Dylan  Iqbal

Dylan Iqbal

1570765619

How to set-up a powerful API with Nodejs, GraphQL, MongoDB, Hapi, and Swagger

Separating your frontend and backend has many advantages:

  • The biggest reason why reusable APIs are popular — APIs allow you to consume data from a web client, mobile app, desktop app — any client really.
  • Separation of concerns. Long gone are the days where you have one monolithic-like app where everything is bundled together. Imagine you have an extremely convoluted application. Your only option is to hire extremely experienced/senior developers due to the natural complexity.

I’m all for hiring juniors and training your staff, and that’s exactly why you should separate concerns. With separation of concerns, you can reduce the complexity of your application by splitting responsibilities into “micro-services” where each team is specialized in their micro-service.

As mentioned above, the on-boarding/ramp-up process is much quicker thanks to splitting up responsibilities (backend team, frontend team, dev ops team, and so on)


Forward thinking and getting started

We will be building a very powerful, yet flexible, GraphQL API based on Nodejs with Swagger documentation powered by MongoDB.

The main backbone of our API will be Hapi.js. We will go over all the technology in substantial detail.

At the very end, we will have a very powerful GraphQL API with great documentation.

The cherry on top will be our integration with the client (React, Vue, Angular)


Prerequisites

  • NodeJS installed
  • Basic JavaScript
  • Terminal (any will do, preferably bash-based)
  • Text editor (any will do)
  • MongoDB (install instructions here) — Mac: brew install mongodb

Let’s goo!

Open the terminal and create the project. Inside the project directory we initialize a Node project.

Creating our project

Next, we want to setup our Hapi server, so let’s install the dependencies. You can either use Yarn or NPM.

yarn add hapi nodemon

Before we go on, let’s talk about what hapi.js is and what it can do for us.

hapi enables developers to focus on writing reusable application logic instead of spending time building infrastructure.

Instead of going with Express, we are going with Hapi. In a nutshell, Hapi is a Node framework. The reason why I chose Hapi is rather simple — simplicity and flexibility over boilerplate code_._

Hapi enables us to build our API in a very rapid manner.

Optional: check out this quick crash course on hapi.js:

The second dependency we installed was the good-ole nodemon. Nodemon restarts our server automatically whenever we make changes. It speeds up our development by a big factor.

Let’s open our project with a text editor. I chose Visual Studio Code.

Setting up a Hapi server is very straightforward. Create a index.js file at the root directory with the contents of the following:

  • We require the hapi dependency
  • Secondly, we make a constant called server which creates a new instance of our Hapi server — as the arguments, we pass an object with the port and host options.
  • Third and finally, we create an asynchronous expression called init. Inside the init method, we have another asynchronous method which starts the server. See server.start() — at the bottom we call the init()function.

If you’re unsure about async await — watch this:

Now, if we head over to [http://localhost:4000](http://localhost:4000) we should see the following:

Which is perfectly fine, since the Hapi server expects a route and a handler. More on that in a second.

Let’s quickly add the script to run our server with nodemon. Open package.json and edit the scripts section.

Now we can do the following 😎


Routing

Routing is very intuitive with Hapi. Let’s say you hit / — what would you expect to happen? There are three main components in play here.

  • What’s the path? — path
  • What’s the HTTP method? Is it a GET — POST or something else? — method
  • What will happen if that route is reached? — handler

Inside the init method we attached a new method to our server called route with options passed as our argument.

If we refresh our page we should see return value of our root handler

Well done, but there is so much more we can do!


Setting up our database

Right, next up we are going to setup our database. We’re going to use mongodb with mongoose.

Let’s face it, writing MongoDB validation, casting and business logic boilerplate is a drag. That’s why we wrote Mongoose.

The next final ingredient related to our database is mlab. Instead of running mongo on our local computer, we are gonna use a cloud provider like mlab.

The reason why I chose mlab is because of the free plan (useful for prototyping) and how simple it is to use. There are more alternatives out there, and I encourage you to explore all of them ❤

Head over to https://mlab.com/ and signup.

Let’s create our database.

And finally create a user for the database. That will be all we will be editing on mlab.


Connecting mongoose with mlab

Open index.js and add the following lines and credentials. We are basically just telling mongoose which database we want to connect. Make sure to use your credentials.

If you want to brush up your MongoDB skills, here’s a solid series.

If everything went according the plan, we should see ‘connected to database’ in the console.


Wohoo!

Good job! Take a quick break and grab some coffee, we are almost ready to dive into the “cool parts”.


