In this series, you'll learn to develop an app using Node.js, deploy it to a local Kubernetes cluster, scale it, and deploy it to Amazon Web Services on a production-grade Kubernetes cluster.

And in this particular article, you'll cover the development of an app you'll use throughout this series.

Here's how the development will unfold.

Knote — a note taking app
Standard Express.js stack
Connecting a database
Saving and retrieving notes
Rendering Markdown to HTML
Uploading pictures
Deploying apps with containers
Linux containers
Containerising the app
Running the container
Uploading the container image to a container registry
Recap and next steps

Knote — a note-taking app

The essential ingredient to learning how to deploy and scale applications in Kubernetes is the application itself.

As you'll learn throughout this course, mastering Kubernetes doesn't guarantee that you have zero incidents in production.

If your application isn't designed to be resilient and observable, the risk of downtime in production is high — even if you're using Kubernetes.

Learning how to design and architect applications that leverage Kubernetes is crucial.

And that's precisely what you will learn in this part of the course.

Now you will develop a small application for note-taking similar to Evernote and Google Keep.

The app should let you:

Record notes and
Attach images to your notes.

Notes aren't lost when the app is killed or stopped.

So you will use a database to store the content.

Here is what the app looks like:

The app is available in this repository.

Go and check out the code with:

git clone https://github.com/learnk8s/knote-js
cd knote-js/01

You can install and start it with:

npm install
node index.js

The app will be hosted on http://localhost:3000.

Try to upload a picture — you should see a link inserted in the text box.

And when you publish the note, the picture should be displayed in the rendered note.

There're a couple of code choices worth discussing.

Standard Express.js stack

Express and Pug are two popular choices when it comes to web servers and templating engines in Node.js.

This is what a basic template for a Node.js project with Express and Pug looks like.

Now, create an index.js file with the following content:

const path = require('path')
const express = require('express')

const app = express()
const port = process.env.PORT || 3000

async function start() {
  app.set('view engine', 'pug')
  app.set('views', path.join(__dirname, 'views'))
  app.use(express.static(path.join(__dirname, 'public')))

  app.listen(port, () => {
    console.log(`App listening on http://localhost:${port}`)
  })
}

start()

You also need a route and view to render the main page.

async function start() {
  // ...
  app.get('/', (req, res) => res.render('index'))
}

You can find the pug template in this repository.

This code is adapted from a simple Express boilerplate app, so it doesn't do anything useful yet.

To enhance it, let's learn to connect it to a database.

Connecting a database

The database will store the notes.

What database should you use? MySQL? Redis?

MongoDB is well-suited for your note-taking application because it's easy to set up and doesn't introduce the overhead of a relational database.

So, go on and install the MongoDB package:

npm install mongodb

Then add the following lines to the beginning of your index.js file:

const MongoClient = require('mongodb').MongoClient
const mongoURL = process.env.MONGO_URL || 'mongodb://localhost:27017/dev'

Now your code needs to connect to the MongoDB server.

You have to consider something important here.

When the app starts, it shouldn't crash because the database isn't ready.

Instead, the app should keep trying to connect to the database until it succeeds.

Kubernetes expects that application components can be started in any order and retrying solves that.

To achieve this, add the following function to your index.js file.

Add the following function to your index.js file:

async function initMongo() {
  console.log('Initialising MongoDB...')
  let success = false
  while (!success) {
    try {
      client = await MongoClient.connect(mongoURL, {
        useNewUrlParser: true,
        useUnifiedTopology: true,
      })
      success = true
    } catch {
      console.log('Error connecting to MongoDB, retrying in 1 second')
      await new Promise(resolve => setTimeout(resolve, 1000))
    }
  }
  console.log('MongoDB initialised')
  return client.db(client.s.options.dbName).collection('notes')
}

With this function, the app will continuously retry to connect to the MongoDB database at the URL.

On a successful connection, it creates a collection called notes.

MongoDB collections are like tables in relational databases — lists of items.

