service_name,
        namespace=namespace,
        body=client.V1DeleteOptions()
    )
    print("Service deleted")

def main():
    config.load_kube_config()
    core_v1 = client.CoreV1Api()

    namespace = "default"
    service_name = "nginx-service"
    delete_service(core_v1, service_name, namespace)

if __name__ == '__main__':
    main()

Run the script using the following:

python delete_service.py

Assembling the Pieces

After putting all the pieces together, we have a list_deployment.py, list_service.py, update_deployment.py, update_service.py, delete_deployment.py and delete_service.py file containing all the code snippets we discussed previously.

Conclusion

To summarise, we demonstrated how to interact with Kubernetes Deployments and Services using Python and the official Kubernetes Python client. You can now use these examples as a starting point to build more complex interactions and automation for your Kubernetes workloads.

faizan

Faizan Bashir

Principal Engineer | Architecting and building distributed applications in the Cloud | Adventurer

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