Congratulations! on your learning on K8s on Day 31
What is Deployment in k8s
A Deployment provides a configuration for updates for Pods and ReplicaSets.
You describe a desired state in a Deployment, and the Deployment Controller changes the actual state to the desired state at a controlled rate. You can define Deployments to create new replicas for scaling or to remove existing Deployments and adopt all their resources with new Deployments.
Today's task let's keep it very simple.
Task-1:
Create one Deployment file to deploy a sample todo-app on K8s using the "Auto-healing" and "Auto-Scaling" feature
apply the deployment to your k8s (minikube) cluster by command
kubectl apply -f deployment.yml
Step 1:- To create a deployment file we need to clone the repository of sample todo-app so let's clone the repository of django-todo-app
git clone <repository URL>
Step 2:- After that build the django-todo-app using this command
docker build . -t nsparthu/django-todo:latest
Step 3:- Now push to docker hub
docker push <docker hub username>/django-todo:latest
Step 4:- Let's create a deployment for the django-todo-app vim deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
labels:
app: todo-app
spec:
replicas: 3
selector:
matchLabels:
app: todo-app
template:
metadata:
labels:
app: todo-app
spec:
containers:
- name: todo-app
image: nsparthu/django-todo
ports:
- containerPort: 8000
Step 4:- Use this command to apply for deployment.yaml file
kubectl apply -f deployment.yaml
This command will read the deployment configuration from the file and create the necessary resources on your Kubernetes cluster. Wait for the deployment to be successfully applied ⬆️
Step 5:- To verify that the deployment is running correctly, use the following command to get the status of the deployment:
kubectl get deployment
Step 6:- Check the status of the pods created by the deployment using the following command:
kubectl get pods
Congratulations you have successfully launched your Kubernetes cluster using Minikube and deploying a django-todo-app with auto-healing and auto-scaling features.
Happy Learning
Thanks For Reading! :)
-Sriparthu💝💥