Building Serverless CRUD apps with Netlify Functions & FaunaDB

Serverless functions seem to be all the rage these days. But why?

Devs are adopting the FAAS (Functions-as-a-Service) because of:

Pay-per-execution pricing: You only pay for the how long your function code runs, not for idle server time.
Scalability: Load balancing, security patches, logging, etc. are all handled by the FAAS provider. That leaves more time for companies to focus on their app instead of the underlying infrastructure.

Most importantly, perhaps, is that serverless functions give frontend developers superpowers.

If you can write JavaScript, you can build out robust backend applications and APIs using simple AWS Lambda functions.

Need to process payments? Functions have your back.

Need to build a backend API? Yep, functions can do that.

Need to send transactional emails/SMS to users? Functions got you.

We’ve previously explored how functions work together with Identity on Netlify, but today we’re going a step further. This post will focus on using functions to build a backend API for a React App.

We will be walking through how you can use FaunaDB with Netlify Functions to build a CRUD (Create, Read, Update, Delete) API.

All the code used in the post can be found here in the repo.

About this application

This application is using React for the frontend, Netlify Functions for API calls, and FaunaDB as the backing database.

faunadb netlify

Setup & Run Locally

Clone down the repository

git clone https://github.com/netlify/netlify-faunadb-example.git

Enter the repo directory
```
cd netlify-faunadb-example
```
Install the dependencies
```
npm install
```
Sign up for a FaunaDB account

https://dashboard.fauna.com/accounts/register
Create a database

In the Fauna Cloud Console:
- Click “New Database”
- Enter “Netlify” as the “Database Name”
- Click “Save”
Create a database access key

In the Fauna Cloud Console:
- Click “Security” in the left navigation
- Click “New Key”
- Make sure that the “Database” field is set to “Netlify”
- Make sure that the “Role” field is set to “Admin”
- Enter “Netlify” as the “Key Name”
- Click “Save”
Copy the database access key’s secret

Save the secret somewhere safe; you won’t get a second chance to see it.
Set your database access secret in your terminal environment

In your terminal, run the following command:
```
export FAUNADB_SERVER_SECRET=YourFaunaDBSecretHere
```
Replace YourFaunaDBSecretHere with the value of the secret that you copied in the previous step.
Bootstrap your FaunaDB collection and indexes
```
npm run bootstrap
```
Run project locally

npm start

TLDR; Quick Deploy

Click the Deploy to Netlify button

Click “Connect to GitHub”. Authorize Netlify, when asked.
Paste your FaunaDB database access secret into the “Your FaunaDB Server Secret” field.
Click “Save & Deploy”. Netlify clones your repo, then builds and deploys your app. All done!

setup steps

Tutorial

Background

This application is using React for the frontend, Netlify Functions for API calls, and FaunaDB as the backing database.

We are going to explore how to get up and running with Netlify Functions and how to deploy your own serverless backend.

1. Create React app

We are using React for this demo app, but you can use whatever you want to manage the frontend.

Into VueJS? Awesome use that.

Miss the days of jQuery? Righto, jQuery away!

Fan of VanillaJS? By all means, have at it!

Install create react app
```
npm install create-react-app -g
```
Create the react app!
```
create-react-app my-app
```

The react app is now setup!

# change directories into my-app
cd my-app

2. Set up FaunaDB

We are using FaunaDB to hold and store all of our todo data.

To setup a FaunaDB account and get the API key we’ll use to scaffold out our todos database, head over to https://dashboard.fauna.com/accounts/register and create a free Fauna Cloud account.

Sign up
Create a key
Name your key and create
Copy this API key for later use, or use the Deploy to Netlify Button and plugin this API key.
Create your FaunaDB database

Set the FaunaDB API key locally in your terminal
```
# on mac
export FAUNADB_SERVER_SECRET=YourFaunaDBKeyHere
# on windows
set FAUNADB_SERVER_SECRET=YourFaunaDBKeyHere
```
Replace YourFaunaDBSecretHere with the value of the secret that you copied in the previous step.

Add the /scripts/bootstrap-fauna-database.js to the root directory of the project. This is an idempotent script that you can run one million times and have the same result (one todos database)

Next up, add the bootstrap command to npm scripts in your package.json file
```
{
  "scripts": {
    "bootstrap": "node ./scripts/bootstrap-fauna-database.js"
  }
}
```
Now we can run the bootstrap command to setup our Fauna database in our FaunaDB account.
```
npm run bootstrap
```
If you log in to the FaunaDB dashboard you will see your todo database.

