A connector is a type of Elastic integration that syncs data from an original data source to Elasticsearch. Each connector extracts the original files, records, or objects; and transforms them into documents within Elasticsearch.

Connector clients are self-managed connectors that you run on your own infrastructure. These connectors are written in Python and the source code is available in the elastic/connectors repo.

Available connectors

Connector clients are available for the following third-party data sources:

Overview

Because connector clients are self-managed on your own infrastructure, they run outside of your Elasticsearch serverless project.

You can run them from source or in a Docker container.

Data source prerequisites

The first decision you need to make before deploying a connector is which third party service (data source) you want to sync to Elasticsearch. See the list of available connectors.

Note that each data source will have specific prerequisites you'll need to meet to authorize the connector to access its data. For example, certain data sources may require you to create an OAuth application, or create a service account. You'll need to check the individual connector documentation for these details.

Initial setup in UI

In your project's UI, go to Elasticsearch → Connectors. Read the high-level instructions under Create a connector to make sure you understand the process. Follow these steps:

1. Select Create a connector.
2. Choose a third-party service from the list of connector types.
3. Add a name and optional description to identify the connector.
4. Copy the connector_id, service_type, and elasticsearch.host values printed to the screen. You'll need to update these values in your config.yml file.
5. Make a note of your Elasticsearch endpoint and API key values. You can create a new API key under Security → API keys.
6. Run the connector code using one of the options documented on this page.

Deploy your self-managed connector

To use connector clients, you must deploy the connector service so your connector can talk to your Elasticsearch instance. The source code is hosted in the elastic/connectors repository.

You have two deployment options:

• Run from source
• Run with Docker

Run from source

This is a good option if you're comfortable working with Python and want to iterate quickly locally. First, you need to clone the elastic/connectors repository.

Follow these steps:

• Clone or fork the repository locally with the following command:

  git clone https://github.com/elastic/connectors

• Create a config.yml configuration file by copying this example.

• Replace the values for host (your Elasticsearch endpoint), api_key, connector_id, and service_type.

  Tip

  Learn more about the config.yml file in the repo docs.

Run the connector service

Once you've configured the connector code, you can run the connector service.

In your terminal or IDE:

• cd into the root of your elastic/connectors clone/fork.

• Run the following commands to compile and run the connector service:

  make install
  make run

The connector service should now be running in your terminal. Your project's UI will let you know that the connector has successfully connected to your Elasticsearch instance.

Here we're working locally. In a production setup, you'll deploy the connector service to your own infrastructure.

Run with Docker

You can also deploy connector clients using Docker. Follow these instructions.

Step 1: Download sample configuration file

You can either download the configuration file manually or run the following command:

curl https://raw.githubusercontent.com/elastic/connectors/main/config.yml.example --output </absolute/path/to>/connectors-config/config.yml

Change the --output argument value to the path where you want to save the configuration file.

Step 2: Update the configuration file for your self-managed connector

Update the following settings to match your environment:

• elasticsearch.host
• elasticsearch.api_key
• connectors

Your configuration file should look like this:

elasticsearch.host: <ELASTICSEARCH_ENDPOINT>
elasticsearch.api_key: <ELASTICSEARCH_API_KEY>

connectors:
  -
    connector_id: <CONNECTOR_ID_FROM_UI>
    service_type: <SERVICE-NAME> # sharepoint_online (example)
    api_key: <CONNECTOR_API_KEY> # Optional. If not provided, the connector will use the elasticsearch.api_key instead

Step 3: Run the Docker image

Use the following command, substituting values where necessary:

docker run \
-v "</absolute/path/to>/connectors-config:/config" \ # NOTE: change absolute path to match where config.yml is located on your machine
--tty \
--rm \
docker.elastic.co/enterprise-search/elastic-connectors:{version}.0 \
/app/bin/elastic-ingest \
-c /config/config.yml # Path to your configuration file in the container

Find all available Docker images in the official Elastic Docker registry.

Enter data source details in UI

Once the connector service is running, it's time to head back to the UI to finalize the connector configuration. You should now see the Configure your connector step in your project's UI.

In this step, you need to add the specific connection details about your data source instance, like URL, authorization credentials, etc. These details will vary based on the third-party data source you’re connecting to.

For example, the Sharepoint Online connector requires the following details about your Sharepoint instance:

• Tenant ID
• Tenant name
• Client ID
• Secret value
• Comma-separated list of tables

Connect to an index

Once you've entered the data source details, you need to connect to an index. This is the final step in your project's UI, before you can run a sync.

You can choose to sync to an existing Elasticsearch index, or create a new index for your connector. You can also create an API key that is limited to only access your selected index.

Once this step is completed, you're ready to run a sync. When a sync is launched you'll start to see documents being added to your Elasticsearch index.

Learn how syncing works in the elastic/connectors repo docs.

Learn more

• Read the main Elastic connectors documentation
• The Elastic connector framework enables you to:
  • Customize existing connector clients.
  • Build your own connector clients.