- Sharon Rajendra Manmothe
- Feb 17
- 2 min read
Project: student-feedback-app
This is a simple Flask application that:
Shows Application Version
Shows Environment Mode
Runs inside Docker
Deployed in Kubernetes
Uses Rolling Update
Uses ConfigMap
Everything with real names.
PART 1 – Create Real Application
Step 1: Create Project Folder
On your system:
mkdir student-feedback-app
cd student-feedback-app
Step 2: Create Flask Application
Create file:
from flask import Flask
import os
app = Flask(__name__)
@app.route("/")
def home():
version = os.getenv("APP_VERSION")
mode = os.getenv("APP_MODE")
return f"""
<h2>Student Feedback Application</h2>
<p>Application Version: {version}</p>
<p>Environment Mode: {mode}</p>
"""
if __name__ == "__main__":
app.run(host="0.0.0.0", port=5000)
What we are doing here?
os.getenv() reads environment variables
We are NOT hardcoding version
We are NOT hardcoding mode
These values will come from Kubernetes
This is real DevOps practice.
Step 3: Create requirements.txt
flask
Step 4: Create Dockerfile
FROM python:3.9-slim
WORKDIR /app
COPY . .
RUN pip install -r requirements.txt
EXPOSE 5000
CMD ["python", "app.py"]
What each line does?
Line | Meaning |
FROM | Base image |
WORKDIR | Creates working directory |
COPY | Copies project files |
RUN | Installs flask |
EXPOSE | Opens port 5000 |
CMD | Starts app |
PART 2 – Build Docker Image
Step 5: Build Image
docker build -t student-feedback-app:v1 .
What happens here?
Docker reads Dockerfile
Creates image named student-feedback-app
Version tagged as v1
PART 3 – Deploy to Kubernetes
Step 6: Create Deployment YAML
Create file:
student-feedback-deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
name: student-feedback-deployment
spec:
replicas: 3
selector:
matchLabels:
app: student-feedback
template:
metadata:
labels:
app: student-feedback
spec:
containers:
- name: student-feedback-container
image: student-feedback-app:v1
imagePullPolicy: Never
ports:
- containerPort: 5000
env:
- name: APP_VERSION
value: "1.0"
- name: APP_MODE
value: "development"
Explanation of Important Sections
Real name of deployment:
student-feedback-deployment
replicas: 3
Creates 3 Pods → High Availability
matchLabels
Connects Deployment to Pods
imagePullPolicy: Never
Since we built image locally
env:
We are setting:
APP_VERSION = 1.0
APP_MODE = development
These go inside container as environment variables.
Step 7: Apply Deployment
kubectl apply -f student-feedback-deployment.yaml
Check:
kubectl get pods
You should see 3 running pods.
PART 4 – Expose Application
Step 8: Create Service
kubectl expose deployment student-feedback-deployment --type=NodePort --port=5000
Check service:
kubectl get svc
Open:
You will see:
Student Feedback ApplicationApplication Version: 1.0Environment Mode: development
PART 5 – Rolling Update (Real Example)
Now imagine we improved UI and want version 2.
Step 9: Modify app.py
Change heading to:
<h2>Student Feedback Application - Updated UI</h2>
Build new image:
docker build -t student-feedback-app:v2 .
Step 10: Update Deployment Image
kubectl set image deployment/student-feedback-deployment \
student-feedback-container=student-feedback-app:v2
What happens?
Kubernetes does NOT delete all pods
It replaces pods one by one
Zero downtime
This is Rolling Update
Check:
kubectl rollout status deployment student-feedback-deployment
Rollback (If Something Breaks)
kubectl rollout undo deployment student-feedback-deployment
Kubernetes returns to previous version automatically.
This is real production practice.
PART 6 – Use ConfigMap (Real DevOps Practice)
Now instead of hardcoding APP_MODE inside YAML, we externalize it.
Step 11: Create ConfigMap
kubectl create configmap student-feedback-config \
--from-literal=APP_MODE=production
Check:
kubectl get configmap
Step 12: Update Deployment YAML
Replace APP_MODE section:
- name: APP_MODE
valueFrom:
configMapKeyRef:
name: student-feedback-config
key: APP_MODE
Apply again:
kubectl apply -f student-feedback-deployment.yaml
What happened?
We did NOT rebuild Docker image
We changed only configuration
App now shows:
Environment Mode: production
That is clean DevOps architecture.
