In this workshop, we'll deploy a simple serverless application which generates Doge meme images, randomly choosing colors and locations of text, writing an image into an S3 bucket.

This will create an API that can be used by web services or users to generate doge images, while consuming no dedicated or long-lived resources besides space on S3.

1. Access to a MacOS or Linux machine. These instructions are not tested on Windows; users may need to make small adaptations or run these commands inside of a Docker container or Linux VM. (Install Docker for Windows)
2. Amazon Web Services account. Creation of an account is free and various services are provided under a free-tier, although a credit card is required at the time of account creation. AWS Lambda is free for up to 1 million invocations per month, for all users, which is more than sufficient for this course. Storage of functions may incur small fees (normally pennies / month). Students are solely responsible for their AWS bill and all charges incurred as a result of this course.
3. Install NodeJS 4.4.3 or higher: NodeJS downloads
4. Curl (you probably have this already! Curl ships with MacOS and is easily installed via Linux package managers.

• Create ~/.aws/credentials (manually or via aws-cli configure), or set environment variables:

export AWS_ACCESS_KEY_ID=<key>
export AWS_SECRET_ACCESS_KEY=<secret>

There are several frameworks for building so-called "serverless" applications. The most popular one is called, aptly, The Serverless Framework. Other frameworks can be found on this fairly exhaustive list.

For the sake of convenience, we'll settle using TheServerlessFramework with a NodeJS application for this workshop.

• Install module: sudo npm install -g serverless@beta
• Create project directory: mkdir iopipe-workshop; cd iopipe-workshop
• Create! serverless create --template aws-nodejs also see alternatives to nodejs
• Deploy! serverless deploy
• Test! serverless invoke --function hello -p event.json

We've prepared an example project for you to test!

Checkout this repo:

$ git clone https://github.com/iopipe/lambda-workshop

Edit serverless.yml and doge.js to change iopipe-workshop-doge-1 to a unique name.

$ sed -i "s/iopipe-workshop-doge-1/iopipe-workshop-doge-$(($RANDOM*$RANDOM))/g" doge.js serverless.yml

This function uploads files into Amazon S3. To accomplish this, the Lambda function must be granted permission to the S3 bucket.

• Go into the IAM policy editor, click Roles.
• Select the role which looks like, iopipe-workshop-doge-1-dev-IamRoleLambda-
• Click Attach Policy and select AmazonS3FullAccess.

$ serverless deploy

$ serverless invoke --function create -p event.json

A URL should be printed to your console. Visit this in your browser. Edit event.json to change the text overlaid onto the image.

Edit the code and do fun things!

While not critical for a doge-text app, more serious applications, including ChatBots, Voice assistents, production web services, etc. will benefit from Application Performance Monitoring & Management (APM).

IOpipe is offering free beta access to an APM service designed specifically for serverless applications.

• npm install --save iopipe
• Import & configure the module:

/* Get client-id token from https://dashboard.iopipe.com */
require("iopipe")({ clientId: "my-client-id-here" })

• Modify the handler, wrapping the function declaration with iopipe(). Make sure to close the parens by placing a ) character after the final } character.

module.exports.create = iopipe((event, context, cb) => {
  ...
})

• Redeploy: serverless deploy
• Invoke function: serverless invoke --function hello -p event.json
• Check dashboard

This is actually a functioning Slackbot! If you have admin permission on a Slack, you can add this as a /doge slash command!

• Visit Custom Integrations, choose 'Slash Commands', then 'Add Configuration'.
• Specify the command /doge and click, Add Integration.
• Provide the URL given by serverless deploy
• Specify GET as the HTTP method.
• Click Save Integration

Now you can type /doge this text gets printed onto your doge!

We have created various resources during this course. You may, of course, keep these applications and resources deployed, but you may incur small fees from Amazon in doing so. Make sure to delete all AWS Lambda functions, S3 objects, S3 buckets, and other resources created during this course using your AWS console. If in doubt, check the Billing "Service" in your AWS Console.

Resources will have been created under IAM roles, Lambda functions, S3 buckets, API Gateway, and Cloudformation. Simply deleting the cloud formation resources is usually enough, but again, double-check!

The following command should remove all resources:

$ serverless remove