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    How To Setup Your Local Node.js Development Environment Using Docker

    How To Setup Your Local Node.js Development Environment Using Docker

    Docker is the defacto toolset for building modern applications and setting up a CI/CD pipeline ā€“ helping you build, ship and run your applications in containers on-prem and the cloud.

    Whether you're running on simple compute instances such as AWS EC2 or Azure VMs or something a little fancier like a hosted Kubernetes service like AWS EKS, Azure AKS, Digital Ocean Kluster, Docker's toolset is your new BFF.

    But what about your local development environment? Setting up local dev environments can be frustrating.

    Remember the last time you joined a new development team?

    You needed to configure your local machine, install development tools, pull repositories, fight through out-of-date onboarding docs and READMEs, get everything running and work locally without knowing about the code and its architecture. Oh, and don't forget about databases, caching layers and message queues. These are notoriously hard to set up and develop locally.

    I've never worked at a place where we didn't expect at least a week or more of onboarding for new developers.

    So what are we to do? There is no silver bullet, and these things are hard to do (that's why you get paid the big bucks), but with the help of Docker and its toolset, we can make things a lot easier.

    In Part I of this tutorial, we'll walk through setting up a local development environment for a relatively complex application that uses React for its front end, Node and Express for a couple of micro-services and MongoDb for our datastore. Then, we'll use Docker to build our images and Docker Compose to simplify everything.

    Let's get started.


    To complete this tutorial, you will need:

    Did you know that VSCode has an embedded terminal, which can be accessed using the Ctrl + Tilde (~) Key combination?

    Clone the Code Repository

    Do you know what the difference is between Cloning and Forking?
    Take a look at our article on the topic git fork vs clone; what's the difference

    The first thing we want to do is download the code to our local development machine. Let's do this using the following git command:

    git clone

    Now that we have the source code available locally, let's look at the project structure. First, open the code in your favourite IDE and expand the root level directories. Then, you'll see the following file structure.

    ā”œā”€ā”€ docker-compose.yml
    ā”œā”€ā”€ nginx
    ā”‚   ā”œā”€ā”€ default.conf
    ā”‚   ā””ā”€ā”€ Dockerfile
    ā””ā”€ā”€ node_api
        ā”œā”€ā”€ api
        ā”‚   ā”œā”€ā”€ controller
        ā”‚   ā”‚   ā””ā”€ā”€ rootController.js
        ā”‚   ā”œā”€ā”€ lib
        ā”‚   ā”‚   ā”œā”€ā”€ logger.js
        ā”‚   ā”‚   ā”œā”€ā”€ responder.js
        ā”‚   ā”‚   ā””ā”€ā”€ wrapper.js
        ā”‚   ā””ā”€ā”€ routes
        ā”‚       ā”œā”€ā”€ index.js
        ā”‚       ā””ā”€ā”€ root.js
        ā”œā”€ā”€ app.js
        ā”œā”€ā”€ Dockerfile
        ā”œā”€ā”€ lambda.js
        ā”œā”€ā”€ package.json
        ā”œā”€ā”€ server.js
        ā””ā”€ā”€ yarn.lock

    The application comprises simple microservices that provide a restful APIEven though not consumed as part of the existing skeleton structure; it would use PostgreSQL as its relational database or its datastore. It also has a caching layer that can be consumed, provided by Redis.

    Typically at this point, we would start a local version of PostgreSQL or start looking through the project to find out where our applications will be looking for the database.

    Additionally, we would do the same for Redis.

    For larger applications, where there are multiple microservices, we would start each of our microservices independently and then finally start the UI and hope that the default configuration works.

    It can be very complicated and frustrating, mainly if our micro-services use different versions of node.js and are configured differently.

    To make things worse, when it gets to the deployment, we would need to sit and mess with a webserver, to be able to expose the microservice path.

    So let's walk through making this process easier by dockerizing our application and putting our database into a container.

    Dockerizing Applications

    Docker is a great way to provide consistent development environments. It will allow us to run each of our services and UI in a container. We'll also set up things so that we can develop locally and start our dependencies with one docker command.

    The first thing we want to do is dockerize each of our applications. For larger applications containing multiple microservices, you can even share the same Dockerfile between them.

    Create Dockerfiles

    Create a Dockerfile in the notes-services directory and add the following commands.

    FROM node:lts
    RUN mkdir -p /src && npm i -g nodemon npm
    WORKDIR /src
    ADD package.json package.json
    RUN yarn install
    COPY . /src/
    The above is a very basic Dockerfile to use with node.js. If you are not familiar with the commands, you can start with the Docker getting-started guide. Also, please take a look at their reference documentation.

