In today’s fast-paced development environment, Docker has become a vital tool for developers, simplifying the process of creating, deploying, and running applications in containers. However, to truly harness the power of Docker, it’s crucial to follow best practices that ensure efficiency, security, and maintainability. In this blog post, we’ll explore ten essential tips to help you use Docker effectively and get the most out of your containerized applications. Whether you’re a seasoned developer or just getting started with Docker, these best practices will guide you towards Docker done right.
1. Always opt for using official docker images when available
Always choose official Docker images when they are available because they are maintained and updated by the software’s creators or trusted contributors. This ensures the images are secure, reliable, and optimized for performance. Official images also come with proper documentation and support, reducing the risk of running into issues. By using official images, you can save time and avoid potential security vulnerabilities that might exist in unofficial or poorly maintained images.
Here’s an example of using an official Docker image for a Node.js application, along with an explanation.
# Use the official Node.js image from Docker Hub
FROM node:14
# Create and change to the app directory
WORKDIR /usr/src/app
# Copy the package.json and package-lock.json files
COPY package*.json ./
# Install the dependencies
RUN npm install
# Copy the rest of the application files
COPY . .
# Expose the port the app runs on
EXPOSE 3000
# Define the command to run the application
CMD ["node", "app.js"]
2. Reduce the number of layers in your docker image as much as possible
Each instruction in a Dockerfile creates a new layer in the image. While layers help with flexibility and caching, having too many can make your image bigger and slower. To reduce layers, combine related commands with && and use multi-stage builds when needed.
Here’s an example of an optimized Dockerfile for a Node.js application using combined commands and multi-stage builds.
# Stage 1: Build the application
FROM node:14 as builder
# Set the working directory
WORKDIR /app
# Copy package.json and package-lock.json and install dependencies
COPY package*.json ./
RUN npm install
# Copy the rest of the application source code
COPY . .
# Build the application (if you have any build step like transpiling TypeScript or building React/Vue/Angular apps)
RUN npm run build
# Stage 2: Create a lightweight runtime image
FROM node:14-slim
# Set the working directory
WORKDIR /app
# Copy the node_modules from the builder stage
COPY --from=builder /app/node_modules ./node_modules
# Copy the built application from the builder stage
COPY --from=builder /app .
# Expose the application port
EXPOSE 3000
# Define the command to run the application
CMD ["node", "app.js"]
Multi-stage builds: This Dockerfile uses two stages: a build stage and a runtime stage.
Stage 1: Build the application
FROM node:14 as builder: Uses the official Node.js image for building the application.WORKDIR /app: Sets the working directory inside the container.COPY package*.json ./: Copies package.json and package-lock.json files to the working directory.RUN npm install: Installs the dependencies.COPY . .: Copies the rest of the application source code.RUN npm run build: Builds the application if you have a build step (e.g., transpiling TypeScript, building React/Vue/Angular apps). If not, this line can be omitted.
Stage 2: Create a lightweight runtime image
FROM node:14-slim: Uses a smaller Node.js image for the final runtime environment.WORKDIR /app: Sets the working directory inside the container.COPY --from=builder /app/node_modules ./node_modules: Copies the node_modules directory from the builder stage to the runtime stage to ensure all dependencies are included.COPY --from=builder /app .: Copies the built application from the builder stage to the runtime stage.EXPOSE 3000: Documents that the application listens on port 3000.CMD ["node", "app.js"]: Defines the command to run the application.
By using multi-stage builds, this Dockerfile ensures that the final image is lightweight and only contains the necessary runtime dependencies. The build stage handles dependency installation and any build steps, while the runtime stage uses a smaller image, resulting in a smaller overall image size and improved performance.
3. Minimize the size of your docker image
Smaller Docker images are better: they use less space, deploy faster. Make them slim by using only what’s needed.
# Use a smaller base image
FROM node:alpine
# Set working directory
WORKDIR /app
# Copy package.json
COPY package.json ./
# Install dependencies
RUN npm install --production
# Copy application code
COPY . .
# Clean up unnecessary files
RUN rm -rf /tmp/* /var/tmp/*
# Start the application
CMD [ "npm", "start" ]
4. Use a .dockerignore file to exclude unnecessary files
We can use a .dockerignore file to remove unnecessary files like node_modules and reduce the size of the image. An example of a Node.js application’s.dockerignore file is provided here:
node_modules
npm-debug.log
.DS_Store
Including these lines in a file called “.dockerignore” instructs Docker to skip certain folders and files during image creation. These are: the “node_modules” directory, npm debug logs, and “.DS_Store” files. This makes the final image smaller and speeds up the building process.
