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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.

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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.

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