Serverless Ruby on AWS Lambda with the Jets framework

Originally published by PHIL NASH at  twilio.com

When AWS launched Lambda in 2014 there was no love for Ruby. Platforms like Python, Node.js, and Java started the serverless revolution for hosting and running functions in the cloud. At the end of 2018, support for Ruby was finally launched.

You can build with Ruby on Lambda using raw functions and Serverless Application Model (SAM) templates as described in the getting started guide for Ruby on Lambda, but Ruby is all about developer happiness and when the config file is longer than your program the process could be described as painful. Enter the Jets framework a framework that "leverages the power of Ruby to make serverless joyful for everyone."

From Rails to Jets

Jets combines the experience of building a Rails application with the ability to deploy to AWS Lambda and related services, including API Gateway, S3, and DynamoDB. In this post we're going to see how to get started with Jets and deploy a Lambda powered Twilio application written in Ruby.

What we're building

To keep things simple we're going to build an SMS based app and to make it a bit more fun, we're going to include a little humour. When you text into the application it will respond with a bad joke. Sorry, misspelling there, I meant a dad joke, courtesy of the icanhazdadjoke API.

This application will show us how to get started with Jets, create controllers, actions and routes. We'll build a single endpoint that responds to HTTP requests from Twilio when a number receives an incoming SMS message. The endpoint will return TwiML with a random dad joke each time and hilarity will ensue.

What you'll need

To follow along with this project you'll need:

• A Twilio account (sign up for a free one here)
• An AWS account
• Ruby 2.5 (the version supported by Lambda) and Bundler installed. If you don't have Ruby 2.5 installed, you can use one of the tools listed here to install and manage your Ruby versions.

Got all that? Then let's get started.

Getting started

We'll start by installing the jets gem globally. On the command line type:

gem install jets

The Jets executable can then be used like Rails as a generator to initiate a new project and then run commands within the project. We'll create a new project now, but given our scope in this post we are going to limit it a little. First up, we're going to create the project in API mode as there's no need for HTML views in this application. That also avoids asset compilation with webpacker, which will save in our build time. We also don't need a database. Run the following command to create a new project:

jets new dad-jokes-sms --mode api --no-database

Once the generator has finished running, change into the dad-jokes-sms directory and run your application locally with the following command:

jets serve

Open up http://localhost:8888 and you will see a page that look like this:

If you see this page then your new Jets project is running successfully.

Our first Jets controller

Now we have a Jets application we can use the gem to generate parts of our application, from models and controllers to full scaffolds. For our application we're going to need a controller with one action. Generate it with the following:

jets generate controller Messages create

The generator will create and edit a number of files for us. We need to check the new routes so open config/routes.rb.

Jets generated a GET route, but Twilio webhooks make POST requests by default and I prefer to keep it that way. Set the application up to receive POST request webhooks on the /messages endpoint instead like so:

Jets.application.routes.draw do
  post 'messages', to: 'messages#create'
  root "jets/public#show"
  # The jets/public#show controller can serve static utf8 content out of the public folder.

  # Note, as part of the deploy process Jets uploads files in the public folder to s3

  # and serves them out of s3 directly. S3 is well suited to serve static assets.

  # More info here: http://rubyonjets.com/docs/assets-serving/

  any “*catchall”, to: “jets/public#show”

end

Now, let’s go write our controller action. Open app/controllers/messages_controller.rb and you will see one method for the create action. This is the action which will receive our Twilio webhook and respond with TwiML to send back a dad joke.

Fetching a dad joke

To send back a dad joke we need to make a call to the icanhazdadjoke API. Let’s write a quick private method we can use to achieve this.

We’ll use open-uri as it’s useful for making simple web requests (including downloading files and images). The API will respond with plain text if we ask it to, which saves us doing any parsing. Add the following to the MessagesController:

require ‘open-uri’

class MessagesController < ApplicationController

def create

end
private
def random_joke

open(‘https://icanhazdadjoke.com/’, { ‘Accept’ => ‘text/plain’ }).read

end

end

Now we’re ready to return our joke to Twilio as TwiML.

