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Elastic Docs ›Elasticsearch Guide [8.16] ›Ingest content with Elastic connectors ›Self-managed connectors

Running from the source code

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Running from the source code

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The basic way to run connectors is to clone the repository and run the code locally. This is a good option if you are comfortable with Python and want to iterate quickly.

Initial setup in Kibana

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Follow the Connector workflow in the Kibana UI to select the Connector ingestion method.

Next, complete these steps:

  1. Choose which third-party service you’d like to use by selecting a data source.
  2. Create and name a new Elasticsearch index.
  3. Generate a new API key and save it somewhere safe.
  4. Name your connector and provide an optional description
  5. Convert managed connector to a self-managed connector (Only applicable if connector is also available natively). This action is irreversible.

  6. Copy the configuration block from the example shown on the screen. You’ll use this in a later step:

    # ...
connectors:
  - connector_id: <CONNECTOR-ID>
    api_key: <API-KEY> # Scoped API key for this connector (optional). If not specified, the top-level `elasticsearch.api_key` value is used.
    service_type: gmail # example
Clone the repository and edit config.yml
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Once you’ve created an index, and entered the access details for your data source, you’re ready to deploy the connector service.

First, you need to clone the elastic/connectors repository.

Follow these steps:

  • Clone or fork the connectors repository locally with the following command: git clone https://github.com/elastic/connectors.
  • Run make config to generate your initial config.yml file
  • Open the config.yml configuration file in your editor of choice.

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

    Expand to see an example config.yml file

    Replace the values for api_key, connector_id, and service_type with the values you copied earlier.

    elasticsearch:
  api_key: <key1> # Used to write data to .elastic-connectors and .elastic-connectors-sync-jobs
                # Any connectors without a specific `api_key` value will default to using this key
connectors:
  - connector_id: 1234
    api_key: <key2> # Used to write data to the `search-*` index associated with connector 1234
                    # You may have multiple connectors in your config file!
  - connector_id: 5678
    api_key: <key3> # Used to write data to the `search-*` index associated with connector 5678
  - connector_id: abcd # No explicit api key specified, so this connector will use <key1>

    API keys for connectors

    You can configure multiple connectors in your config.yml file.

    The Kibana UI enables you to create API keys that are scoped to a specific index/connector. If you don’t create an API key for a specific connector, the top-level elasticsearch.api_key or elasticsearch.username:elasticsearch.password value is used.

    If these top-level Elasticsearch credentials are not sufficiently privileged to write to individual connector indices, you’ll need to create these additional, scoped API keys.

    Use the example above as a guide.

Run the connector service
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You need Python version 3.10 or 3.11 to run the connectors service from source.

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

In your terminal or IDE:

  1. cd into the root of your connectors clone/fork.

  2. Run the following commands to compile and run the connector service:

    make install
make run

The connector service should now be running. The UI will let you know that the connector has successfully connected to your Elasticsearch instance.

As a reminder, here we’re working locally. In a production setup, you’ll deploy the connector service to your own infrastructure.

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