Creating Models

With mongoDB, we follow the convention of models. In other words — data modeling.

It’s a relatively simple concept which you will be able to grasp. Basically we just declare our schema for collections. Think of collections as tables in an SQL database.

Let’s create a directory called models. Inside we will create a file Painting.js

Painting.js is our painting model. It will hold all data related to paintings. Here’s how it will look:

  • We require the mongoose dependency.
  • We declare our PaintingSchema by calling the mongoose schema constructor and passing in the options. Notice how it’s strongly typed: for example the name field can consist of a string, and techniques consists of an array of strings.
  • We export the model and name it Painting

Let’s fetch all of our paintings from the database

First we need to import the Painting model to index.js


Adding new routes

Ideally, we want to have URL endpoints reflecting our actions.

such as /api/v1/paintings — /api/v1/paintings/{id} — and so on.

Let’s start off with a GET and POST route. GET fetches all the paintings and POST adds a new painting.

Notice we modified the route to be an array of objects instead a single object. Also, arrow functions 😊

  • We created a GET for [/api/v1/paintings](http://localhost:4000/api/v1/paintings) path. Inside the handler we are calling the mongoose schema. Mongoose has built-in methods — the handy method we are using is find() which returns all paintings since we’re not passing in any conditions to find by. Therefore it returns all records.
  • We also created a POST for the same path. The reason for that is we’re following REST conventions. Let’s deconstruct (pun intended) the route handler — remember in our Painting schema we declared three fields: name — url — techniques 
  • Here we are just accepting those arguments from the request (we will be doing that with postman in a sec) and passing the request arguments to our mongoose schema. After we’re done passing arguments, we call the save() method on our new record, which saves it to the mlab database.

If we head over to [http://localhost:4000**/api/v1/paintings**](http://localhost:4000/api/v1/paintings) we should see an empty array.

Why empty? Well we haven’t added any paintings just yet. Let’s do that now!

Install postman, it’s available for all platforms.

After installation, open postman.

  • On the left you can see the method options. Change that to POST
  • Next to the POST method we have the URL. That’s the URL we want to send our method to.
  • On the right you can see blue button which sends the request.
  • Below the URL bar we have the options. Click on the body and fill in the fields like in the example.
{
  "name": "Mona Lisa",
  "url": "https://en.wikipedia.org/wiki/Mona_Lisa#/media/File:Mona_Lisa,_by_Leonardo_da_Vinci,_from_C2RMF_retouched.jpg",
  "techniques": ["Portrait"]
}

POST paintings

Alright. Good to go! Let’s open [http://localhost:4000/api/v1/paintings](http://localhost:4000/api/v1/paintings)

Excellent! We still have some way to go! Next up — GraphQL!


Here’s the source code just in case anyone needs it :-)


#node-js #graphql #mongodb #api #hapi-js

What is GEEK

Buddha Community

Hermann  Frami

Hermann Frami

1651383480

A Simple Wrapper Around Amplify AppSync Simulator

This serverless plugin is a wrapper for amplify-appsync-simulator made for testing AppSync APIs built with serverless-appsync-plugin.

Install

npm install serverless-appsync-simulator
# or
yarn add serverless-appsync-simulator

Usage

This plugin relies on your serverless yml file and on the serverless-offline plugin.

plugins:
  - serverless-dynamodb-local # only if you need dynamodb resolvers and you don't have an external dynamodb
  - serverless-appsync-simulator
  - serverless-offline

Note: Order is important serverless-appsync-simulator must go before serverless-offline

To start the simulator, run the following command:

sls offline start

You should see in the logs something like:

...
Serverless: AppSync endpoint: http://localhost:20002/graphql
Serverless: GraphiQl: http://localhost:20002
...

