![]() We'll be using MongoDB Atlas, which is a document-based cloud database. Similar to the serverless function, let's use a database that is also on the cloud and has the ability to scale up and down as needed. Understand how to connect our function with a database, as logic operates over data and databases hold the data. In order to create a real-world function, which we will do in the next section, we need to But real-world applications are far more complicated than this. In the previous step, we created our first Azure function, which takes user input and returns a result. Connecting the serverless function with MongoDB Atlas To learn more, you can also follow the official guide. Update the URL by appending the query parameter name to Return request.createResponseBuilder(HttpStatus.OK).body("Hello, " + name).build() body("Please pass a name on the query string or in the request body").build() Return request.createResponseBuilder(HttpStatus.BAD_REQUEST) This will prompt passing the name as a query parameter as defined in the bootstrapped function. To deploy and run locally, press the play icon against the function name on line 20, as shown in the above screenshot, and select run from the dialogue.Ĭopy the URL shown in the console log and open it in the browser to run the Azure function. We can deploy the Azure function either locally or on the cloud. Without further ado, let's run this and see it in action. With this complete, we have a bootstrapped project with a sample function implementation. In the last step, update the name of the project and location. Now we can edit the project details if needed, or you can leave them on default. Go ahead and select File > New > Project from the menu bar, select Azure functions from Generators as shown below, and hit Next. Now, let's create a project that will contain our function and have the necessary dependencies to execute it. With this, we are ready to create our first Azure function. Open Plugins and then search for " Azure Toolkit for IntelliJ" in the Marketplace. The Azure plugin can be installed on IntelliJ in a very standard manner using the IntelliJ plugin manager. So, before we jump into actual code, let's install the plugin. Getting started with the Azure serverless function is very simple, thanks to the Azure IntelliJ plugin, which offers various features - from generating boilerplate code to the deployment of the Azure function. A basic understanding of the Java programming language.An Azure supported Java Development Kit (JDK) for Java, version 8 or 11.If this is not your preferred IDE, then you can use other IDEs like Eclipse, Visual Studio, etc., but the steps will be slightly different. IntelliJ IDEA Community Edition to aid our developmentĪctivities for this tutorial.A MongoDB Atlas account, which is a cloud-based document database.If you don't have one, you can sign up for free. A Microsoft Azure account that we will be using for running and deploying our serverless function.In this article, you'll learn how to use MongoDB Atlas, a cloud database, when you're getting started with Azure functions in Java. FaaS can also be very useful in A/B testing when you want to quickly release an independent function without going into actual implementation or release. In this article, we are going write the function as a service (FaaS) - i.e., a serverless function that will interact with data via a database, to produce meaningful results. ![]() Having the ability to scale your infrastructure up and down instantly is just one of the many benefits associated with serverless apps. Cloud computing is one of the most discussed topics in the tech industry.
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