Well, the AWS SDK is a tool created for Visual Studio in order to ease your development process for AWS using Visual Studio. It lets you configure your own AWS user into your Visual Studio and monitor and manipulate different types of resources from the Visual Studio environment itself. It is quite similar to the Azure SDK for Visual Studio. The goal is to be able to open a.NET Core Lambda project in Visual Studio and just push F5 to start debugging without any dependencies other than the AWS Toolkit for Visual Studio. When a project is opened in Visual Studio the toolkit will detect the project is a Lambda project by looking for the Lambda.

So mostly for entertainment sake and to see how easy it would be, I wondered if I could create a Python-based lambda in AWS using GitHub and Visual Studio Online. So, let’s see how this goes and how long it takes …

Pre-Requisites

For this little experiment, you will need:

A GitHub account
An Azure account
An AWS account

Set Up the Development Environment

Let’s create an empty repository in GitHub as we need somewhere to keep code! Go to https://github.com/new and create a new repository, I called mine PythonLambda. I made it public and with a README (so not empty to start).

Next hop over to Visual Studio Online and click get started. You will then need to log in using your Azure account. Then click Create Environment. Enter in a name (I chose the same as the GitHub project) and then paste the URL for the GitHub repo into the Git repository. Click create and wait for it to be available.

Next, connect to the environment. A window that looks remarkably like Visual Studio Code will appear; I chose to install support for Python. This took virtually no time whatsoever. Next hit Ctrl-' to open the terminal windows. Let’s check for python by running python --version:

On to installing the AWS CLI. Simply run the command pip3 install awscli --upgrade --user. Once this completes you can run aws --version:

So now we have a working development environment. Took about 3 minutes to set this up. We have a git repository, a copy of Visual Studio Code set up to write python code and the AWS CLI.

Logging into GitHub and AWS

Next, we can edit the README and check we can push back to GitHub as a new branch. Change the README file and save it. You can then go to Source Control tab (press Ctrl-Shift-G), commit the files and push to GitHub. It will pop up a window asking you to authorise microsoft-vs to access your GitHub account. After that, it will push the code to GitHub.

Next head to the AWS IAM console and log in. Ideally, you will create a new user but for the sake of simplicity, I will just create a new access key. Go to the Users link, find your user, go to Security Credentials and select Create Access Key. Back within the terminal in Visual Studio Online run aws configure and copy the Access Key ID and Secret Access Key into the prompts.

This step took me about 5 minutes. So, we are ready to start building the lambda in about 10 minutes.

Make a Python Lambda and Publish

The goal of this post is not really the Lambda more just to get it all set up. The code below is a really trivial function. Create a new file called lambda.py and add the new content:

This is a very simple function which will log whatever is passed to it and return the servers current date.

The bare minimum we need to do for a lambda to run is to create an IAM role and policy, and then we can publish a function. Run the following within the terminal:

This will create the Role and Policy for the lambda to use. Finally, lets publish the first version of the lambda. In the terminal, run:

Finally, we will set up a build task to publish this to AWS. Create a new folder called .vscode and add a new file called tasks.json. Add the following content:

Now if you hit Ctrl-Shift-B within the editor, it will zip and deploy the python code as it stands to AWS.

Wrapping Up

Visual Studio Online is amazing. You can get a development environment up and running in minutes. It works anywhere and can easily be hooked into whatever you like. While this post has only created a very basic set up, it is hopefully enough to show you how you could do everything from the comfort of your own browser and in very little time.

Developers write code. They shouldn’t have to worry about the infrastructure running that code. Luckily, they have AWS cloud services like Amazon Web Services’ AWS Lambda functions, also known as Lambda, to let them get back to what they do best. In this guide, you’re going to learn how to get started with AWS Lambda and, more specifically, learn how to set up your first AWS Lambda Python!

Stay tuned to learn how Lambda functions work and how to apply your newfound Lambda knowledge by using the Boto3 AWS Python SDK to create a Lambda function and start an EC2 instance.

AWS Lambda Functions: What’s the Hype on Serverless?

Before you get down to brass tax and start learning how to build an AWS Lambda function in Python, let’s first cover why Lambda is great and why you should do this in the first place.

What is Lambda?

AWS Lambda is a serverless computing technology. At a high level, the term ‘serverless’ defines services that allow developers to run code “without” a server. Depending on the programming language you’re using, you’ll find a few different ways of creating a serverless application. One of the most common ways is via Python.

When the underlying server requirements go out the window, it opens up more opportunities to do what developers do; write code. Developers can deploy code and see it in action.

Why Lambda?

Using a serverless platform gives you some key abilities that you may not have elsewhere. Some of those key abilities include:

Running code based on a response or event – You can schedule code to run at any given time and as many times as you want based on nearly any AWS event. You no longer have to run scripts ad-hoc.
You don’t need an operating system to run the code on – With serverless functions, you don’t need to set up an environment to run code on. That means you don’t have to set up networking, virtual machines, storage, etc. You just have a place to run code.
Run almost any type of code – Lambda is compatible with Python, Node.JS, Ruby, Go, Java, C#, and even PowerShell.
Built-in failover/fault tolerance – The servers that Lambda runs on are located across multiple availability zones in a region.
Cheap – Lambda functions are cheap. You only pay for what you use for. The code could be sitting in a Lambda Function for as long as you want. As long as it’s not being used, you don’t get charged.

Tutorial Overview on writing AWS Lambda Python

The rest of this article will be a step-by-step tutorial. In this in-depth guide, you’ll create a Lambda function to run Python code to start an EC2 instance. You will learn how to build a Lambda function that:

Starts an EC2 instance using the Python SDK, Boto3
Creates an archive of the Boto3 code so it can be ran from Lambda
Creates an S3 bucket to store the Boto3 code
Creates a Lambda function using Boto3
Tests the Lambda function
Starts an EC2 instance

Prerequisites

If you’d like to follow along with the tutorial, you’ll need a few key items and pieces of software to accomplish the task at hand.

An AWS EC2 instance – You won’t need anything special for this tutorial.
Python v3 – You can download and install Python from here. All examples will be using v3.7.6.
A code editor of your choice – All examples will be using Visual Studio Code with the Python extension installed. If you decide to use another code editor, the screenshots will not be the same.
An AWS profile configured – The code you’ll be writing with the Boto3 Python library requires authentication to AWS. Configuring a profile using the AWS CLI creates the required profile on the computer.
An IAM user and role – All examples will assume you already have already created a new IAM user and role created with EC2FullAccess and LambdaFullAccess privileges.
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Aws Lambda On Visual Studio