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Aws Serverless Skeleton

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Overview

Aws Serverless Skeleton is built on top of AWS (Amazon Web Service) using multiple services :

  • API Gateway
  • DynamoDB
  • DynamoDB Streams
  • S3
  • Lambda
  • Cognito
  • ES (Elasticsearch Service)
  • CloudFormation
  • CloudWatch

Note: This project may be edited directly in the browser using the gitpod application which is provides a full blown IDE.

Open in Gitpod

Contents

Requirements

Installing

in order to start running the Skeleton on your AWS account you need to install some requirements before starting with :

install python3 is via brew:

brew install python3

install npm is via brew:

brew install node

install serverless is via npm:

npm install -g serverless

install serverless plugins:

cd aws-serverless-skeleton (you have to be in the repo root directory)
npm install

Setup AWS

You need to configure AWS with your own credentials. You need to install aws cli. In your python3 virtualenv, do:

pip3 install awscli

Then configure it:

aws configure

you will be asked to provide your AWS Access Key ID, AWS Secret Access Key and region (eu-west-1) and default output format (json). once you are done, make sure the configuration is working:

aws sts get-caller-identity
aws iam list-users --output table

if all is well, then you are good to go!

Deploy to AWS

by simple command from terminal:

npm run deploy-dev
// for prod env 
npm run deploy-prod

also you could deploy the function changed , Use this to quickly upload and overwrite your AWS Lambda code on AWS, allowing you to develop faster.

sls deploy function -f #function_name# --stage #stage_name#

Run it locally

  • first of all you need to install all python and npm requirements:
pip3 install -r requirements.txt
npm install
  • Install dynamodb-local:
npm run dynamo-install
  • install elasticsearch:

The below command will install elastic search in ~/sources/

npm run elasticsearch-install
  • Start serverless-offline, dynamodb-local and elasticsearch. Make sure above command is executed before this.
npm run start

By default you can send your requests to http://localhost:3000/ or http://localhost:8000/shell to access the web shell for dynamodb-local or http://localhost:9200 for elasticsearch.

Please note that:

  • You'll need to restart the plugin if you modify your serverless.yml or any of the default template files.
  • The event object passed to your λs has one extra key: { isOffline: true }. Also, process.env.IS_OFFLINE is true.
  • Seed config for dynamodb-local is enabled, that's mean each table will be seeded automatically on startup from JSON files. You can start the server with fresh table by this command: npm run dynamo-start

Trying the service with Postman:

To install Postman, go to the apps page and click Download for Mac / Windows / Linux depending on your platform. Download

after downloading Postman you need to add the collection of endpoint of the services to be called from collections

  1. from import button, choose import from url and paste the url above.
  2. right click on the collection "posts", choose edit, and then choose variables tab.
  3. add key = BASE_URL and value is either: YOUR_BASE_URL or local
  4. to run any of the requests, just select it and hit run ( to test, choose post and then "get all posts" )

Configuration

You will find a folder config that have a separate file for each environment (dev, prod and local) each file has

  • environment for environment values like DynamoDB table names or elastic search endpoint.
  • custom to modify and update the resource configuration, for example from custom you can change the elastic search instance type.
  • functions for a list of lambda function to deploy in environment.
  • authorizer For more information please read this section

resourse folder that contains a bunch of files to deploy the required resources in the CloudFormation stack, you can enable or disable any resource from serverless.yml file.

Authorization

Over lambda function

We have a dummy function AuthorizerService to authorize the request, you can update it with any authorizer you like.

For this approach, you need to append below code in your env (dev-env.yml or prod-env.yml) file.

authorizer:
  name: auth_authorizer
  resultTtlInSeconds: 0
  type: token

Over Cognito

Please read more about this in Cognito Section

Cognito

In this skeleton, We are counting on Cognito with Authorization and Authentication process, and there are two ways to apply cognito.

First approach

Separate cognito in a different stack or do it manually and then append Pool ARN to your environment. if you are following this approach then you need to update POOL_ARN value in your env file (dev-env.yml or prod-env.yml) with your user pool ARN like so:

environment:
  POOL_ARN: 'arn:aws:cognito-idp:{REGION}:{ACCOUNT_NUMBER}:userpool/{REGION}_{USER_POOL_ID}'

And in your env file just change the authorizer to :

authorizer:
  name: authorizer
  arn: ${self:provider.environment.POOL_ARN}

After deploying the stack, just go to your user pool and enable PostConfirmation trigger with auth_post function.

NOTE make sure to remove cognito recourse form serverless.yml file.

Second approach

Deploying the user pool resource within the same stack by appending ${file(config/resource/cognito.yml)} under resources in serverless.yml file.

resources:
  - ${file(config/resource/cognito.yml)}

Go to lambda_functions/aut/functions.yml and change:

auth_post:
  handler: lambda_functions/auth/auth.post_auth

To:

auth_post:
  handler: lambda_functions/auth/auth.post_auth
  events:
    - cognitoUserPool:
        pool:
          Ref: CognitoUserPool
        trigger: PostConfirmation

In your env file just change the authorizer to :

authorizer:
  type: COGNITO_USER_POOLS
  authorizerId:
    Ref: ApiGatewayAuthorizer

DynamoDB

Working on it.

Elastic Search

Working on it.

S3

Working on it.

VPC

We assume that you already you have a VPC with in your AWS region, so there's no recourse to deploy a VPC with in the same stack however to deploy the lambda functions into a non-default VPC you need to update three values in (dev-env.yml or prod-env.yml) file.

environment:
  VPC_SECURITY_GROUP: "VPC_SECURITY_GROUP"
  VPC_SUBNET_PUBLIC_1: "VPC_SUBNET_PUBLIC_1"
  VPC_SUBNET_PUBLIC_2: "VPC_SUBNET_PUBLIC_2"

NOTE to deploy the lambda functions with default VPC just remove vpc value from serverless.yml file.

provider:
  vpc:
      securityGroupIds:
        - ${self:provider.environment.VPC_SECURITY_GROUP}
      subnetIds:
        - ${self:provider.environment.VPC_SUBNET_PUBLIC_1}
        - ${self:provider.environment.VPC_SUBNET_PUBLIC_2}

Structure

In this skeleton, you will find that we separate the lambda function handler from the business logic itself, for too many reasons.

Lambda Function

It contains a list of folders, each folder for only one route and each folder contains only two files.

  • route_name.py with a list of lambda function handler that returns the service response.
  • functions.yml with a list of lambda function recourse name and the configuration for each function, for example events type, http method or the path for the route.

App Service

This folder (src) contains all our business logic

  • app package has a list of packages, each package has the name for the route with a list of services that represent our CRUD and model class
  • common contains a list of helper classes.

Seeds

we inject some seed data into our tables with local env, this helped us with test our application, to change the data just update any json file from seed folder.

Testing

The project contains a set of unit and integration tests but before all make sure you follow this instruction before run test commands.

You need to install tox tool:

pip install -r requirements-dev.txt

Make sure all the services are ruining on your device:

npm run start

To install dev requirements and test this project against Python3.6, just type:

tox