Now you have to call the above function inside the start function in your index.js file:

async function start() {
  const db = await initMongo()
  // ...
}

Note how the await keyword blocks the app's execution until the database is ready.

The next step is to use the database.

Saving and retrieving notes

When the main page of your app loads, two things happen:

All the existing notes are displayed.
Users can create new notes through an HTML form.

Let's address the displaying of existing notes first.

You need a function to retrieve all notes from the database:

async function retrieveNotes(db) {
  const notes = await db.find().toArray()
  const sortedNotes = notes.reverse()
  return sortedNotes
}

The route of the main page is /, so you have to add a corresponding route to your Express app that retrieves all the notes from the database and displays them.

Change the route inside the start function in your index.js file to:

async function start() {
  // ...
  app.get('/', async (req, res) => {
    res.render('index', { notes: await retrieveNotes(db) })
  })
  // ...
}

The above handler calls the retrieveNotes function to get all the notes from the database and then passes them into the index.pug template.

Next, let's address the creation of new notes.

First of all, you need a function that saves a single note in the database:

async function saveNote(db, note) {
  await db.insertOne(note)
}

The form for creating notes is defined in the index.pug template.

Note that it handles both the creation of notes and the uploading of pictures.

You should use Multer, a middleware for multi-part form data, to handle the uploaded data.

Go on and install Multer:

npm install multer

And include it in your code:

const multer = require('multer')

The form submits to the /note route, so you need to add this route to your app:

async function start() {
  // ...
  app.post(
    '/note',
    multer().none(),
    async (req, res) => {
      if (!req.body.upload && req.body.description) {
        await saveNote(db, { description: req.body.description })
        res.redirect('/')
      }
    }
  )
  // ...
}

The above handler calls the saveNote function with the content of the text box, which causes the note to be saved in the database.

It then redirects to the main page so that the newly created note appears immediately on the screen.

Your app is functional now (although not yet complete)!

You can already run your app at this stage.

But to do so, you need to start MongoDB as well.

You can install MongoDB following the instructions in the official MongoDB documentation.

Once MongoDB is installed, create an empty folder data/db and run the following to start a MongoDB server which points the DB path to the folder that you just created:

npm run mongodb -- --dbpath ./data/db

Now run your app with:

npm run start

The app should connect to MongoDB and then listen for requests.

You can access your app on http://localhost:3000.

You should see the main page of the app.

Try to create a note — you should see it displayed on the main page.

Your app seems to work.

But it's not complete yet.

We have not fulfilled the following requirements:

Display formatted markdown text (currently, it only displays verbatim).
Uploading pictures.

Let's work on those next.

Rendering Markdown to HTML

The Markdown notes should be rendered to HTML so that you can read them properly formatted.

Marked is an excellent engine for rendering Markdown to HTML.

As always, install the package first:

npm install marked

And import it into your index.js file:

const { marked } = require('marked')

Then, change the retrieveNotes function as follows (changed lines are highlighted):

async function retrieveNotes(db) {
  const notes = await db.find().toArray()
  const sortedNotes = notes.reverse()
  return sortedNotes.map(it => ({ ...it, description: marked(it.description) }))
}

The new code converts the description of all the notes to HTML before returning them.

Restart the app and access it on http://localhost:3000.

All your notes should now be nicely formatted.

Let's tackle uploading files.

Uploading pictures

When a user uploads a picture, the file should be saved on disk, and a link should be inserted in the text box.

This is similar to how adding pictures on StackOverflow works.

Note that for this to work, the picture upload handler must have access to the text box — this is why picture uploading and note creation are combined in the same form.

For now, the pictures will be stored on the local file system.

You will use Multer to handle the uploaded pictures.