3. Create a function

Now, let’s create a function for our app and wire that up to run locally.

The functions in our project are going to live in a /functions folder. You can set this to whatever you’d like but we like the /functions convention.

Anatomy of a Lambda function

All AWS Lambda functions have the following signature:

exports.handler = (event, context, callback) => {
  // "event" has information about the path, body, headers, etc. of the request
  console.log('event', event)
  // "context" has information about the lambda environment and user details
  console.log('context', context)
  // The "callback" ends the execution of the function and returns a response back to the caller
  return callback(null, {
    statusCode: 200,
    body: JSON.stringify({
      data: '⊂◉‿◉つ'
    })
  })
}

We are going to use the faunadb npm package to connect to our Fauna Database and create an item.

Setting up functions for local development

Let’s rock and roll.

Create a ./functions directory

# make functions directory
mdkir functions

Install netlify-lambda

Netlify lambda is a tool for locally emulating the serverless function for development and for bundling our serverless function with third party npm modules (if we are using those)
```
npm i netlify-lambda --save-dev
```
To simulate our function endpoints locally, we need to setup a proxy for webpack to use.

In package.json add:

{
  "name": "react-lambda",
  "proxy": {
    "/.netlify/functions": {
      "target": "http://localhost:9000",
      "pathRewrite": {
        "^/\\.netlify/functions": ""
      }
    }
  }
}

This will proxy requests we make to `/.netlify/functions` to our locally-running function server at port 9000.

Add our start & build commands

Let’s go ahead and add our start & build command to npm scripts in package.json. These will let us run things locally and give a command for Netlify to build our app and functions when we are ready to deploy.

We are going to be using the npm-run-all npm module to run our frontend and backend in parallel in the same terminal window.

So install it!

```
npm install npm-run-all --save-dev
```

About npm start

The start:app command will run react-scripts start to run our react app

The start:server command will run netlify-lambda serve functions -c ./webpack.config.js to run our function code locally. The -c webpack-config flag lets us set a custom webpack config to fix a module issue with FaunaDB module.

Running npm start in our terminal will run npm-run-all --parallel start:app start:server to fire them both up at once.

About npm build

The build:app command will run react-scripts build to run our React app.

The build:server command will run netlify-lambda build functions -c ./webpack.config.js to run our function code locally.

Running npm run build in our terminal will run npm-run-all --parallel build:** to fire them both up at once.

Your package.json should look like

```json
{
  "name": "netlify-fauna",
  "scripts": {
    "👇 ABOUT-bootstrap-command": "💡 scaffold and setup FaunaDB #",
    "bootstrap": "node ./scripts/bootstrap-fauna-database.js",
    "👇 ABOUT-start-command": "💡 start the app and server #",
    "start": "npm-run-all --parallel start:app start:server",
    "start:app": "react-scripts start",
    "start:server": "netlify-lambda serve functions -c ./webpack.config.js",
    "👇 ABOUT-prebuild-command": "💡 before 'build' runs, run the 'bootstrap' command #",
    "prebuild": "echo 'setup faunaDB' && npm run bootstrap",
    "👇 ABOUT-build-command": "💡 build the react app and the serverless functions #",
    "build": "npm-run-all --parallel build:**",
    "build:app": "react-scripts build",
    "build:functions": "netlify-lambda build functions -c ./webpack.config.js",
  },
  "dependencies": {
    "faunadb": "^0.2.2",
    "react": "^16.4.0",
    "react-dom": "^16.4.0",
    "react-scripts": "1.1.4"
  },
  "devDependencies": {
    "netlify-lambda": "^0.4.0",
    "npm-run-all": "^4.1.3"
  },
  "proxy": {
    "/.netlify/functions": {
      "target": "http://localhost:9000",
      "pathRewrite": {
        "^/\\.netlify/functions": ""
      }
    }
  }
}

```

Install FaunaDB and write the create function

We are going to be using the faunadb npm module to call into our todos index in FaunaDB.

