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1. Introduction

When working with Docker and Docker Compose, managing dependencies can sometimes be tricky. One common issue is when node_modules goes missing after a successful npm install, which can be frustrating and disrupt our development workflow.

In this tutorial, we’ll explore why this issue occurs and provide several practical solutions. We’ll cover different approaches and their respective advantages and disadvantages. Finally, we’ll look into advanced volume management to ensure we manage our node_modules effectively in a Docker environment. Let’s get started!

2. Understanding the Problem

Let’s start by diving into a practical problem scenario. We have a Node.js application set up with Docker and Docker Compose. Our Dockerfile includes instructions on installing npm dependencies, and everything seems to work fine when we build the image. However, when we start the container using docker-compose up, we encounter an error stating that a module cannot be found.

This happens because Docker mounts the worker directory as a volume. During the image build process, it creates and populates node_modules within the container. But when we run docker-compose up, it mounts the worker directory on our host machine over the container’s worker directory. This effectively hides the node_modules directory created during the build process, leading to the missing modules error.

In short, when Docker mounts a volume, it overrides the contents of the corresponding directory in the container. If node_modules isn’t present on the host, it won’t be available in the container, causing the application to fail. This behavior highlights a common pitfall in Docker volume management.

3. An Example Setup

Let’s examine an example application structure to further illustrate this problem and better understand the solutions we’ll discuss.

We have two main components: a web server and a worker. The web server is a Python Flask application, and the worker is a Node.js application that interacts with a queue:

project/
│── web/
│   └─ Dockerfile
│── worker/
│   └─ Dockerfile
└── docker-compose.yml

For this example, our focus will be on the worker component.

Here, our worker’s Dockerfile might look like this:

# worker Dockerfile

FROM node:14

WORKDIR /worker

COPY package.json /worker/
RUN npm install

COPY . /worker/

Then, our docker-compose.yml file might also look like this:

# docker-compose.yml File

version: '3'
services:
  web:
    build: ./web
    ports:
      - "5000:5000"
  worker:
    build: ./worker
    command: npm start
    ports:
      - "9730:9730"
    volumes:
      - ./worker:/worker
    links:
      - redis
  redis:
    image: redis

In this setup, when we run docker-compose build, it installs the npm dependencies and places them in /worker/node_modules inside the container. However, when we run docker-compose up, it mounts the ./worker directory from the host over /worker in the container, hiding the node_modules directory. This results in the application failing to find its dependencies.

This initial setup shows why we encountered the problem. Next, we’ll explore solutions to find a way around the problem.

4. Installing node_modules in a Different Directory

An approach we can use to solve the problem is to install node_modules in a directory, outside the project’s main directory. This avoids conflicts with the host’s directory structure.

To do this, we update our Dockerfile to install node_modules in a different location:

FROM node:14

WORKDIR /install

COPY package.json /install/
RUN npm install

ENV NODE_PATH=/install/node_modules

WORKDIR /worker

COPY . /worker/

In this updated Dockerfile, we temporarily set the working directory to /install. Then, we copy the package.json file and run npm install to install dependencies in /install/node_modules. Afterward, we set the NODE_PATH environment variable to point to /install/node_modules. Lastly, we change the working directory to /worker and copy the application files.

Notably, our docker-compose.yml file remains unchanged.

In this setup, the host’s worker directory remains mapped to the container’s /worker directory. Also, we install node_modules in /install/node_modules, which is unaffected by the volume mapping.

Practically, this method’s advantage is that it’s simple to implement, and there’s no need for additional volumes in docker-compose.yml.

Contrastingly, this method may require changes in how the application resolves module paths and can increase complexity with additional environment variables.

5. Installing Dependencies at Container Startup

Another practical approach is to install dependencies each time the container starts (post-startup npm install). This ensures that node_modules is always up to date without worrying about the volume mappings.

To do this, we need to modify the Dockerfile and the docker-compose.yml file.

First, we adjust the Dockerfile to set up the environment but defer installing dependencies until the container starts:

FROM node:14

WORKDIR /worker

COPY package.json /worker/
COPY . /worker/

CMD ["sh", "-c", "npm install && npm start"]

In this Dockerfile, we copy the package.json and application files to the working directory. Then, the CMD instruction ensures that npm install runs each time the container starts, followed by npm start.

Afterward, we adjust our docker-compose.yml file to run the command before starting the application each time the container launches:

version: '3'
services:
  web:
    build: ./web
    ports:
      - "5000:5000"
  worker:
    build: ./worker
    command: sh -c "npm install && npm start"
    ports:
      - "9730:9730"
    volumes:
      - ./worker:/worker
    links:
      - redis
  redis:
    image: redis

Here, we map the host’s worker directory to the container’s /worker directory. Then, we run npm install before starting the application each time the container launches.

This method’s edge is that it ensures node_modules is always up to date and simplifies dependency management during development.

However, it increases container startup time, as it installs dependencies each time.