5. Use docker compose for application with multiple container
In simple terms, Docker Compose is a helpful tool for managing applications that use multiple Docker containers. It lets you define everything your application needs, including the different parts (services), how they connect, and where data is stored, all in a single file. This file uses a format called YAML. With Docker Compose, you can start up your entire application environment quickly and easily using just one command.
version: "3.8" # Define the Compose file format version
services:
web: # Define a service named "web"
image: nginx:latest # Use the official nginx image
ports: # Map container port to host machine port
- "80:80" # Expose container port 80 to host port 80 (standard web port)
volumes: # Mount a volume from host machine to container
- ./my-app:/var/www/html # Mount current directory's "my-app" folder to container's "/var/www/html"
database: # Define another service named "database"
image: mysql:8.0 # Use the official MySQL image with version 8.0
environment: # Set environment variables inside the container
MYSQL_ROOT_PASSWORD: secret # Set the root password for MySQL
volumes: # Create a persistent volume for database data
- mysql-data:/var/lib/mysql # Named volume "mysql-data" mounted to "/var/lib/mysql"
volumes:
mysql-data: # Define the persistent volume for database data
Explanation:
- version: This line specifies the version of the Compose file format being used. In this case, it’s “3.8”.
- services: This section defines the services that make up your application. Here, we have two services: “web” and “database”.
web: This service uses the official nginx:latest image, which is a popular web server.
- ports: This section maps the container port (80) to the host machine port (80). This allows you to access the web application running in the container by visiting
http://localhost in your browser.
- volumes: This section mounts a volume from your host machine directory (
./my-app) to the container's document root (/var/www/html). Any changes made to your local files will be reflected in the container.
database: This service uses the official mysql:8.0 image, which provides a MySQL database server.
- environment: This section sets an environment variable named
MYSQL_ROOT_PASSWORD inside the container with the value secret. This is used to configure the MySQL root user password.
- volumes: This section creates a named volume called
mysql-data. This volume persists the data stored by the MySQL database container, even if the container is restarted. The volume is mounted to the container's data directory (/var/lib/mysql).
volumes: This section defines named volumes used by the services. Here, we have a single volume named mysql-data which is used persistently by the database service.
6. Utilize docker volumes to store persistent data
Storing data in containers can be tricky. Docker volumes offer a solution by keeping data outside the container itself. This makes it easier to share and manage that data between containers. We’ll explore how to use Docker volumes to persist data for a database container.
We’ll create a special storage area named “db_data” and connect it to a specific folder within the PostgreSQL container ( /var/lib/postgresql/data ). This way, the database information is saved permanently, even if the container is shut down or deleted.
version: '3'
services:
db:
image: postgres:latest
volumes:
- db_data:/var/lib/postgresql/data
volumes:
db_data:
7. Limit resource usage with Docker resource constraints
Imagine containers like roommates sharing an apartment. By setting limits on how much CPU and memory each container can use (like resource constraints), we prevent any one container from hogging everything and slowing down the others. Now, let’s see how to add these limitations in a Docker Compose file, which is like a set of instructions for managing multiple containers.
version: '3'
services:
app:
image: myapp:latest
deploy:
resources:
limits:
cpus: '0.5'
memory: 512M
This code snippet configures resource constraints for the “app” service. It limits the service to using a maximum of half a CPU core and 512 megabytes of memory. Docker will act like a supervisor, making sure the app container doesn’t use more than its allotted share and slowing it down if it tries.
8. Secure your docker environment
When using Docker for real-world applications, security is crucial. Here are some key practices: keeping Docker updated, using well-regarded starting points for your containers (base images), checking for security weaknesses in images, and only granting containers the minimum permissions they need. Now, let’s explore Docker Content Trust, a tool that helps guarantee the images you use are genuine and haven’t been tampered with.
export DOCKER_CONTENT_TRUST=1
Turning on Docker Content Trust makes Docker extra cautious. It will only accept containers that have been officially signed off on by a trusted source, like a security check. This prevents you from accidentally running fake or modified containers that might contain security risks.
9. Monitor and debug docker containers
Just like any car, your Docker containers need regular checkups to run smoothly. To monitor their performance, resource usage, and any unusual happenings, you can use tools like docker logs, docker stats, and docker events. These tools are like gauges on your dashboard, helping you identify potential problems before they cause issues for your applications.
10. Automate docker workflow with CI/CD
Imagine getting your apps out the door faster and with fewer mistakes! You can achieve this by automating your Docker workflow with CI/CD pipelines. These pipelines are like assembly lines for your code. They can automatically build Docker images, run tests, and deploy your apps to production, all without you needing to do everything manually. This frees up your time and reduces the chance of errors creeping in. Tools like GitHub Actions, GitLab CI/CD, or Jenkins can help you set up these pipelines.
Docker lets you build self-contained environments for running applications. By following these ten best practices, you can ensure your Docker apps are efficient, secure, and easy to manage. From using pre-built images to automating deployments, these practices will help you fine-tune your containerized applications and leverage Docker’s full potential. Happy containerizing!