So install it in the project.

npm i faunadb --save

Then create a new function file in /functions called todos-create.js

/* code from functions/todos-create.js */
import faunadb from 'faunadb' /* Import faunaDB sdk */

/* configure faunaDB Client with our secret */
const q = faunadb.query
const client = new faunadb.Client({
  secret: process.env.FAUNADB_SECRET
})

/* export our lambda function as named "handler" export */
exports.handler = (event, context, callback) => {
  /* parse the string body into a useable JS object */
  const data = JSON.parse(event.body)
  console.log("Function `todo-create` invoked", data)
  const todoItem = {
    data: data
  }
  /* construct the fauna query */
  return client.query(q.Create(q.Ref("classes/todos"), todoItem))
  .then((response) => {
    console.log("success", response)
    /* Success! return the response with statusCode 200 */
    return callback(null, {
      statusCode: 200,
      body: JSON.stringify(response)
    })
  }).catch((error) => {
    console.log("error", error)
    /* Error! return the error with statusCode 400 */
    return callback(null, {
      statusCode: 400,
      body: JSON.stringify(error)
    })
  })
}

4. Connect the function to the frontend app

Inside of the React app, we can now wire up the /.netlify/functions/todos-create endpoint to an AJAX request.

// Function using fetch to POST to our API endpoint
function createTodo(data) {
  return fetch('/.netlify/functions/todos-create', {
    body: JSON.stringify(data),
    method: 'POST'
  }).then(response => {
    return response.json()
  })
}

// Todo data
const myTodo = {
  title: 'My todo title',
  completed: false,
}

// create it!
createTodo(myTodo).then((response) => {
  console.log('API response', response)
  // set app state
}).catch((error) => {
  console.log('API error', error)
})

Requests to /.netlify/function/[Function-File-Name] will work seamlessly on localhost and on the live site because we are using the local proxy with webpack.

We will be skipping over the rest of the frontend parts of the app because you can use whatever framework you’d like to build your application.

All the demo React frontend code is available here.

5. Finishing the backend Functions

So far we have created our todo-create function and we’ve seen how we make requests to our live function endpoints. It’s now time to add the rest of our CRUD functions to manage our todos.

Read Todos by ID

Then create a new function file in /functions called todos-read.js

/* code from functions/todos-read.js */
import faunadb from 'faunadb'
import getId from './utils/getId'

const q = faunadb.query
const client = new faunadb.Client({
  secret: process.env.FAUNADB_SECRET
})

exports.handler = (event, context, callback) => {
  const id = getId(event.path)
  console.log(`Function 'todo-read' invoked. Read id: ${id}`)
  return client.query(q.Get(q.Ref(`classes/todos/${id}`)))
  .then((response) => {
    console.log("success", response)
    return callback(null, {
      statusCode: 200,
      body: JSON.stringify(response)
    })
  }).catch((error) => {
    console.log("error", error)
    return callback(null, {
      statusCode: 400,
      body: JSON.stringify(error)
    })
  })
}

Read All Todos

Then create a new function file in /functions called todos-read-all.js

/* code from functions/todos-read-all.js */
import faunadb from 'faunadb'

const q = faunadb.query
const client = new faunadb.Client({
  secret: process.env.FAUNADB_SECRET
})

exports.handler = (event, context, callback) => {
  console.log("Function `todo-read-all` invoked")
  return client.query(q.Paginate(q.Match(q.Ref("indexes/all_todos"))))
  .then((response) => {
    const todoRefs = response.data
    console.log("Todo refs", todoRefs)
    console.log(`${todoRefs.length} todos found`)
    // create new query out of todo refs. http://bit.ly/2LG3MLg
    const getAllTodoDataQuery = todoRefs.map((ref) => {
      return q.Get(ref)
    })
    // then query the refs
    return client.query(getAllTodoDataQuery).then((ret) => {
      return callback(null, {
        statusCode: 200,
        body: JSON.stringify(ret)
      })
    })
  }).catch((error) => {
    console.log("error", error)
    return callback(null, {
      statusCode: 400,
      body: JSON.stringify(error)
    })
  })
}

Update todo by ID

Then create a new function file in /functions called todos-update.js

/* code from functions/todos-update.js */
import faunadb from 'faunadb'
import getId from './utils/getId'

const q = faunadb.query
const client = new faunadb.Client({
  secret: process.env.FAUNADB_SECRET
})

exports.handler = (event, context, callback) => {
  const data = JSON.parse(event.body)
  const id = getId(event.path)
  console.log(`Function 'todo-update' invoked. update id: ${id}`)
  return client.query(q.Update(q.Ref(`classes/todos/${id}`), {data}))
  .then((response) => {
    console.log("success", response)
    return callback(null, {
      statusCode: 200,
      body: JSON.stringify(response)
    })
  }).catch((error) => {
    console.log("error", error)
    return callback(null, {
      statusCode: 400,
      body: JSON.stringify(error)
    })
  })
}

