Docker, Node.js

Microservices PoC: A Docker Calculator Pt.2

In my previous Microservices PoC post, I attempted to use a calculator to conceptualize microservices. The premise was to look at the calculator as a monolithic application and then break it down into discrete services. The focus was on the Add, Subtract, Multiply, and Divide functions and deploying them in separate docker containers thus creating 4 “microservices.”  This post will take you to the next evolution of where we move towards making these services available outside of my local machine.


  • Docker installed

While not required, I did switch over to using Raspberry Pi’s for my Docker environment.
RPi Docker

As always, let’s create a directory to maintain the files required for this exercise

Next, we will need to create dockerfiles for each of the calculation functions. The significant change in this implementation will be the use of node.js instead of python:


Save this as “Dockerfile”.

Before going any further let’s see what’s going on in this Dockerfile.

Line 1: Use the Ubuntu image for Raspberry Pi architecture

Line2: Update Ubuntu

Line3: Install wget and unzip

Line6: Set the work directory to root

Line7&8: Download Node.js and untar the the file to the /usr/local directory in the image

Line9: Use node package manager to install the Node.js web application framework Express

Line10: Set the Node_Path environment variable

Line11: Add the file add2.js to the docker image

Line12: Execute the node add2.js command in the container

Now that you know what is happening, create three more dockerfiles.  I have used:

  • Dockerfile_m

  • Dockerfile_s

  • Dockerfile_d

The next step is to use your favorite editor to code our calculator functions in node and invoke a webservice for each of the following:

  • add2.js

  • multiply2.js

  • subtract2.js

  • divide2.js

At a high level each one of the node.js applications will listen on a port and expect an http request. If you wanted to add two number, you will go to your web browser and enter:
http://localhost:3000/add/?id=1 15

Once these files have been created, your directory should look something like this:

With all this in place, it’s time to build the images. While still in  the directory, issue the following commands at the prompt:

docker build -t <username>/<repository> .

My build commands look like this:
docker build -t dbaontap/node-add-app .
docker build -f Dockerfile_s -t dbaontap/node-subtract-app .
docker build -f Dockerfile_m -t dbaontap/node-multiply-app .
docker build -f Dockerfile_d -t dbaontap/node-divide-app .

The first time you run these, Docker will check for the existence of the necessary files on your local machine. If it doesn’t find them, it will download them from the appropriate repository, and execute the commands outlined in the Dockerfile.  You will notice that I did not include -f Dockerfile in the “add” example. That is because the default file name is Dockerfile. The other Dockerfiles that are used to build the multiply, subtract, and divide containers need to have the Dockerfile_? explicitly defined. We use the -f flag for that.

docker images at the command prompt should result in the something similar to what we see below:


Once the images are done, you can deploy each image into a container. Since these have a webservice running in them, we need to define a port for each one to listen on as part of the docker run command:

If you recall, in the node.js code, each calculation service is set to listen internally on a port. We will map the same external port to this internal port using the -p flag.

docker run -p 3000:3000 -d dbaontap/node-add-app
docker run -p 3001:3001 -d dbaontap/node-subtract-app
docker run -p 3002:3002 -d dbaontap/node-multiply-app
docker run -p 3003:3003 -d dbaontap/node-divide-app

At this point you will have docker containers listening ports 3000, 3001, 3002, 3003 each with a specific purpose. The video below will demonstrate how to access your add, subtract, multiply, divide services from a web browser.

For the records, the docker containers are running on the Raspberry Pi’s shown in the photo at the beginning of this post, and I was accessing the services from my MacBook Pro. Where do we go from here? The next step is try and deploy something like this to the Oracle Container Cloud Service. As you can see, while overly simplified, containers can offer some interesting way to deliver services.

As always, the code for this can be found on my github site.

***UPDATE: Check out my post on using docker-compose to simplify the deployment process.


Also published on Medium.

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