Configuration

Put options under custom.appsync-simulator in your serverless.yml file

| option | default | description | | ------------------------ | -------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------- | | apiKey | 0123456789 | When using API_KEY as authentication type, the key to authenticate to the endpoint. | | port | 20002 | AppSync operations port; if using multiple APIs, the value of this option will be used as a starting point, and each other API will have a port of lastPort + 10 (e.g. 20002, 20012, 20022, etc.) | | wsPort | 20003 | AppSync subscriptions port; if using multiple APIs, the value of this option will be used as a starting point, and each other API will have a port of lastPort + 10 (e.g. 20003, 20013, 20023, etc.) | | location | . (base directory) | Location of the lambda functions handlers. | | refMap | {} | A mapping of resource resolutions for the Ref function | | getAttMap | {} | A mapping of resource resolutions for the GetAtt function | | importValueMap | {} | A mapping of resource resolutions for the ImportValue function | | functions | {} | A mapping of external functions for providing invoke url for external fucntions | | dynamoDb.endpoint | http://localhost:8000 | Dynamodb endpoint. Specify it if you're not using serverless-dynamodb-local. Otherwise, port is taken from dynamodb-local conf | | dynamoDb.region | localhost | Dynamodb region. Specify it if you're connecting to a remote Dynamodb intance. | | dynamoDb.accessKeyId | DEFAULT_ACCESS_KEY | AWS Access Key ID to access DynamoDB | | dynamoDb.secretAccessKey | DEFAULT_SECRET | AWS Secret Key to access DynamoDB | | dynamoDb.sessionToken | DEFAULT_ACCESS_TOKEEN | AWS Session Token to access DynamoDB, only if you have temporary security credentials configured on AWS | | dynamoDb.* | | You can add every configuration accepted by DynamoDB SDK | | rds.dbName | | Name of the database | | rds.dbHost | | Database host | | rds.dbDialect | | Database dialect. Possible values (mysql | postgres) | | rds.dbUsername | | Database username | | rds.dbPassword | | Database password | | rds.dbPort | | Database port | | watch | - *.graphql
- *.vtl | Array of glob patterns to watch for hot-reloading. |

Example:

custom:
  appsync-simulator:
    location: '.webpack/service' # use webpack build directory
    dynamoDb:
      endpoint: 'http://my-custom-dynamo:8000'

Hot-reloading

By default, the simulator will hot-relad when changes to *.graphql or *.vtl files are detected. Changes to *.yml files are not supported (yet? - this is a Serverless Framework limitation). You will need to restart the simulator each time you change yml files.

Hot-reloading relies on watchman. Make sure it is installed on your system.

You can change the files being watched with the watch option, which is then passed to watchman as the match expression.

e.g.

custom:
  appsync-simulator:
    watch:
      - ["match", "handlers/**/*.vtl", "wholename"] # => array is interpreted as the literal match expression
      - "*.graphql"                                 # => string like this is equivalent to `["match", "*.graphql"]`

Or you can opt-out by leaving an empty array or set the option to false

Note: Functions should not require hot-reloading, unless you are using a transpiler or a bundler (such as webpack, babel or typescript), un which case you should delegate hot-reloading to that instead.

Resource CloudFormation functions resolution

This plugin supports some resources resolution from the Ref, Fn::GetAtt and Fn::ImportValue functions in your yaml file. It also supports some other Cfn functions such as Fn::Join, Fb::Sub, etc.

Note: Under the hood, this features relies on the cfn-resolver-lib package. For more info on supported cfn functions, refer to the documentation

Basic usage

You can reference resources in your functions' environment variables (that will be accessible from your lambda functions) or datasource definitions. The plugin will automatically resolve them for you.

provider:
  environment:
    BUCKET_NAME:
      Ref: MyBucket # resolves to `my-bucket-name`

resources:
  Resources:
    MyDbTable:
      Type: AWS::DynamoDB::Table
      Properties:
        TableName: myTable
      ...
    MyBucket:
      Type: AWS::S3::Bucket
      Properties:
        BucketName: my-bucket-name
    ...

# in your appsync config
dataSources:
  - type: AMAZON_DYNAMODB
    name: dynamosource
    config:
      tableName:
        Ref: MyDbTable # resolves to `myTable`

Override (or mock) values

Sometimes, some references cannot be resolved, as they come from an Output from Cloudformation; or you might want to use mocked values in your local environment.

In those cases, you can define (or override) those values using the refMap, getAttMap and importValueMap options.

  • refMap takes a mapping of resource name to value pairs
  • getAttMap takes a mapping of resource name to attribute/values pairs
  • importValueMap takes a mapping of import name to values pairs

Example:

custom:
  appsync-simulator:
    refMap:
      # Override `MyDbTable` resolution from the previous example.
      MyDbTable: 'mock-myTable'
    getAttMap:
      # define ElasticSearchInstance DomainName
      ElasticSearchInstance:
        DomainEndpoint: 'localhost:9200'
    importValueMap:
      other-service-api-url: 'https://other.api.url.com/graphql'

# in your appsync config
dataSources:
  - type: AMAZON_ELASTICSEARCH
    name: elasticsource
    config:
      # endpoint resolves as 'http://localhost:9200'
      endpoint:
        Fn::Join:
          - ''
          - - https://
            - Fn::GetAtt:
                - ElasticSearchInstance
                - DomainEndpoint

Key-value mock notation

In some special cases you will need to use key-value mock nottation. Good example can be case when you need to include serverless stage value (${self:provider.stage}) in the import name.