Change the handler for the /note route as follows (changed lines are highlighted):

async function start() {
  // ...
  app.post(
    '/note',
    multer({ dest: path.join(__dirname, 'public/uploads/') }).single('image'),
    async (req, res) => {
      if (!req.body.upload && req.body.description) {
        await saveNote(db, { description: req.body.description })
        res.redirect('/')
      } else if (req.body.upload && req.file) {
        const link = `/uploads/${encodeURIComponent(req.file.filename)}`
        res.render('index', {
          content: `${req.body.description} ![](${link})`,
          notes: await retrieveNotes(db),
        })
      }
    }
  )
  // ...
}

The new code saves uploaded pictures in the public/uploads folder in your app directory and inserts a link to the file into the text box.

Restart your app again and access it on http://localhost:3000.

Try to upload a picture — you should see a link inserted in the text box.

And when you publish the note, the picture should be displayed in the rendered note.

Your app is feature complete now.

Note that you can find the complete code for the app in in this repository.

You just created a simple note-taking app from scratch.

In the next section, you will learn how to package and run it as a Docker container.

Deploying apps with containers

After creating your app, the next step is to deploy it.

There are a few standard ways of deploying an app.

You could deploy the app to a Platform as a Service (PaaS) like Heroku and forget about the underlying infrastructure and dependencies.
Or you could do it the hard way and provision your own VPS, install nvm, create the appropriate users, configure Node.js as well as PM2 to restart the app when it crashes and Nginx to handle TLS and path-based routing.

However, there has recently been a trend to package applications as Linux containers and deploy them to specialised container platforms.

So what are containers?

Linux containers

Linux containers are often compared to shipping containers.

Shipping containers have a standard format, allowing them to isolate goods in one container from goods in another.

Goods that belong together are packed in the same container, and goods that have nothing to do with each other are packed in separate containers.

Linux containers are similar.

However, the "goods" in a Linux container are processes and their dependencies.

Typically, a container contains a single process and its dependencies.

A container contains everything that is needed to run a process.

That means you can run a process without installing any dependency on your machine because the container has all you need.

Furthermore, the process in a container is isolated from everything else around it.

When you run a container, the process isn't aware of the host machine, and it believes that it's the only process running on your computer.

Of course, that isn't true.

Bundling dependency and isolating processes might remind you of virtual machines.

However, containers are different from virtual machines.

The process in a container still executes on the host machine's kernel.

With virtual machines, you run an entire guest operating system on top of your host operating system and the processes that you want to execute on top of that.

Containers are just processes!

How do containers work?

The magic of containers comes from two features in the Linux kernel:

Control groups (cgroups).
Namespaces.

These are low-level Linux primitives.

Control groups limit a process's resources, such as memory and CPU.

You might want to limit your container to only use up to 512 MB of memory and 10% CPU time.

Namespaces limit what a process can see.

You might want to hide the file system of your host machine and instead provide an alternative file system to the container.

You can imagine that those two features are convenient for isolating process.

However, they are very low-level and hard to work with.

Developers created more and more abstractions to get around the sharp edges of cgroups and namespaces.

These abstractions resulted in container systems.

One of the first container systems was LXC.

But the container breakthrough came with Docker, which was released in 2013.

Docker isn't the only Linux container technology. There are other popular projects such as rkt and containerd.

In this section, you will package your application as a Docker container.

Let's get started!

Containerising the app

First, you must install the Docker Community Edition (CE).

You can follow the instructions in the official Docker documentation.

If you're on Windows, you can follow our handy guide on how to install Docker on Windows.

You can verify that Docker is installed correctly with the following command:

docker run hello-world

Hello from Docker!
This message shows that your installation appears to be working correctly.

You're now ready to build Docker containers.

Docker containers are built from Dockerfiles.

A Dockerfile is like a recipe — it defines what goes in a container.

A Dockerfile consists of a sequence of commands.

You can find the complete list of commands in the Dockerfile reference.

Here is a Dockerfile that packages your app into a container image:

FROM node:18.0-slim
COPY . .
RUN npm install
CMD [ "node", "index.js" ]

Go on and save this as Dockerfile in the root directory of your app.