6. Using Volumes for node_modules

To manage node_modules effectively in a Docker environment, we can utilize volumes to ensure dependencies are preserved and available to the container. We can do this by combining bind mounts for the source code and named volumes for node_modules.

6.1. Using a Data Volume for node_modules

One effective solution is to use a data volume specifically for node_modules. Docker manages data volumes to persist data outside the container’s lifecycle, making them ideal for directories like node_modules that shouldn’t be overwritten. This method efficiently preserves node_modules across container restarts without being overridden by the host’s directory structure.

Our Dockerfile doesn’t need to change from the initial setup to implement data volume for our sample project.

However, in our docker-compose.yml file, we need to define a separate volume for node_modules:

# docker-compose.yml

version: '3'
services:
  web:
    build: ./web
    ports:
      - "5000:5000"
  worker:
    build: ./worker
    command: npm start
    ports:
      - "9730:9730"
    volumes:
      - ./worker:/worker
      - worker_node_modules:/worker/node_modules
    links:
      - redis
  redis:
    image: redis

volumes:
  worker_node_modules:

In this configuration, we map the host directory ./worker to the container directory /worker. Then, we create a named volume worker_node_modules specifically for the node_modules directory.

When we run docker-compose up now, Docker will use the named volume to store node_modules, preserving its contents even when the container restarts. This setup prevents the host’s worker directory from overwriting the node_modules directory within the container.

Ultimately, the main advantage of this setup is that it ensures node_modules is always available within the container. Also, it preserves dependencies across container restarts.

On the other hand, the disadvantage is that it adds complexity to managing additional volumes and requires updating the docker-compose.yml file.

6.2. Using Bind Mounts and Data Volumes

An advanced volume management technique we can further consider is using bind mounts for the source code and data volumes for dependencies. This method optimizes file management in Docker containers by combining the benefits of both approaches.

Specifically, bind mounts link a directory on the host to a directory in the container, making the host’s files available to the container. This is useful for source code, as changes made on the host are immediately reflected in the container.

Similar to our previous interaction, our Dockerfile doesn’t need to change.

However, we need to modify our docker-compose.yml file to include both bind mounts for the source code and named volumes for node_modules:

version: '3'

services:
  redis:
    image: redis

  worker:
    build: ./worker
    command: npm start
    ports:
      - "9730:9730"
    volumes:
      - ./worker:/worker:rw
      - worker_node_modules:/worker/node_modules
    links:
      - redis

volumes:
  node_modules:

In this configuration, we use a bind mount for the worker directory (./worker:/worker:rw), allowing us to edit source code directly.

This method is very similar to our previous interaction with the data volume. However, it can be more efficient, as code changes are immediately reflected without rebuilding the Docker image.

As for its cons, it can be slightly more complex than simpler solutions as it requires careful volume management and potential cleanup.

7. Handling npm cache for Faster Builds

If we notice that any of the solutions slow down our build process, to optimize our Docker setup further, we can leverage npm‘s caching mechanism to speed up our builds. This is especially useful when dealing with large projects or when multiple developers are working on the same project.

npm cache stores downloaded packages and dependencies, which can be reused in subsequent builds. By caching these dependencies, we avoid re-downloading them every time we build our Docker image, significantly reducing build times.

We can now modify our Dockerfile to utilize npm‘s cache:

# Stage 1: Build
FROM node:14 AS builder
WORKDIR /worker

# Copy package.json and package-lock.json first to leverage the cache
COPY package.json package-lock.json ./

# Install dependencies and cache them
RUN npm install --prefer-offline --no-audit --progress=false

# Copy the rest of the application code
COPY . .

# Stage 2: Runtime
FROM node:14-alpine
WORKDIR /worker
COPY --from=builder /worker .

CMD ["npm", "start"]

In this Dockerfile, we copy package.json and package-lock.json to ensure that, if these files haven’t changed, Docker will use the cached layer. Then, we use the npm install –prefer-offline command, which tells npm to use the local cache as much as possible.

Notably, using the npm cache has several benefits. First, we speed up our Docker image builds by avoiding redundant downloads. It also reduces the amount of data downloaded for network efficiency, which is particularly useful in environments with limited bandwidth.

8. Conclusion

In this article, we explored several solutions to address the issue of node_modules being missing in a Docker volume after a successful npm install when using Docker Compose. We started by understanding the root cause of the problem, i.e., the conflict between the bind-mounted volume and the node_modules directory created during the build process.

Then, we covered the practical solutions, including installing node_modules in a different directory, using named volumes, installing dependencies at runtime, and advanced volume management. Each solution has advantages and trade-offs, allowing us to choose the best fit for our development workflow and project requirements, whether we prefer simplicity, persistence, or immediate updates to our code.

Finally, managing node_modules within Docker containers can be challenging due to the interplay between volumes and the build process. However, with these discussed solutions, we can ensure our Dockerized Node.js applications run smoothly and our development environment remains efficient and productive.

Authors – All

If you have a few years of experience in the DevOps ecosystem, and you're interested in sharing that experience with the community, have a look at our Contribution Guidelines.

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