This notation can be used with all mocks - refMap, getAttMap and importValueMap

provider:
  environment:
    FINISH_ACTIVITY_FUNCTION_ARN:
      Fn::ImportValue: other-service-api-${self:provider.stage}-url

custom:
  serverless-appsync-simulator:
    importValueMap:
      - key: other-service-api-${self:provider.stage}-url
        value: 'https://other.api.url.com/graphql'

Limitations

This plugin only tries to resolve the following parts of the yml tree:

  • provider.environment
  • functions[*].environment
  • custom.appSync

If you have the need of resolving others, feel free to open an issue and explain your use case.

For now, the supported resources to be automatically resovled by Ref: are:

  • DynamoDb tables
  • S3 Buckets

Feel free to open a PR or an issue to extend them as well.

External functions

When a function is not defined withing the current serverless file you can still call it by providing an invoke url which should point to a REST method. Make sure you specify "get" or "post" for the method. Default is "get", but you probably want "post".

custom:
  appsync-simulator:
    functions:
      addUser:
        url: http://localhost:3016/2015-03-31/functions/addUser/invocations
        method: post
      addPost:
        url: https://jsonplaceholder.typicode.com/posts
        method: post

Supported Resolver types

This plugin supports resolvers implemented by amplify-appsync-simulator, as well as custom resolvers.

From Aws Amplify:

  • NONE
  • AWS_LAMBDA
  • AMAZON_DYNAMODB
  • PIPELINE

Implemented by this plugin

  • AMAZON_ELASTIC_SEARCH
  • HTTP
  • RELATIONAL_DATABASE

Relational Database

Sample VTL for a create mutation

#set( $cols = [] )
#set( $vals = [] )
#foreach( $entry in $ctx.args.input.keySet() )
  #set( $regex = "([a-z])([A-Z]+)")
  #set( $replacement = "$1_$2")
  #set( $toSnake = $entry.replaceAll($regex, $replacement).toLowerCase() )
  #set( $discard = $cols.add("$toSnake") )
  #if( $util.isBoolean($ctx.args.input[$entry]) )
      #if( $ctx.args.input[$entry] )
        #set( $discard = $vals.add("1") )
      #else
        #set( $discard = $vals.add("0") )
      #end
  #else
      #set( $discard = $vals.add("'$ctx.args.input[$entry]'") )
  #end
#end
#set( $valStr = $vals.toString().replace("[","(").replace("]",")") )
#set( $colStr = $cols.toString().replace("[","(").replace("]",")") )
#if ( $valStr.substring(0, 1) != '(' )
  #set( $valStr = "($valStr)" )
#end
#if ( $colStr.substring(0, 1) != '(' )
  #set( $colStr = "($colStr)" )
#end
{
  "version": "2018-05-29",
  "statements":   ["INSERT INTO <name-of-table> $colStr VALUES $valStr", "SELECT * FROM    <name-of-table> ORDER BY id DESC LIMIT 1"]
}

Sample VTL for an update mutation

#set( $update = "" )
#set( $equals = "=" )
#foreach( $entry in $ctx.args.input.keySet() )
  #set( $cur = $ctx.args.input[$entry] )
  #set( $regex = "([a-z])([A-Z]+)")
  #set( $replacement = "$1_$2")
  #set( $toSnake = $entry.replaceAll($regex, $replacement).toLowerCase() )
  #if( $util.isBoolean($cur) )
      #if( $cur )
        #set ( $cur = "1" )
      #else
        #set ( $cur = "0" )
      #end
  #end
  #if ( $util.isNullOrEmpty($update) )
      #set($update = "$toSnake$equals'$cur'" )
  #else
      #set($update = "$update,$toSnake$equals'$cur'" )
  #end
#end
{
  "version": "2018-05-29",
  "statements":   ["UPDATE <name-of-table> SET $update WHERE id=$ctx.args.input.id", "SELECT * FROM <name-of-table> WHERE id=$ctx.args.input.id"]
}

Sample resolver for delete mutation

{
  "version": "2018-05-29",
  "statements":   ["UPDATE <name-of-table> set deleted_at=NOW() WHERE id=$ctx.args.id", "SELECT * FROM <name-of-table> WHERE id=$ctx.args.id"]
}