The above Dockerfile includes the following commands:

FROM defines the base layer for the container, in this case, a version of Ubuntu with Node.js installed.
COPY copies your app files into the container.
RUN executes npm install inside the container.
CMD defines the command that should be executed when the container starts.

You can now build a container image from your app with the following command:

docker build -t knote .

Note the following about this command:

-t knote defines the name ("tag") of your container — in this case, your container is just called knote.
. is the location of the Dockerfile and application code — in this case, it's the current directory.

The command executes the steps outlined in the Dockerfile, one by one:

{
  "description": "Layers in containers images",
  "slides": [
    {
      "image": "assets/build-1.svg",
      "description": "The first layer is called the base layer. All subsequent layers are built on top of this."
    },
    {
      "image": "assets/build-2.svg",
      "description": "The `COPY` instruction copies the file on the host inside the container. The action creates a new layer."
    },
    {
      "image": "assets/build-3.svg",
      "description": "A new layer is created when the `RUN` command is executed, and the packages are installed."
    },
    {
      "image": "assets/build-4.svg",
      "description": "The result is a container image made of several layers."
    }
  ]
}

The output is a Docker image.

What is a Docker image?

A Docker image is an archive containing all the files in a container.

You can create many Docker containers from the same Docker image:

Don't believe that Docker images are archives? Save the image locally with docker save knote > knote.tar, then you can run tar -tf knote.tar to inspect it.

You can list all the images on your system with the following command:

docker images
REPOSITORY    TAG         IMAGE ID         CREATED            SIZE
knote         latest      dc2a8fd35e2e     30 seconds ago     165MB
node          12-slim     d9bfca6c7741     2 weeks ago        150MB

You should see the knote image that you built.

You should also see the node:18-slim, which is the base layer of your knote image — it is just an ordinary image as well, and the docker run command downloaded it automatically from Docker Hub.

Docker Hub is a container registry — a place to distribute and share container images.

You packaged your app as a Docker image — let's run it as a container.

Running the container

Remember that your app requires a MongoDB database.

In the previous section, you installed MongoDB on your machine and ran it with the mongod command.

You could do the same now.

But guess what: you can also run MongoDB as a container.

MongoDB is provided as a Docker image named mongo on Docker Hub.

You can run MongoDB without actually "installing" it on your machine.

You can run it with docker run mongo.

But before you do that, you need to connect the containers.

The knote and mongo containers should communicate with each other, but they can do so only if they are on the same Docker network.

So, create a new Docker network as follows:

docker network create knote

Now you can run MongoDB with:

docker run \
  --name=mongo \
  --rm \
  --network=knote mongo

Note the following about this command:

--name defines the name for the container — if you don't specify a name explicitly, then a name is generated automatically
--rm automatically cleans up the container and removes the file system when the container exits
--network represents the Docker network in which the container should run — when omitted, the container runs in the default network
mongo is the name of the Docker image that you want to run

Note that the docker run command automatically downloads the mongo image from Docker Hub if it's not yet present on your machine.

MongoDB is now running.

Now, you can run your app as follows:

docker run \
  --name=knote \
  --rm \
  --network=knote \
  -p 3000:3000 \
  -e MONGO_URL=mongodb://mongo:27017/dev \
  knote

Note the following about this command:

--name defines the name for the container.
--rm automatically cleans up the container and removes the file system when the container exits.
--network represents the Docker network in which the container should run.
-p 3000:3000 publishes port 3000 of the container to port 3000 of your local machine. That means, if you now access port 3000 on your computer, the request is forwarded to port 3000 of the Knote container. You can use forwarding to access the app from your local machine.
-e sets an environment variable inside the container.

Regarding the last point, remember that your app reads the URL of the MongoDB server to connect to from the MONGO_URL environment variable.

If you look closely at the value of MONGO_URL, you see that the hostname is mongo.

Why is it mongo and not an IP address?

mongo is the name you gave to the MongoDB container with the --name=mongo flag.

If you named your MongoDB container foo, then you would need to change the value of MONGO_URL to mongodb://foo:27017.

