Devops-exercises/exercises/docker/docker-debugging.md

Docker Scenario-Based Exercises

This file contains scenario-based Docker questions to help DevOps engineers practice real-world troubleshooting and configuration tasks. Each question simulates a practical scenario with a step-by-step answer.

Question 1: Debugging a Docker Container Failure

Question

You’re a DevOps engineer deploying a Node.js application using Docker. You run docker run -d -p 3000:3000 my-node-app, but the container exits immediately. Using docker ps -a, you see the container status as Exited. How would you troubleshoot and resolve this issue?

Answer

To troubleshoot a container exiting immediately:

1. Check Logs: Run docker logs my-node-app to view error messages. Common issues include missing dependencies (e.g., npm install failed) or an incorrect command.
2. Inspect the Container: Use docker inspect my-node-app to check Config.Cmd or Config.Entrypoint. Ensure the command (e.g., node app.js) is valid.
3. Verify the Dockerfile: Check if CMD or ENTRYPOINT is correct, e.g., CMD ["node", "app.js"]. Update and rebuild if needed: docker build -t my-node-app ..
4. Test Interactively: Run docker run -it my-node-app sh to debug manually (e.g., node app.js).
5. Check Resources: Ensure the host has enough memory/CPU using docker stats.

Example Fix: If logs show node: command not found, update the Dockerfile to use FROM node:18, rebuild, and rerun.

Additional Notes

• Always start with docker logs for error clues.
• Use docker ps -a to check container status and ID.
• Common issues include missing dependencies or crashing apps.

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Question 2: Configuring a Multi-Container Application

Question

As a DevOps engineer, you need to deploy a web application with a Node.js backend and a MySQL database using Docker. The Node.js app connects to MySQL on localhost:3306, but running docker run for each container separately fails because they can’t communicate. How would you set up these containers to work together?

Answer

To make the Node.js and MySQL containers communicate:

1. Use Docker Compose: Create a docker-compose.yml file to define and link both services:

   version: '3.8'
   services:
     node-app:
       image: my-node-app
       build: .
       ports:
         - "3000:3000"
       depends_on:
         - mysql-db
       environment:
         - DB_HOST=mysql-db
         - DB_PORT=3306
     mysql-db:
       image: mysql:8.0
       environment:
         - MYSQL_ROOT_PASSWORD=secret
       ports:
         - "3306:3306"
   

2. Run the Application: Execute docker-compose up -d to start both containers. The node-app service connects to mysql-db using the service name (mysql-db) as the hostname, not localhost.
3. Verify Connectivity: Check logs with docker-compose logs node-app to ensure the Node.js app connects to MySQL. If it fails, verify the environment variables and MySQL’s readiness.
4. Alternative Without Compose: Use a custom network:
   • Create a network: docker network create my-app-network
   • Run MySQL: docker run -d --name mysql-db --network my-app-network -e MYSQL_ROOT_PASSWORD=secret mysql:8.0
   • Run Node.js: docker run -d --name node-app --network my-app-network -p 3000:3000 -e DB_HOST=mysql-db my-node-app

Additional Notes

• Docker Compose simplifies multi-container setups by managing networks and dependencies.
• Always set environment variables for database credentials to avoid hardcoding.

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Question 3: Optimizing a Dockerfile for CI/CD

Question

You’re a DevOps engineer integrating a Dockerized Python application into a Jenkins CI/CD pipeline. The Dockerfile builds slowly, causing pipeline delays. How would you optimize the Dockerfile to speed up builds while maintaining functionality?

Answer

To optimize a Dockerfile for faster CI/CD builds:

1. Use a Smaller Base Image: Replace heavy images like python:3.9 with python:3.9-slim to reduce size and download time.

   FROM python:3.9-slim
   

2. Leverage Layer Caching: Order instructions from least to most likely to change. Copy requirements.txt and install dependencies before copying the app code:

   COPY requirements.txt .
   RUN pip install -r requirements.txt
   COPY . .
   

3. Minimize Layers: Combine related commands with && to reduce layers:

   RUN pip install -r requirements.txt && rm -rf /root/.cache/pip
   

4. Use Multi-Stage Builds: If the app needs build tools, use a multi-stage build to keep the final image small:

   FROM python:3.9 AS builder
   COPY requirements.txt .
   RUN pip install -r requirements.txt
   FROM python:3.9-slim
   COPY --from=builder /usr/local/lib/python3.9 /usr/local/lib/python3.9
   COPY . .
   CMD ["python", "app.py"]
   

5. Test in Jenkins: Update the Jenkins pipeline to rebuild the image only when Dockerfile or code changes, using a cached image otherwise:

   pipeline {
       agent any
       stages {
           stage('Build Docker Image') {
               when { changeset "Dockerfile,**.py" }
               steps { sh 'docker build -t my-python-app .' }
           }
       }
   }
   

Additional Notes

• Use .dockerignore to exclude unnecessary files (e.g., .git, tests/) from the build context.
• Monitor build times in Jenkins to confirm improvements.

Contributed by Lahiru Galhena