Delete by ID

Then create a new function file in /functions called todos-delete.js

/* code from functions/todos-delete.js */
import faunadb from 'faunadb'
import getId from './utils/getId'

const q = faunadb.query
const client = new faunadb.Client({
  secret: process.env.FAUNADB_SECRET
})

exports.handler = (event, context, callback) => {
  const id = getId(event.path)
  console.log(`Function 'todo-delete' invoked. delete id: ${id}`)
  return client.query(q.Delete(q.Ref(`classes/todos/${id}`)))
  .then((response) => {
    console.log("success", response)
    return callback(null, {
      statusCode: 200,
      body: JSON.stringify(response)
    })
  }).catch((error) => {
    console.log("error", error)
    return callback(null, {
      statusCode: 400,
      body: JSON.stringify(error)
    })
  })
}

Delete batch todos

Then create a new function file in /functions called todos-delete-batch.js

/* code from functions/todos-delete-batch.js */
import faunadb from 'faunadb'
import getId from './utils/getId'

const q = faunadb.query
const client = new faunadb.Client({
  secret: process.env.FAUNADB_SECRET
})

exports.handler = (event, context, callback) => {
  const data = JSON.parse(event.body)
  console.log('data', data)
  console.log("Function `todo-delete-batch` invoked", data.ids)
  // construct batch query from IDs
  const deleteAllCompletedTodoQuery = data.ids.map((id) => {
    return q.Delete(q.Ref(`classes/todos/${id}`))
  })
  // Hit fauna with the query to delete the completed items
  return client.query(deleteAllCompletedTodoQuery)
  .then((response) => {
    console.log("success", response)
    return callback(null, {
      statusCode: 200,
      body: JSON.stringify(response)
    })
  }).catch((error) => {
    console.log("error", error)
    return callback(null, {
      statusCode: 400,
      body: JSON.stringify(error)
    })
  })
}

After we deploy all these functions, we will be able to call them from our frontend code with these fetch calls:

/* Frontend code from src/utils/api.js */
/* Api methods to call /functions */

const create = (data) => {
  return fetch('/.netlify/functions/todos-create', {
    body: JSON.stringify(data),
    method: 'POST'
  }).then(response => {
    return response.json()
  })
}

const readAll = () => {
  return fetch('/.netlify/functions/todos-read-all').then((response) => {
    return response.json()
  })
}

const update = (todoId, data) => {
  return fetch(`/.netlify/functions/todos-update/${todoId}`, {
    body: JSON.stringify(data),
    method: 'POST'
  }).then(response => {
    return response.json()
  })
}

const deleteTodo = (todoId) => {
  return fetch(`/.netlify/functions/todos-delete/${todoId}`, {
    method: 'POST',
  }).then(response => {
    return response.json()
  })
}

const batchDeleteTodo = (todoIds) => {
  return fetch(`/.netlify/functions/todos-delete-batch`, {
    body: JSON.stringify({
      ids: todoIds
    }),
    method: 'POST'
  }).then(response => {
    return response.json()
  })
}

export default {
  create: create,
  readAll: readAll,
  update: update,
  delete: deleteTodo,
  batchDelete: batchDeleteTodo
}

Wrapping Up

That’s it. You now have your own CRUD API using Netlify Functions and FaunaDB.

As you can see, functions can be extremely powerful when combined with a cloud database!

The sky is the limit on what you can build with the JAMstack and we’d love to hear about what you make. Give us a shout about it on Twitter

Next Steps

This example can be improved with users/authentication. Next steps to build out the app would be:

Add in the concept of users for everyone to have their own todo list
Wire up authentication using the JSON web token-based Netlify Identity
Add in due dates to todos and wire up Functions to notify users via email/SMS
File for IPO?

Building Serverless CRUD apps with Netlify Functions & FaunaDB

About this application

Setup & Run Locally

TLDR; Quick Deploy

Tutorial

Background

1. Create React app

2. Set up FaunaDB

3. Create a function

Anatomy of a Lambda function

Setting up functions for local development

4. Connect the function to the frontend app

5. Finishing the backend Functions

Wrapping Up

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About this application

Setup & Run Locally

TLDR; Quick Deploy

Tutorial

Background

1. Create React app

2. Set up FaunaDB

3. Create a function

Anatomy of a Lambda function

Setting up functions for local development

4. Connect the function to the frontend app

5. Finishing the backend Functions

Wrapping Up

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