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Get started with Elasticsearch Serverless

Serverless

Tip

Not sure whether Elasticsearch on Elastic Cloud Serverless is the right deployment choice for you?

Check out the following resources to help you decide:

• What’s different?: Understand the differences between Elastic Cloud Serverless and other deployment types.
• Billing: Learn about the billing model for Elasticsearch on Elastic Cloud Serverless.

Elasticsearch Serverless is one of the three available project types on Elastic Cloud Serverless.

This project type enables you to use the core functionality of Elasticsearch: searching, indexing, storing, and analyzing data of all shapes and sizes.

When using Elasticsearch on Elastic Cloud Serverless you don’t need to worry about managing the infrastructure that keeps Elasticsearch distributed and available: nodes, shards, and replicas. These resources are completely automated on the serverless platform, which is designed to scale up and down with your workload.

This automation allows you to focus on building your search applications and solutions.

On this page, you will learn how to:

• Create an Elasticsearch Serverless project.

• Get started with Elasticsearch:

  • Option 1: Guided index flow: Follow the step-by-step tutorial provided in the UI to create an index and ingest data.
  • Option 2: In-product Getting Started guide: Use the Getting Started page’s instructions to ingest data and perform your first search.
  • Option 3: Explore on your own: If you’re already familiar with Elasticsearch, retrieve your connection details, select an ingest method that suits your needs, and start searching.

Use your Elastic Cloud account to create a fully-managed Elasticsearch project:

1. Navigate to cloud.elastic.co and create a new account or log in to your existing account.

2. Within Serverless Projects, choose Create project.

3. Choose the Elasticsearch project type.

4. Select a configuration for your project, based on your use case.

   • General purpose: For general search use cases across various data types.
   • Optimized for Vectors: For search use cases using vectors and near real-time retrieval.

5. Provide a name for the project and optionally edit the project settings, such as the cloud platform region. Select Create project to continue.

6. Once the project is ready, select Continue.

Now your project is ready to start creating indices, adding data, and performing searches. You can choose one of the following options to proceed.

Once your project is set up, you’ll be directed to a page where you can create your first index. An index is where documents are stored and organized, making it possible to search and retrieve data.

1. Enter a name for your index.

2. Click Create my index. You can also create the index by clicking on Code to view and run code through the command line.

3. You’ll be directed to the Index Management page. Here, copy and save the following:

   • Elasticsearch URL
   • API key

Note

You won’t be able to view this API key again. If needed you'll need to generate a new one.

The UI provides ready-to-use code examples for ingesting data via the REST API. Choose your preferred tool for making these requests:

• Console in your project’s UI
• Python
• JavaScript
• cURL

To get started using the in-product tutorial, navigate to the Getting Started page and follow the on-screen steps.

If you’re already familiar with Elasticsearch, you can jump right into setting up a connection and ingesting data as per your needs.

1. Retrieve your connection details.

2. Ingest your data. Elasticsearch provides several methods for ingesting data:

   • Elasticsearch API
   • Connector clients
   • File Uploader
   • Beats
   • Logstash
   • Elastic Open Web Crawler

• Once you’ve added data to your Elasticsearch Serverless project, you can use Playground to test and tweak Elasticsearch queries and chat with your data, using GenAI.
• You can also try our hands-on quick start tutorials in the core Elasticsearch documentation.

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