Sample mutation response VTL with support for handling AWSDateTime

#set ( $index = -1)
#set ( $result = $util.parseJson($ctx.result) )
#set ( $meta = $result.sqlStatementResults[1].columnMetadata)
#foreach ($column in $meta)
    #set ($index = $index + 1)
    #if ( $column["typeName"] == "timestamptz" )
        #set ($time = $result["sqlStatementResults"][1]["records"][0][$index]["stringValue"] )
        #set ( $nowEpochMillis = $util.time.parseFormattedToEpochMilliSeconds("$time.substring(0,19)+0000", "yyyy-MM-dd HH:mm:ssZ") )
        #set ( $isoDateTime = $util.time.epochMilliSecondsToISO8601($nowEpochMillis) )
        $util.qr( $result["sqlStatementResults"][1]["records"][0][$index].put("stringValue", "$isoDateTime") )
    #end
#end
#set ( $res = $util.parseJson($util.rds.toJsonString($util.toJson($result)))[1][0] )
#set ( $response = {} )
#foreach($mapKey in $res.keySet())
    #set ( $s = $mapKey.split("_") )
    #set ( $camelCase="" )
    #set ( $isFirst=true )
    #foreach($entry in $s)
        #if ( $isFirst )
          #set ( $first = $entry.substring(0,1) )
        #else
          #set ( $first = $entry.substring(0,1).toUpperCase() )
        #end
        #set ( $isFirst=false )
        #set ( $stringLength = $entry.length() )
        #set ( $remaining = $entry.substring(1, $stringLength) )
        #set ( $camelCase = "$camelCase$first$remaining" )
    #end
    $util.qr( $response.put("$camelCase", $res[$mapKey]) )
#end
$utils.toJson($response)

Using Variable Map

Variable map support is limited and does not differentiate numbers and strings data types, please inject them directly if needed.

Will be escaped properly: null, true, and false values.

{
  "version": "2018-05-29",
  "statements":   [
    "UPDATE <name-of-table> set deleted_at=NOW() WHERE id=:ID",
    "SELECT * FROM <name-of-table> WHERE id=:ID and unix_timestamp > $ctx.args.newerThan"
  ],
  variableMap: {
    ":ID": $ctx.args.id,
##    ":TIMESTAMP": $ctx.args.newerThan -- This will be handled as a string!!!
  }
}

Requires

Author: Serverless-appsync
Source Code: https://github.com/serverless-appsync/serverless-appsync-simulator 
License: MIT License

#serverless #sync #graphql 

Dylan  Iqbal

Dylan Iqbal

1570765619

How to set-up a powerful API with Nodejs, GraphQL, MongoDB, Hapi, and Swagger

Separating your frontend and backend has many advantages:

  • The biggest reason why reusable APIs are popular — APIs allow you to consume data from a web client, mobile app, desktop app — any client really.
  • Separation of concerns. Long gone are the days where you have one monolithic-like app where everything is bundled together. Imagine you have an extremely convoluted application. Your only option is to hire extremely experienced/senior developers due to the natural complexity.

I’m all for hiring juniors and training your staff, and that’s exactly why you should separate concerns. With separation of concerns, you can reduce the complexity of your application by splitting responsibilities into “micro-services” where each team is specialized in their micro-service.

As mentioned above, the on-boarding/ramp-up process is much quicker thanks to splitting up responsibilities (backend team, frontend team, dev ops team, and so on)


Forward thinking and getting started

We will be building a very powerful, yet flexible, GraphQL API based on Nodejs with Swagger documentation powered by MongoDB.

The main backbone of our API will be Hapi.js. We will go over all the technology in substantial detail.

At the very end, we will have a very powerful GraphQL API with great documentation.

The cherry on top will be our integration with the client (React, Vue, Angular)


Prerequisites

  • NodeJS installed
  • Basic JavaScript
  • Terminal (any will do, preferably bash-based)
  • Text editor (any will do)
  • MongoDB (install instructions here) — Mac: brew install mongodb

Let’s goo!

Open the terminal and create the project. Inside the project directory we initialize a Node project.

Creating our project

Next, we want to setup our Hapi server, so let’s install the dependencies. You can either use Yarn or NPM.

yarn add hapi nodemon

Before we go on, let’s talk about what hapi.js is and what it can do for us.

hapi enables developers to focus on writing reusable application logic instead of spending time building infrastructure.

Instead of going with Express, we are going with Hapi. In a nutshell, Hapi is a Node framework. The reason why I chose Hapi is rather simple — simplicity and flexibility over boilerplate code_._

Hapi enables us to build our API in a very rapid manner.

