13 Developing AI applications locally with the Atlas CLI

 

This chapter covers

  • Deploying locally with the Atlas CLI
  • Creating an Atlas cluster on your local host
  • Using mongorestore to load data into a local cluster
  • Diving into a local Atlas cluster
  • Using the createSearchIndex() wrapper

The Atlas command-line interface (CLI) simplifies working with MongoDB Atlas in the cloud and locally by managing setup, connections, and tasks across environments. It allows you to handle deployments efficiently, ensuring a seamless workflow from development to production.

You can use the Atlas CLI to develop locally with MongoDB Atlas deployments, including Atlas Search and Atlas Vector Search. This interface allows you to create full-text search or AI-powered applications in your preferred development environment. You can use the Atlas CLI to handle setup, connections, and management tasks from development to production. For full-text search, the Atlas CLI allows you to create and manage Atlas Search indexes, whether you’re working locally or in the cloud. For applications using semantic search and AI, the Atlas CLI supports creating and managing local instances with Atlas Vector Search indexes.

13.1 Introducing local Atlas clusters

To create a local Atlas deployment with default settings in interactive mode, you can use the command atlas deployments. The following listing shows what this command offers.

13.2 Creating an Atlas cluster locally with Atlas CLI

13.2.1 Configuring Docker

13.2.2 Building your first local Atlas cluster

13.3 Managing your local Atlas cluster

13.3.1 Stopping, starting, checking, and deleting your local cluster

13.3.2 Loading a sample data set

13.4 Diving into a local Atlas cluster

13.4.1 Displaying processes

13.4.2 Executing into the container

13.5 Creating search indexes

13.5.1 Executing full-text search locally

Summary