Containers in the same Docker network can talk to each other by name.

This is made possible by a built-in DNS mechanism.

You should now have two containers running on your machine, knote and mongo.

You can display all running containers with the following command:

docker ps
CONTAINER ID    IMAGE    COMMAND                  PORTS                    NAMES
2fc0a10bf0f1    knote    "node index.js"          0.0.0.0:3001->3000/tcp   knote
41b50740a920    mongo    "docker-entrypoint.s…"   27017/tcp                mongo

Great!

It's time to test your application!

Since you published port 3000 of your container to port 3000 of your local machine, your app is accessible on http://localhost:3000.

Go on and open the URL in your web browser.

You should see your app!

Verify that everything works as expected by creating some notes with pictures.

When you're done experimenting, stop and remove the containers as follows:

docker stop mongo knote
docker rm mongo knote

Uploading the container image to a container registry

Imagine you want to share your app with a friend — how would you go about sharing your container image?

You could save the image to disk and send it to your friend.

But there is a better way.

When you ran the MongoDB container, you specified its Docker Hub ID (mongo), and Docker automatically downloaded the image.

You could create your images and upload them to DockerHub.

If your friend doesn't have the image locally, Docker automatically pulls the image from DockerHub.

There exist other public container registries, such as the GitHub Container Registry — however, Docker Hub is the default registry used by Docker.

To use Docker Hub, you first have to create a Docker ID.

A Docker ID is your Docker Hub username.

Once you have your Docker ID, you have to authorise Docker to connect to the Docker Hub account:

docker login

Before you can upload your image, there is one last thing to do.

Images uploaded to Docker Hub must have a name of the form username/image:tag:

username is your Docker ID.
image is the name of the image.
tag is an optional additional attribute — often, it is used to indicate the version of the image.

To rename your image according to this format, run the following command:

docker tag knote <username>/knote-js:1.0.0

Please replace <username> with your Docker ID, e.g. lyqht/knote-js:1.0.0.

Now you can upload your image to Docker Hub:

docker push <username>/knote-js:1.0.0

Your image is now publicly available as <username>/knote-js:1.0.0 on Docker Hub, and everybody can download and run it.

You can find the one you uploaded at https://hub.docker.com/repository/docker/your_username/knote-js.

You can re-run your app using the new image name to verify this.

docker run \
  --name=mongo \
  --rm \
  --network=knote \
  mongo
docker run \
  --name=knote \
  --rm \
  --network=knote \
  -p 3000:3000 \
  -e MONGO_URL=mongodb://mongo:27017/dev \
  <username>/knote-js:1.0.0

Everything should work exactly as before.

Note that now everybody in the world can run your application by executing the above two commands.

And the app will run on their machine precisely as it runs on yours — without installing any dependencies.

This is the power of containerisation!

Once you're done testing your app, you can stop and remove the containers with:

docker stop mongo knote
docker rm mongo knote

Well done for making it this far!

Recap and next steps

Here's a recap of what you've done so far.

You created an application using Express.js and MongoDB.
You packaged the app as a container using Docker.
You uploaded the container to Docker Hub — a container registry.
You ran the app and the databases locally using Docker.

In the next section, you will learn how to run your containerised application on Kubernetes!

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01_writing_a_note_taking_app.md

01_writing_a_note_taking_app.md

Table of contents

Knote — a note-taking app

Standard Express.js stack

Connecting a database

Saving and retrieving notes

Rendering Markdown to HTML

Uploading pictures

Deploying apps with containers

Linux containers

Containerising the app

Running the container

Uploading the container image to a container registry

Recap and next steps

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01_writing_a_note_taking_app.md

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01_writing_a_note_taking_app.md

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Table of contents

Knote — a note-taking app

Standard Express.js stack

Connecting a database

Saving and retrieving notes

Rendering Markdown to HTML

Uploading pictures

Deploying apps with containers

Linux containers

Containerising the app

Running the container

Uploading the container image to a container registry

Recap and next steps