Returning TwiML

We’ll build up a response using the helpers from the twilio-ruby helper library. Open the Gemfile and add twilio-ruby:

source “https://rubygems.org”

gem “jets”

gem “twilio-ruby”

On the command line, run bundle install to install the gem. Now in the create action instantiate a new TwiML response object, reply to the incoming message using the <Message> TwiML element and render the XML response, like so:

require ‘open-uri’

class MessagesController < ApplicationController

def create

twiml = Twilio::TwiML::MessagingResponse.new

twiml.message body: random_joke

render xml: twiml.to_xml

end
private
def random_joke

open(‘https://icanhazdadjoke.com/’, { ‘Accept’ => ‘text/plain’ }).read

end

end

You can read more about how to use the twilio-ruby helper library for generating TwiML in the documentation.

We can run this locally to test we are getting the expected response. If you stopped the application, start it again with jets serve. Make a POST request to localhost:8888/messages using curl and you’ll see your joke, provided by icanhazdadjoke, in the TwiML response:

curl --data “” http://localhost:8888/messages

<?xml version=“1.0” encoding=“UTF-8”?>

<Response>

<Message>What’s the advantage of living in Switzerland? Well, the flag is a big plus.</Message>

</Response>

Great, our Jets application is working! Now to deploy it to AWS Lambda.

Are you ready to deploy? IAM!

To deploy our Jets application to AWS we first need to set up our project with credentials to allow it to access AWS services. A good practice here is to create a user that has the minimum number of permissions required to do everything it needs to. The Jets documentation describes the minimum permissions that our user will need. Within our AWS account we’re going to create a policy that contains these permissions and a new user that will be assigned the policy. We can then use that user’s credentials to deploy our application.

In your AWS console find the IAM service (or head straight to the IAM section).

Go to the Policies section and create a new policy.

Choose the JSON tab and enter the following JSON from the Jets documentation:

{

“Version”: “2012-10-17”,

“Statement”: [

{

“Effect”: “Allow”,

“Action”: [

“apigateway:",

"cloudformation:”,

“dynamodb:",

"events:”,

“iam:",

"lambda:”,

“logs:",

"route53:”,

“s3:"

],

“Resource”: [

"”

]

}

]

}

Click through to review the policy and give it a name.

Save the policy. Now we need to create a new user and attach the policy to it, giving it the permissions to create the resources Jets needs to deploy. Open the Users section in the IAM console and create a new user.

Give the user a name and select Programmatic Access for the Access Type.

Click Next to choose the permissions for your new user. Choose Attach existing policies directly and filter for the name of the policy you just created. Select that policy and click Next.

Click Next until you reach the success page.

Save the Access key ID and Secret access key from the last screen. We’ll need them to deploy with. Now we’re ready to deploy.

Deploying to Lambda

On the command line enter:

AWS_ACCESS_KEY_ID=YOUR_USER_KEY AWS_SECRET_ACCESS_KEY=YOUR_USER_SECRET_KEY jets deploy

Jets will use the credentials as environment variables to set up all the resources in your AWS account to run the application. It takes a little while, but when it is complete you will have a URL where your application is running.

You’ll notice this deployed to a “dev” environment. You can read more about how Jets handles environments in the documentation.

We can now test this URL using curl. Remember we use the route /messages so add that to the end of your API Gateway endpoint and make a POST request.

$ curl --data “” https://YOUR_API_GATEWAY_ENDPOINT/messages

<?xml version=“1.0” encoding=“UTF-8”?>

<Response>

<Message>I knew a guy who collected candy canes, they were all in mint condition</Message>

</Response>

Now to have dad jokes on hand at all times let’s hook this up to a Twilio number.

Dad jokes by SMS

Head into your Twilio console to your active phone numbers. If you already have a number you want to work with, edit it, otherwise buy a new number that can receive incoming SMS messages. In the field for A message comes in enter your application URL.

