Serverless Development with Kotlin, AWS Lambda, and MongoDB Atlas

As seen in a previous tutorial, creating a serverless function for AWS Lambda with Java and MongoDB isn’t too complicated of a task. In fact, you can get it done with around 35 lines of code!

However, maybe your stack doesn’t consist of Java, but instead Kotlin. What needs to be done to use Kotlin for AWS Lambda and MongoDB development? The good news is not much will be different!

In this tutorial, we’ll see how to create a simple AWS Lambda function. It will use Kotlin as the programming language and it will use the MongoDB Kotlin driver for interacting with MongoDB.

Serverless Development with AWS Lambda and MongoDB Atlas Using Java

So you need to build an application that will scale with demand and a database to scale with it? It might make sense to explore serverless functions, like those offered by AWS Lambda, and a cloud database like MongoDB Atlas.

Serverless functions are great because you can implement very specific logic in the form of a function and the infrastructure will scale automatically to meet the demand of your users. This will spare you from having to spend potentially large amounts of money on always on, but not always needed, infrastructure. Pair this with an elastically scalable database like MongoDB Atlas, and you’ve got an amazing thing in the works.

In this tutorial, we’re going to explore how to create a serverless function with AWS Lambda and MongoDB, but we’re going to focus on using Java, one of the available AWS Lambda runtimes.

Local Development with the MongoDB Atlas CLI and Docker

Need a consistent development and deployment experience as developers work across teams and use different machines for their daily tasks? That is where Docker has you covered with containers. A common experience might include running a local version of MongoDB Community in a container and an application in another container. This strategy works for some organizations, but what if you want to leverage all the benefits that come with MongoDB Atlas in addition to a container strategy for your application development?

In this tutorial we’ll see how to create a MongoDB-compatible web application, bundle it into a container with Docker, and manage creation as well as destruction for MongoDB Atlas with the Atlas CLI during container deployment.

Getting Started with MongoDB Atlas and Azure Functions using .NET and C#

So you need to build an application with minimal operating costs that can also scale to meet the growing demand of your business. This is a perfect scenario for a serverless function, like those built with Azure Functions. With serverless functions you can focus more on the application and less on the infrastructure and operations side of things. However, what happens when you need to include a database in the mix?

In this tutorial we’ll explore how to create a serverless function with Azure Functions and the .NET runtime to interact with MongoDB Atlas. If you’re not familiar with MongoDB, it offers a flexible data model that can be used for a variety of use cases while being integrated into most application development stacks with ease. Scaling your MongoDB database and Azure Functions to meet demand is easy, making them a perfect match.

Interact with MongoDB in an AWS Lambda Function Using Go

If you’re a Go developer and you’re looking to go serverless, AWS Lambda is a solid choice that will get you up and running in no time. But what happens when you need to connect to your database? With serverless functions, also known as functions as a service (FaaS), you can never be sure about the uptime of your function or how it has chosen to scale automatically with demand. For this reason, concurrent connections to your database, which aren’t infinite, happen a little differently. In other words, we want to be efficient in how connections and interactions to the database are made.

In this tutorial we’ll see how to create a serverless function using the Go programming language and that function will connect to and query MongoDB Atlas in an efficient manner.

Getting Started with MongoDB Atlas and Azure Functions using Node.js

So you’re building serverless applications with Microsoft Azure Functions, but you need to persist data to a database. What do you do about controlling the number of concurrent connections to your database from the function? What happens if the function currently connected to your database shuts down or a new instance comes online to scale with demand?

The concept of serverless in general, whether that be through a function or database, is great because it is designed for the modern application. Applications that scale on-demand reduce the maintenance overhead and applications that are pay as you go reduce unnecessary costs.

In this tutorial, we’re going to see just how easy it is to interact with MongoDB Atlas using Azure functions. If you’re not familiar with MongoDB, it offers a flexible document model that can be used to model your data for a variety of use cases and is easily integrated into most application development stacks. On top of the document model, MongoDB Atlas makes it just as easy to scale your database to meet demand as it does your Azure Function.

Build a Totally Serverless REST API with MongoDB Atlas

So you want to build a REST API, but you don’t want to worry about the management burden when it comes to scaling it to meet the demand of your users. Or maybe you know your API will experience more burst usage than constant demand and you’d like to reduce your infrastructure costs.

These are two great scenarios where a serverless architecture could benefit your API development. However, did you know that the serverless architecture doesn’t stop at just the API level? You could make use of a serverless database in addition to the application layer and reap the benefits of going totally serverless.

In this tutorial, we’ll see how to go totally serverless in our application and data development using a MongoDB Atlas serverless instance as well as Atlas HTTPS endpoints for our application.