Optional: check out this quick crash course on hapi.js:

The second dependency we installed was the good-ole nodemon. Nodemon restarts our server automatically whenever we make changes. It speeds up our development by a big factor.

Let’s open our project with a text editor. I chose Visual Studio Code.

Setting up a Hapi server is very straightforward. Create a index.js file at the root directory with the contents of the following:

  • We require the hapi dependency
  • Secondly, we make a constant called server which creates a new instance of our Hapi server — as the arguments, we pass an object with the port and host options.
  • Third and finally, we create an asynchronous expression called init. Inside the init method, we have another asynchronous method which starts the server. See server.start() — at the bottom we call the init()function.

If you’re unsure about async await — watch this:

Now, if we head over to [http://localhost:4000](http://localhost:4000) we should see the following:

Which is perfectly fine, since the Hapi server expects a route and a handler. More on that in a second.

Let’s quickly add the script to run our server with nodemon. Open package.json and edit the scripts section.

Now we can do the following 😎


Routing

Routing is very intuitive with Hapi. Let’s say you hit / — what would you expect to happen? There are three main components in play here.

  • What’s the path? — path
  • What’s the HTTP method? Is it a GET — POST or something else? — method
  • What will happen if that route is reached? — handler

Inside the init method we attached a new method to our server called route with options passed as our argument.

If we refresh our page we should see return value of our root handler

Well done, but there is so much more we can do!


Setting up our database

Right, next up we are going to setup our database. We’re going to use mongodb with mongoose.

Let’s face it, writing MongoDB validation, casting and business logic boilerplate is a drag. That’s why we wrote Mongoose.

The next final ingredient related to our database is mlab. Instead of running mongo on our local computer, we are gonna use a cloud provider like mlab.

The reason why I chose mlab is because of the free plan (useful for prototyping) and how simple it is to use. There are more alternatives out there, and I encourage you to explore all of them ❤

Head over to https://mlab.com/ and signup.

Let’s create our database.

And finally create a user for the database. That will be all we will be editing on mlab.


Connecting mongoose with mlab

Open index.js and add the following lines and credentials. We are basically just telling mongoose which database we want to connect. Make sure to use your credentials.

If you want to brush up your MongoDB skills, here’s a solid series.

If everything went according the plan, we should see ‘connected to database’ in the console.


Wohoo!

Good job! Take a quick break and grab some coffee, we are almost ready to dive into the “cool parts”.


Creating Models

With mongoDB, we follow the convention of models. In other words — data modeling.

It’s a relatively simple concept which you will be able to grasp. Basically we just declare our schema for collections. Think of collections as tables in an SQL database.

Let’s create a directory called models. Inside we will create a file Painting.js

Painting.js is our painting model. It will hold all data related to paintings. Here’s how it will look:

  • We require the mongoose dependency.
  • We declare our PaintingSchema by calling the mongoose schema constructor and passing in the options. Notice how it’s strongly typed: for example the name field can consist of a string, and techniques consists of an array of strings.
  • We export the model and name it Painting

Let’s fetch all of our paintings from the database

First we need to import the Painting model to index.js


Adding new routes

Ideally, we want to have URL endpoints reflecting our actions.

such as /api/v1/paintings — /api/v1/paintings/{id} — and so on.

Let’s start off with a GET and POST route. GET fetches all the paintings and POST adds a new painting.

Notice we modified the route to be an array of objects instead a single object. Also, arrow functions 😊

  • We created a GET for [/api/v1/paintings](http://localhost:4000/api/v1/paintings) path. Inside the handler we are calling the mongoose schema. Mongoose has built-in methods — the handy method we are using is find() which returns all paintings since we’re not passing in any conditions to find by. Therefore it returns all records.
  • We also created a POST for the same path. The reason for that is we’re following REST conventions. Let’s deconstruct (pun intended) the route handler — remember in our Painting schema we declared three fields: name — url — techniques 
  • Here we are just accepting those arguments from the request (we will be doing that with postman in a sec) and passing the request arguments to our mongoose schema. After we’re done passing arguments, we call the save() method on our new record, which saves it to the mlab database.

If we head over to [http://localhost:4000**/api/v1/paintings**](http://localhost:4000/api/v1/paintings) we should see an empty array.

Why empty? Well we haven’t added any paintings just yet. Let’s do that now!

Install postman, it’s available for all platforms.

After installation, open postman.