Save your number and send it a message. You should get a dad joke in response. Now, in celebration, go and tell someone nearby that joke and let me know whether they laugh or groan.

Serverless Comedy

In this post we’ve seen how to get started with Jets to write Ruby applications that you can deploy to AWS Lambda. You can see the full project on GitHub.

There’s a lot more to what Jets can help you accomplish, including responding to events, storing data in databases and even run your existing Rails application. Check out these articles from the Jets documentation for more on what you can do with Jets.

Originally published by PHIL NASH at  twilio.com

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What is GEEK

Buddha Community

How To Unite AWS KMS with Serverless Application Model (SAM)

The Basics

AWS KMS is a Key Management Service that let you create Cryptographic keys that you can use to encrypt and decrypt data and also other keys. You can read more about it here.

Important points about Keys

Please note that the customer master keys(CMK) generated can only be used to encrypt small amount of data like passwords, RSA key. You can use AWS KMS CMKs to generate, encrypt, and decrypt data keys. However, AWS KMS does not store, manage, or track your data keys, or perform cryptographic operations with data keys.

You must use and manage data keys outside of AWS KMS. KMS API uses AWS KMS CMK in the encryption operations and they cannot accept more than 4 KB (4096 bytes) of data. To encrypt application data, use the server-side encryption features of an AWS service, or a client-side encryption library, such as the AWS Encryption SDK or the Amazon S3 encryption client.

Scenario

We want to create signup and login forms for a website.

Passwords should be encrypted and stored in DynamoDB database.

What do we need?

1. KMS key to encrypt and decrypt data
2. DynamoDB table to store password.
3. Lambda functions & APIs to process Login and Sign up forms.
4. Sign up/ Login forms in HTML.

Lets Implement it as Serverless Application Model (SAM)!

Lets first create the Key that we will use to encrypt and decrypt password.

KmsKey:
    Type: AWS::KMS::Key
    Properties: 
      Description: CMK for encrypting and decrypting
      KeyPolicy:
        Version: '2012-10-17'
        Id: key-default-1
        Statement:
        - Sid: Enable IAM User Permissions
          Effect: Allow
          Principal:
            AWS: !Sub arn:aws:iam::${AWS::AccountId}:root
          Action: kms:*
          Resource: '*'
        - Sid: Allow administration of the key
          Effect: Allow
          Principal:
            AWS: !Sub arn:aws:iam::${AWS::AccountId}:user/${KeyAdmin}
          Action:
          - kms:Create*
          - kms:Describe*
          - kms:Enable*
          - kms:List*
          - kms:Put*
          - kms:Update*
          - kms:Revoke*
          - kms:Disable*
          - kms:Get*
          - kms:Delete*
          - kms:ScheduleKeyDeletion
          - kms:CancelKeyDeletion
          Resource: '*'
        - Sid: Allow use of the key
          Effect: Allow
          Principal:
            AWS: !Sub arn:aws:iam::${AWS::AccountId}:user/${KeyUser}
          Action:
          - kms:DescribeKey
          - kms:Encrypt
          - kms:Decrypt
          - kms:ReEncrypt*
          - kms:GenerateDataKey
          - kms:GenerateDataKeyWithoutPlaintext
          Resource: '*'

The important thing in above snippet is the KeyPolicy. KMS requires a Key Administrator and Key User. As a best practice your Key Administrator and Key User should be 2 separate user in your Organisation. We are allowing all permissions to the root users.

So if your key Administrator leaves the organisation, the root user will be able to delete this key. As you can see **KeyAdmin **can manage the key but not use it and KeyUser can only use the key. ${KeyAdmin} and **${KeyUser} **are parameters in the SAM template.

You would be asked to provide values for these parameters during SAM Deploy.

