8 Deploying our full stack GraphQL application

 

This chapter covers

  • Deploying our full stack GraphQL application so it is accessible to users on the web
  • Using serverless deployment and cloud-managed services like Netlify, AWS Lambda, and Neo4j Aura
  • A framework for evaluating various deployment options to help us reconcile the inherent tradeoffs

While developing our application so far, we have been running it locally on our machine for testing. Now, it’s time to deploy our application so we can share it with the world and have users interact with it. There are many different ways to deploy applications, especially with the growth and evolution of cloud-managed services that offer improved developer experiences and usage pricing. There is not a single best deployment option for any application, as each choice has tradeoffs; ultimately, the developer must decide what options make the most sense for them and their use case.

8.1 Deploying our full stack GraphQL application

8.1.1 Advantages of this deployment approach

8.1.2 Disadvantages of our deployment approach

8.1.3 Overview of our approach to full stack GraphQL

8.2 Neo4j Aura database as a service

8.2.1 Creating a Neo4j Aura cluster

8.2.2 Connecting to a Neo4j Aura cluster

8.2.3 Uploading data to Neo4j Aura

8.2.4 Exploring the graph with Neo4j Bloom

8.3 Deploying a React application with Netlify Build

8.3.1 Adding a site to Netlify

8.3.2 Setting environment variables for Netlify builds

8.3.3 Netlify deploy previews

8.4 Serverless GraphQL with AWS Lambda and Netlify Functions

8.4.1 Serving a GraphQL API as a Lambda function

8.4.2 The Netlify dev CLI