  • On the left you can see the method options. Change that to POST
  • Next to the POST method we have the URL. That’s the URL we want to send our method to.
  • On the right you can see blue button which sends the request.
  • Below the URL bar we have the options. Click on the body and fill in the fields like in the example.
{
  "name": "Mona Lisa",
  "url": "https://en.wikipedia.org/wiki/Mona_Lisa#/media/File:Mona_Lisa,_by_Leonardo_da_Vinci,_from_C2RMF_retouched.jpg",
  "techniques": ["Portrait"]
}

POST paintings

Alright. Good to go! Let’s open [http://localhost:4000/api/v1/paintings](http://localhost:4000/api/v1/paintings)

Excellent! We still have some way to go! Next up — GraphQL!


Here’s the source code just in case anyone needs it :-)


#node-js #graphql #mongodb #api #hapi-js

Shad  Blanda

Shad Blanda

1589082245

Setup a powerful API with Nodejs, GraphQL, MongoDB, Hapi, and Swagger

Set-up a powerful API with Nodejs, GraphQL, MongoDB, Hapi, and Swagger. Separating your frontend and backend has many advantage

#javascript #nodejs #graphql #mongodb #hapi

Top 10 API Security Threats Every API Team Should Know

As more and more data is exposed via APIs either as API-first companies or for the explosion of single page apps/JAMStack, API security can no longer be an afterthought. The hard part about APIs is that it provides direct access to large amounts of data while bypassing browser precautions. Instead of worrying about SQL injection and XSS issues, you should be concerned about the bad actor who was able to paginate through all your customer records and their data.

Typical prevention mechanisms like Captchas and browser fingerprinting won’t work since APIs by design need to handle a very large number of API accesses even by a single customer. So where do you start? The first thing is to put yourself in the shoes of a hacker and then instrument your APIs to detect and block common attacks along with unknown unknowns for zero-day exploits. Some of these are on the OWASP Security API list, but not all.

Insecure pagination and resource limits

Most APIs provide access to resources that are lists of entities such as /users or /widgets. A client such as a browser would typically filter and paginate through this list to limit the number items returned to a client like so:

First Call: GET /items?skip=0&take=10 
Second Call: GET /items?skip=10&take=10

However, if that entity has any PII or other information, then a hacker could scrape that endpoint to get a dump of all entities in your database. This could be most dangerous if those entities accidently exposed PII or other sensitive information, but could also be dangerous in providing competitors or others with adoption and usage stats for your business or provide scammers with a way to get large email lists. See how Venmo data was scraped

A naive protection mechanism would be to check the take count and throw an error if greater than 100 or 1000. The problem with this is two-fold:

  1. For data APIs, legitimate customers may need to fetch and sync a large number of records such as via cron jobs. Artificially small pagination limits can force your API to be very chatty decreasing overall throughput. Max limits are to ensure memory and scalability requirements are met (and prevent certain DDoS attacks), not to guarantee security.
  2. This offers zero protection to a hacker that writes a simple script that sleeps a random delay between repeated accesses.
skip = 0
while True:    response = requests.post('https://api.acmeinc.com/widgets?take=10&skip=' + skip),                      headers={'Authorization': 'Bearer' + ' ' + sys.argv[1]})    print("Fetched 10 items")    sleep(randint(100,1000))    skip += 10

How to secure against pagination attacks

To secure against pagination attacks, you should track how many items of a single resource are accessed within a certain time period for each user or API key rather than just at the request level. By tracking API resource access at the user level, you can block a user or API key once they hit a threshold such as “touched 1,000,000 items in a one hour period”. This is dependent on your API use case and can even be dependent on their subscription with you. Like a Captcha, this can slow down the speed that a hacker can exploit your API, like a Captcha if they have to create a new user account manually to create a new API key.

Insecure API key generation

Most APIs are protected by some sort of API key or JWT (JSON Web Token). This provides a natural way to track and protect your API as API security tools can detect abnormal API behavior and block access to an API key automatically. However, hackers will want to outsmart these mechanisms by generating and using a large pool of API keys from a large number of users just like a web hacker would use a large pool of IP addresses to circumvent DDoS protection.

How to secure against API key pools

The easiest way to secure against these types of attacks is by requiring a human to sign up for your service and generate API keys. Bot traffic can be prevented with things like Captcha and 2-Factor Authentication. Unless there is a legitimate business case, new users who sign up for your service should not have the ability to generate API keys programmatically. Instead, only trusted customers should have the ability to generate API keys programmatically. Go one step further and ensure any anomaly detection for abnormal behavior is done at the user and account level, not just for each API key.