#aws #serverless #aws-sam #aws-key-management-service #aws-certification #aws-api-gateway #tutorial-for-beginners #aws-blogs

Serverless Framework: Use AWS S3 Object Lambda to Resize Images on The Fly

Goal

In this post, I will show you how to use Amazon S3 Object Lambda to resize images on the fly. The  Serverless Framework will be used to define the Infrastructure as Code and to simplify the deployment. Sharp will be used to resize the images. Lambda will be written using the Node.js 14x  Lambda runtime

What’s Amazon S3 Object Lambda

One of the most common Lambda patterns is to transform data stored inside Amazon S3. Generally, a lambda function is invoked after a file has been uploaded. Lambda would retrieve that file, apply any needed transformation (e.g. converting type of file) and store the result in S3.

That pattern was working well, however, it would require some work done onto a file despite that being accessed in the future or not.

If you needed to convert a file on the fly you should have created a Lambda function, invoke it via Amazon API GW and wait for the lambda to perform the transformation.

AWS has recently introduced  Amazon S3 Object Lambda in a good post by Danilo Poccia. S3 Object Lambda allows creating a Lambda directly connected to the S3 bucket (using  S3 Access Points) that is automatically invoked when retrieving the object from S3!

That means that our application needs only to send an S3 Get Object request to retrieve the original or transformed data

Also, a very important peculiarity of using Amazon S3 Object Lambda it’s that the file you want to retrieve doesn’t need to exist on S3! We will make use of this for our scenario

_Note: High-level AWS CLI S3 commands (e.g. _aws s3 cp_) don’t currently support S3 Object Lambda, instead we need to use low-level S3 API commands (e.g. __aws s3api get-object)_

Common Use Cases

In his post, Danilo highlighted the most common use cases for Amazon S3 Object Lambda:

• Converting across data formats (e.g. XML to JSON)
• Compressing or decompressing files on the fly
• Resizing images on the fly (our use case!)
• Many more (left to the devs’ creativity)

#aws-lambda #serverless #aws-s3 #aws

Adding Code to AWS Lambda, Lambda Layers, and Lambda Extensions Using Docker

2020 was a difficult year for all of us, and it was no different for engineering teams. Many software releases were postponed, and the industry slowed its development speed quite a bit.

But at least at AWS, some teams released updates out of the door at the end of the year. AWS Lambda received two significant improvements:

• AWS Lambda Extensions; and
• Support of Docker images for your functions.

With these two new features and Lambda Layers, we now have three ways to add code to Lambda that isn’t directly part of our Lambda function.

The question is now: when should we use what?

In this article, I try to shine some light on the Lambda Layers, Lambda Extensions, and Docker image for Lambda.

First things first. All these Lambda features can be used together. So if you think about where to put your code, at least your decisions aren’t mutually exclusive. You can upload a Docker image and attach a regular Lambda Layer and a Lambda Extension. The same is possible if your Lambda function is based on a ZIP archive.

What does this all mean? Keep reading and find out.

#aws #aws-lambda #serverless #devops #docker #lambda

Creating your first AWS Lambda Function in Node.js | Serverless Saturday

In this Serverless Saturday video, we’ll be going over how to create your first AWS Lambda function!
In the next video, we’ll be covering how to set up CI/CD with your AWS Lambda function so stay tuned and make sure to subscribe!

To get started, log-in to your AWS account here: https://aws.amazon.com/console/

Found this video helpful? Feel free to support this channel here: https://ko-fi.com/jacksonyuan

#node.js #node #lambda #aws #aws lambda #serverless

AWS Lambda Vs EC2 | Serverless Vs EC2 | EC2 Alternatives

In this video we are going to learn the differences between ec2 vs lambda by going over:

1. What is Serverless and what is EC2
2. Environment, Use Case difference between lambda and ec2
3. Learn how differently EC2 and Lambda scale
4. Do Cost comparison lambda vs ec2 for couple cases
5. Finally we are going to look at some EC2 alternatives and end with parting words.

#aws #lambda #ec2 #serverless #aws lambda