Scenario-Based Questions And Answers

February 26, 2026

1️⃣ Your Dockerized Django app works locally but fails in production. How do you debug?

Scenario

App runs fine with Docker Compose locally but crashes on server.

Approach

Check running containers
```
docker ps -a
```
Check logs
```
docker logs <container_id>
```
Check environment variables
Verify database connectivity
Check network configuration
Inspect container
```
docker inspect <container_id>
```

Most failures are due to:

Missing env variables
Database host mismatch
Static files not collected
DEBUG=False misconfiguration

2️⃣ Your Celery tasks are not executing. What will you check?

Stack Example

Django
Celery
Redis

Debug Steps

Is Redis running?
```
docker ps
```
Check Celery worker logs
```
docker logs celery_container
```

Verify broker URL:


CELERY_BROKER_URL = "redis://redis:6379/0"

Ensure task is decorated:
```
@shared_task
def send_email():
    pass
```
Confirm worker started:
```
celery -A project worker -l info
```

3️⃣ Production server CPU is 100%. How do you handle it?

Investigation Steps

SSH into server
Check process usage:
```
top
htop
```
Check container stats:
```
docker stats
```

Possible Reasons

Infinite loop in code
Too many Gunicorn workers
Memory leak
High traffic spike

Fix

Adjust Gunicorn workers:
```
workers = (2 × CPU cores) + 1
```
Add autoscaling
Use load balancer
Add caching (Redis)

4️⃣ Deployment failed after merging to main branch. What will you do?

Ideal CI/CD Setup

Using:

GitHub Actions
Jenkins

Debug Plan

Check pipeline logs
Identify failed stage
Rollback to previous stable version
Fix issue in feature branch
Redeploy

Mention:

Blue-Green deployment
Zero downtime deployment
Rollback strategy

5️⃣ Database container crashed and data is lost. Why?

Root Cause

No volume configured.

Bad setup:


db:
  image: postgres:15

Correct setup:


db:
  image: postgres:15
  volumes:
    - postgres_data:/var/lib/postgresql/data

Lesson

Always use Docker volumes for persistent storage.

6️⃣ How would you scale a Django app handling 1M users?

Architecture

Nginx Load Balancer
Multiple Django containers
Managed DB (RDS)
Redis caching
Celery workers
CDN for static files

Cloud Options:

Amazon ECS
Kubernetes

Key Concepts to Mention

Horizontal scaling
Stateless containers
Caching strategy
Read replicas
Rate limiting

7️⃣ Docker image size is 1.5GB. How do you reduce it?

Steps

Use python:3.12-slim
Multi-stage builds
Remove build dependencies
Use .dockerignore
Use --no-cache-dir

Example:


RUN pip install --no-cache-dir -r requirements.txt

8️⃣ How do you secure secrets in production?

Never store in:

Git repository
Docker image

Use:

Environment variables
AWS Secrets Manager
Kubernetes secrets

Cloud example:

AWS Secrets Manager

9️⃣ Users report slow API responses. What will you check?

Debug Strategy

Enable logging
Check DB query performance
Add Django debug toolbar locally
Check slow queries
Add indexing
Add caching

Advanced Fixes

Redis caching
Query optimization
Use connection pooling
Add CDN
Add load balancer

🔟 How do you achieve zero-downtime deployment?

Methods

Blue-Green deployment
Rolling updates
Canary deployment