Accidental key exposure

APIs are used in a way that increases the probability credentials are leaked:

  1. APIs are expected to be accessed over indefinite time periods, which increases the probability that a hacker obtains a valid API key that’s not expired. You save that API key in a server environment variable and forget about it. This is a drastic contrast to a user logging into an interactive website where the session expires after a short duration.
  2. The consumer of an API has direct access to the credentials such as when debugging via Postman or CURL. It only takes a single developer to accidently copy/pastes the CURL command containing the API key into a public forum like in GitHub Issues or Stack Overflow.
  3. API keys are usually bearer tokens without requiring any other identifying information. APIs cannot leverage things like one-time use tokens or 2-factor authentication.

If a key is exposed due to user error, one may think you as the API provider has any blame. However, security is all about reducing surface area and risk. Treat your customer data as if it’s your own and help them by adding guards that prevent accidental key exposure.

How to prevent accidental key exposure

The easiest way to prevent key exposure is by leveraging two tokens rather than one. A refresh token is stored as an environment variable and can only be used to generate short lived access tokens. Unlike the refresh token, these short lived tokens can access the resources, but are time limited such as in hours or days.

The customer will store the refresh token with other API keys. Then your SDK will generate access tokens on SDK init or when the last access token expires. If a CURL command gets pasted into a GitHub issue, then a hacker would need to use it within hours reducing the attack vector (unless it was the actual refresh token which is low probability)

Exposure to DDoS attacks

APIs open up entirely new business models where customers can access your API platform programmatically. However, this can make DDoS protection tricky. Most DDoS protection is designed to absorb and reject a large number of requests from bad actors during DDoS attacks but still need to let the good ones through. This requires fingerprinting the HTTP requests to check against what looks like bot traffic. This is much harder for API products as all traffic looks like bot traffic and is not coming from a browser where things like cookies are present.

Stopping DDoS attacks

The magical part about APIs is almost every access requires an API Key. If a request doesn’t have an API key, you can automatically reject it which is lightweight on your servers (Ensure authentication is short circuited very early before later middleware like request JSON parsing). So then how do you handle authenticated requests? The easiest is to leverage rate limit counters for each API key such as to handle X requests per minute and reject those above the threshold with a 429 HTTP response. There are a variety of algorithms to do this such as leaky bucket and fixed window counters.

Incorrect server security

APIs are no different than web servers when it comes to good server hygiene. Data can be leaked due to misconfigured SSL certificate or allowing non-HTTPS traffic. For modern applications, there is very little reason to accept non-HTTPS requests, but a customer could mistakenly issue a non HTTP request from their application or CURL exposing the API key. APIs do not have the protection of a browser so things like HSTS or redirect to HTTPS offer no protection.

How to ensure proper SSL

Test your SSL implementation over at Qualys SSL Test or similar tool. You should also block all non-HTTP requests which can be done within your load balancer. You should also remove any HTTP headers scrub any error messages that leak implementation details. If your API is used only by your own apps or can only be accessed server-side, then review Authoritative guide to Cross-Origin Resource Sharing for REST APIs

Incorrect caching headers

APIs provide access to dynamic data that’s scoped to each API key. Any caching implementation should have the ability to scope to an API key to prevent cross-pollution. Even if you don’t cache anything in your infrastructure, you could expose your customers to security holes. If a customer with a proxy server was using multiple API keys such as one for development and one for production, then they could see cross-pollinated data.

#api management #api security #api best practices #api providers #security analytics #api management policies #api access tokens #api access #api security risks #api access keys

Autumn  Blick

Autumn Blick

1601381326

Public ASX100 APIs: The Essential List

We’ve conducted some initial research into the public APIs of the ASX100 because we regularly have conversations about what others are doing with their APIs and what best practices look like. Being able to point to good local examples and explain what is happening in Australia is a key part of this conversation.

Method

The method used for this initial research was to obtain a list of the ASX100 (as of 18 September 2020). Then work through each company looking at the following:

  1. Whether the company had a public API: this was found by googling “[company name] API” and “[company name] API developer” and “[company name] developer portal”. Sometimes the company’s website was navigated or searched.
  2. Some data points about the API were noted, such as the URL of the portal/documentation and the method they used to publish the API (portal, documentation, web page).
  3. Observations were recorded that piqued the interest of the researchers (you will find these below).
  4. Other notes were made to support future research.
  5. You will find a summary of the data in the infographic below.

Data

With regards to how the APIs are shared:

#api #api-development #api-analytics #apis #api-integration #api-testing #api-security #api-gateway