Does Flask Work With Kubernetes?

Fully CompatibleLast verified: 2026-02-20

Flask applications run seamlessly in Kubernetes via containerization; they're a natural fit for cloud-native deployments.

Quick Facts

Compatibility
full
Setup Difficulty
Easy
Official Integration
No — community maintained
Confidence
high
Minimum Versions
Flask: 1.0.0
Kubernetes: 1.14.0

How Flask Works With Kubernetes

Flask and Kubernetes work together perfectly because Kubernetes doesn't care about the application framework—it orchestrates containerized workloads. You package your Flask app in a Docker image, then Kubernetes manages deployment, scaling, and networking. The typical workflow involves creating a Dockerfile, pushing the image to a registry, and defining Kubernetes manifests (Deployment, Service, Ingress) that tell the cluster how many replicas to run and how to expose them. Flask's lightweight nature actually makes it ideal for Kubernetes: it has minimal dependencies, starts quickly, and scales horizontally with ease. The developer experience is straightforward—you write Flask as normal, but add health check endpoints (liveness and readiness probes) so Kubernetes can manage your pods intelligently. Multi-instance deployments work well because Flask is stateless by design, though you'll want to externalize session storage to Redis or a database for production use.

Best Use Cases

Microservices architecture with multiple Flask services communicating via internal Kubernetes DNS
Autoscaling REST APIs that handle variable traffic loads with HPA (Horizontal Pod Autoscaler)
CI/CD pipelines deploying Flask updates with zero downtime using rolling deployments
Distributed data processing workflows where Flask orchestrates jobs across Kubernetes worker nodes

Flask App with Kubernetes Health Checks

bash
pip install flask gunicorn
python
# app.py
from flask import Flask, jsonify
import os

app = Flask(__name__)

@app.route('/health')
def health():
    """Kubernetes liveness and readiness probe endpoint"""
    return jsonify({'status': 'healthy'}), 200

@app.route('/api/hello')
def hello():
    return jsonify({'message': 'Hello from Kubernetes!'}), 200

if __name__ == '__main__':
    app.run(host='0.0.0.0', port=5000)

# Dockerfile
FROM python:3.11-slim
WORKDIR /app
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt
COPY app.py .
EXPOSE 5000
CMD ["gunicorn", "--bind", "0.0.0.0:5000", "--workers", "4", "app:app"]

# k8s-deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: flask-app
spec:
  replicas: 3
  selector:
    matchLabels:
      app: flask-app
  template:
    metadata:
      labels:
        app: flask-app
    spec:
      containers:
      - name: flask
        image: myregistry/flask-app:latest
        ports:
        - containerPort: 5000
        livenessProbe:
          httpGet:
            path: /health
            port: 5000
          initialDelaySeconds: 10
          periodSeconds: 10
        readinessProbe:
          httpGet:
            path: /health
            port: 5000
          initialDelaySeconds: 5
          periodSeconds: 5

Known Issues & Gotchas

critical

Flask's development server (flask run) is single-threaded and unsuitable for Kubernetes production deployments

Fix: Use a production WSGI server like Gunicorn or uWSGI in your Dockerfile; configure it with multiple worker processes matching your CPU requests

warning

Readiness probes failing because health check endpoints aren't implemented

Fix: Add a simple /health endpoint that returns 200 OK; configure Kubernetes probes to hit this endpoint with appropriate delays

warning

Session data lost across pod restarts when stored in-process

Fix: Use Flask-Session with Redis or Memcached as the backend; ensure the backing service is accessible from all pods

info

Container images bloated with unnecessary dependencies increase startup time and pod density

Fix: Use multi-stage Docker builds; pin dependency versions; consider Alpine Linux as base image for smaller footprints

Alternatives

  • Django + Kubernetes: More batteries-included than Flask, better for complex applications with built-in ORM and admin panel
  • FastAPI + Kubernetes: Modern async Python framework with automatic API documentation, faster than Flask for high-concurrency workloads
  • Spring Boot + Kubernetes: JVM-based framework with native Kubernetes support and excellent observability tooling

Resources

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