In true newline-fashion, we'll get *rolling* with a practical application right away. We're creating a fully functional, dice-rolling chat bot for Slack!

Create a Serverless Slack Bot with AWS Lambda and Python

Introduction

There's no `AWS Lambda` without `AWS`. That means we'll need a few AWS resources created and configured on the AWS side of things to develop and effectively.

How to Setup a Free AWS Developer Environment

Here, we'll configure an `AWS Workspace` or `AWS EC2 Instance` as the development environment to use for developing for AWS Lambda.

How to Configure EC2 and AWS Workspaces Local Credentials

Configuring Your AWS Environment

We can comfortably develop for AWS Lambda with python on any modern Operating System

Setup a Local Python AWS Lambda Development Environment

We will be using the AWS Lambda runtime for the latest stable version of Python 3 - `python3.7`.

Installing Python 3 and Pyenv on MacOS, Windows, and Linux

The easiest way to configure our local development with our credentials is to run the command `aws configure`

How to Login to AWS CLI and Configure Default Region

Configuring Your Local Machine

How Our Slack Bot "Dicebot" Will Work

How to Create an AWS S3 Bucket for Lambda Artifacts

How to Code a Lambda Hello World Function with AWS SAM

How to Test AWS Lambda Functions Locally With Docker

The Beginner Guide to AWS Lambda Deployment

Creating Hello-world Lambda

How to Create a Slack Bot

How to Code a Python Dice Rolling Simulator Program

How to Turn Serverless Python Lambda Code Into a Slack Bot

Testing Our Serverless Slack Dicebot with Docker Locally

Cleaning Up Our Serverless Dicebot Deployment

Creating Dicebot Lambda

*Serverless Computing* may sound like a scary topic, but with the rise of AWS Lambda and mature tools supporting it - it's more approachable than ever. In this newline course, we're going to learn what serverless technology is and isn't, and why it belongs in your developer toolbox. We'll see that for certain common projects - like custom chat bot creation - AWS Lambda really shines for it's simplicity, affordability, and ability to integrate with the wider AWS ecosystem. 

Some developers love using serverless tech because it helps them save money, scale quickly, and deliver on reliability goals. While all of those things are possible with Lambda (especially cost savings which are common - but certainly not guaranteed), it's the development agility and reduction of operations overhead that drives my love for the service. It's a relief to be able to get right into the code, without worrying about configuring operating systems, deploying containers, or scaling clusters. Serverless on Lambda gives developers the resources needed to write, deploy, and _maintain_ production-ready software - all without significant operational overhead.

In true newline-fashion, we'll get *rolling* with a practical application right away. RPG players rejoice - we're creating a fully functional, dice-rolling chat bot for Slack! While the example bot will be for Slack, the same idea can be easily adapted to create a bot for Telegram, Discord, or nearly any other chat service with a bot API. 

We will be using Python 3 for this project, but it's worth noting that [AWS Lambda works with other common languages and runtimes](https://docs.aws.amazon.com/lambda/latest/dg/lambda-runtimes.html), including NodeJS, Java, ruby, go, and .NET. The basic mechanisms of creating, testing, and deploying your Lambda do not vary significantly based on your runtime choice.

By the end of this course you'll:

* Deploy a Slack Bot that runs on AWS Lambda
* Understand how to keep your AWS account secure
* Be able to deploy custom Lambda functions
* Understand serverless architecture and how it works

In this course we'll build and deploy a Serverless Slack Bot using AWS Lambda and Python. Along the way you'll learn about proper security, how lambda works, and how to deploy your service.

Create a Serverless Slackbot with AWS Lambda and Python

How to deploy a serverless bot into production

Deploying Your First AWS Lambda Hello-World Function Into Production

It may not rolling dice yet, but let's go ahead and deploy it! It may seem like we're getting ahead of ourselves, but the truth is that we need to deploy it so that our API Gateway Infrastructure can be created and used in the next portion of the work.

Before we deploy, we will need to package our built lambda. Go ahead and run the command 

 to see the full details around how this command is used.

For our case, we will run this from the same 

 directory we have been using. Use the example shown below, but replace 

sam package \
    --template-file template.yaml \
    --output-template-file packaged.yaml \
    --s3-bucket <your-bucket-name>

Uploading to 8f2252e7beae23803e866250271c52bf  1369 / 1369.0  (100.00%)
Successfully packaged artifacts and wrote output template to file packaged.yaml.
Execute the following command to deploy the packaged template
aws cloudformation deploy --template-file /home/ec2-user/Development/dicebot/packaged.yaml --stack-name <YOUR STACK NAME>

---
title: The Beginner Guide to AWS Lambda Deployment
isPublicLesson: false
---

# Deploying Your First AWS Lambda Hello-World Function Into Production

It may not rolling dice yet, but let's go ahead and deploy it! It may seem like we're getting ahead of ourselves, but the truth is that we need to deploy it so that our API Gateway Infrastructure can be created and used in the next portion of the work.

Before we deploy, we will need to package our built lambda. Go ahead and run the command `sam package --help` to see the full details around how this command is used.

For our case, we will run this from the same `dicebot` directory we have been using. Use the example shown below, but replace `<your-bucket-name>` with the name of the [S3 Bucket](#s3bucket) you created above.

```bash
sam package \
    --template-file template.yaml \
    --output-template-file packaged.yaml \
    --s3-bucket <your-bucket-name>
```

The output should look like:

    Uploading to 8f2252e7beae23803e866250271c52bf  1369 / 1369.0  (100.00%)
    Successfully packaged artifacts and wrote output template to file packaged.yaml.
    Execute the following command to deploy the packaged template
    aws cloudformation deploy --template-file /home/ec2-user/Development/dicebot/packaged.yaml --stack-name <YOUR STACK NAME>

As you can see, they're nice enough to include the next deploy command in the next step! We just need to pick a name to give it in place of `<YOUR STACK NAME>`. Let's call it, "DicebotChap1". We'll also need to add one more flag to that for it to work - `--capabilities CAPABILITY_IAM`. That flag just ensures that CloudFormation has the permissions necessary to create IAM resources for our Lambda.