    Building Docker Images

    Now that we've created our Dockerfile, let's build our image. Make sure you're still located in the node_api directory and run the following command:

    docker build -t node_api .

    $ docker build -t node_api .
    [+] Building 1.1s (11/11) FINISHED                                       
     => [internal] load build definition from Dockerfile                0.0s
     => => transferring dockerfile: 175B                                0.0s
     => [internal] load .dockerignore                                   0.0s
     => => transferring context: 2B                                     0.0s
     => [internal] load metadata for         1.0s
     => [1/6] FROM  0.0s
     => [internal] load build context                                   0.0s
     => => transferring context: 94.79kB                                0.0s
     => CACHED [2/6] RUN mkdir -p /src && npm i -g nodemon npm          0.0s
     => CACHED [3/6] WORKDIR /src                                       0.0s
     => CACHED [4/6] ADD package.json package.json                      0.0s
     => CACHED [5/6] RUN yarn install                                   0.0s
     => CACHED [6/6] COPY . /src/                                       0.0s
     => exporting to image                                              0.0s
     => => exporting layers                                             0.0s
     => => writing image sha256:2a6894296dcce08e11624cd8e3d634bbef62d1  0.0s
     => => naming to                         0.0s

    Now that we have our image built, let's run it as a container and test that it's working.

    docker run --rm -p 8080:8080 --name node node_api yarn start

    Okay, while we have a successful running container, the command prompt is locked to the container's process. Therefore, only the container breaking or us performing some intervention would stop the container.

    Let us open another terminal and go through some docker basics.

    • See running containers: docker ps
      • For this example, I've launched all the containers - which we will cover later in this tutorial
    docker ps
    CONTAINER ID   IMAGE                        COMMAND                  CREATED         STATUS         PORTS                                       NAMES
    1ac9214f991d   node-api-skeleton_nginx      "/docker-entrypoint.ā€¦"   6 seconds ago   Up 6 seconds>80/tcp, :::80->80/tcp           nginx
    85f538fa26af   node-api-skeleton_node_api   "docker-entrypoint.sā€¦"   7 seconds ago   Up 6 seconds   8080/tcp                                    node_api
    662ac5a63f54   redis                        "docker-entrypoint.sā€¦"   8 seconds ago   Up 7 seconds>6379/tcp, :::6379->6379/tcp   redis-cache
    fd3d05b487a5   postgres:alpine              "docker-entrypoint.sā€¦"   8 seconds ago   Up 7 seconds   5432/tcp
    • Find a container ID by container name: docker ps -q --flter ancestor=node_api
    $ docker ps -q --filter ancestor=node_api
    • Stop the container named node_api:
    docker stop $(docker ps -q --filter ancestor=node_api )
    • Stop and delete the container named node_api:
    docker rm $(docker stop $(docker ps -a -q --filter ancestor=node_api

    In our new terminal, let us proceed to stop the node_api container:

    docker stop $(docker ps -q --filter ancestor=node_api )

    Our original terminal has been released, and we can use it again.

    Local Database and Containers

    So. we have seen how we can use only Docker to run our API, but what about the databases and other dependencies?

    Not to stress. Docker Compose to the rescue.

    Let us open the Docker compose file in our editor:

    version: '3'
        restart: always
        image: postgres:alpine
        env_file: ./.env
          - "5432"
          - data:/var/lib/postgresql/data
        container_name: redis-cache
        image: redis
          - '6379:6379'
          - '6379'
        restart: always
        build: ./node_api
        container_name: node_api
          - "8080"
        command: yarn start
          - postgres
          - redis
        env_file: ./.env
          - DB_HOST=postgres
          - VIRTUAL_HOST=proxy.example
        stdin_open: true
        tty: true
          context: ./nginx
        container_name: nginx
          - "80:80"
          - node_api:node_api
        external: false

    As seen above, we use service definitions to define upstream images that supply Postgresql and Redis.

    This structure will download the images, set them up, pass environment variables into them, and run them with connectivity between each other while only exposing the rest API to us on port 80 through Nginx.

    To launch the stack, Ā run docker-compose up -d from your terminal.

    $ docker-compose up -d
    Creating network "node-api-skeleton_default" with the default driver
    Creating redis-cache                  ... done
    Creating node-api-skeleton_postgres_1 ... done
    Creating node_api                     ... done
    Creating nginx                        ... done

    We can now see that without needing to worry about installing any additional dependencies into our code, we can quickly and easily set up a development environment using nothing but Docker, Git and an IDE, such as VSCode.

    Until next time, where we will look at deploying our application in the cloud.