Flask with Docker: Deploying Microservices on Cloud with Kubernetes

Modern web applications are shifting from monolithic architectures to microservices to achieve better scalability, fault isolation, and faster development cycles. Flask, a lightweight Python web framework, is a perfect fit for building microservices. Combined with Docker for containerization and Kubernetes for orchestration, Flask-based microservices can be deployed seamlessly to cloud environments. In this blog, we’ll walk through how to deploy Flask microservices on the cloud using Docker and Kubernetes.


Why Flask for Microservices?

Flask is simple, modular, and flexible—making it an ideal choice for developing microservices. Its minimal overhead allows you to build RESTful APIs quickly and integrate with other services easily. Each microservice can focus on a single responsibility, such as user management, billing, or notifications.


Containerizing Flask Microservices with Docker

Let’s say you have a Flask-based user service:


python


# user_service.py

from flask import Flask, jsonify


app = Flask(__name__)


@app.route('/user/<int:user_id>')

def get_user(user_id):

    return jsonify({"user_id": user_id, "name": "User Example"})

Create a requirements.txt file:


ini


Flask==2.3.2

gunicorn==21.2.0

Create a Dockerfile:


Dockerfile


FROM python:3.11-slim


WORKDIR /app


COPY requirements.txt .

RUN pip install -r requirements.txt


COPY . .


CMD ["gunicorn", "-b", "0.0.0.0:5000", "user_service:app"]

Build and tag the image:


bash


docker build -t user-service .

Deploying to Kubernetes

Once you have multiple microservices (like user-service, order-service, etc.) containerized, the next step is deploying them to Kubernetes.


Step 1: Push Docker Images to Container Registry

Tag and push the images to Docker Hub or a cloud container registry like Google Container Registry (GCR) or Amazon ECR.


bash


docker tag user-service gcr.io/YOUR_PROJECT/user-service

docker push gcr.io/YOUR_PROJECT/user-service


Step 2: Create Kubernetes Manifests

Here’s an example deployment file for the user service:


yaml

Copy

Edit

# user-deployment.yaml

apiVersion: apps/v1

kind: Deployment

metadata:

  name: user-service

spec:

  replicas: 2

  selector:

    matchLabels:

      app: user-service

  template:

    metadata:

      labels:

        app: user-service

    spec:

      containers:

      - name: user-service

        image: gcr.io/YOUR_PROJECT/user-service

        ports:

        - containerPort: 5000

And expose it:


yaml

Copy

Edit

# user-service.yaml

apiVersion: v1

kind: Service

metadata:

  name: user-service

spec:

  type: ClusterIP

  selector:

    app: user-service

  ports:

    - protocol: TCP

      port: 80

      targetPort: 5000

Apply the files:


bash

Copy

Edit

kubectl apply -f user-deployment.yaml

kubectl apply -f user-service.yaml


Step 3: Deploy to Cloud Kubernetes Services

You can deploy your Kubernetes cluster on cloud platforms like:

Google Kubernetes Engine (GKE)

Amazon Elastic Kubernetes Service (EKS)

Azure Kubernetes Service (AKS)

Use CLI tools (gcloud, aws eks, or az aks) to create and manage your clusters. After provisioning, use kubectl to deploy services and monitor their status.


Monitoring and Scaling

Use Kubernetes Horizontal Pod Autoscaler for automatic scaling.

Use Prometheus and Grafana for monitoring.

Configure Ingress controllers for API gateway-style routing.

Store secrets securely using Kubernetes Secrets or services like AWS Secrets Manager.


Conclusion

By combining Flask with Docker and Kubernetes, you can deploy microservices on the cloud with ease and efficiency. Docker simplifies packaging and portability, while Kubernetes handles deployment, scaling, and management. This stack empowers development teams to build modular, resilient, and cloud-ready applications—perfect for the dynamic demands of modern software systems.

Learn FullStack Python Training Course

Read More : Fullstack Python: Managing Secrets in Cloud Environments with AWS Secrets Manager

Read More : Fullstack Python: Deploying Flask with Docker and Google Kubernetes Engine

Read More : Fullstack Flask: Implementing Multi-Cloud Deployment for High Availability

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