Serverless development with Node.js, AWS Lambda and MongoDB Atlas

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The developer landscape has dramatically changed in recent years. It used to be fairly common for us developers to run all of our tools (databases, web servers, development IDEs…) on our own machines, but cloud services such as GitHub, MongoDB Atlas and AWS Lambda are drastically changing the game. They make it increasingly easier for developers to write and run code anywhere and on any device with no (or very few) dependencies.

A few years ago, if you crashed your machine, lost it or simply ran out of power, it would have probably taken you a few days before you got a new machine back up and running with everything you need properly set up and configured the way it previously was.

With developer tools in the cloud, you can now switch from one laptop to another with minimal disruption. However, it doesn’t mean everything is rosy. Writing and debugging code in the cloud is still challenging; as developers, we know that having a local development environment, although more lightweight, is still very valuable.

And that’s exactly what I’ll try to show you in this blog post: how to easily integrate an AWS Lambda Node.js function with a MongoDB database hosted in MongoDB Atlas, the DBaaS (database as a service) for MongoDB. More specifically, we’ll write a simple Lambda function that creates a single document in a collection stored in a MongoDB Atlas database. I’ll guide you through this tutorial step-by-step, and you should be done with it in less than an hour.

Let’s start with the necessary requirements to get you up and running:

An Amazon Web Services account available with a user having administrative access to the IAM and Lambda services. If you don’t have one yet, sign up for a free AWS account.
A local machine with Node.js (I told you we wouldn’t get rid of local dev environments so easily…). We will use Mac OS X in the tutorial below but it should be relatively easy to perform the same tasks on Windows or Linux.
A MongoDB Atlas cluster alive and kicking. If you don’t have one yet, sign up for a free MongoDB Atlas account and create a cluster in just a few clicks. You can even try our M0, free cluster tier, perfect for small-scale development projects!).

Now that you know about the requirements, let’s talk about the specific steps we’ll take to write, test and deploy our Lambda function:

MongoDB Atlas is by default secure, but as application developers, there are steps we should take to ensure that our app complies with least privilege access best practices. Namely, we’ll fine-tune permissions by creating a MongoDB Atlas database user with only read/write access to our app database.
We will set up a Node.js project on our local machine, and we’ll make sure we test our lambda code locally end-to-end before deploying it to Amazon Web Services.
We will then create our AWS Lambda function and upload our Node.js project to initialize it.
Last but not least, we will make some modifications to our Lambda function to encrypt some sensitive data (such as the MongoDB Atlas connection string) and decrypt it from the function code.

A Short Note About VPC Peering

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