Elastic Confluence connector referenceedit

The Elastic Confluence connector is a connector for Atlassian Confluence.

Availability and prerequisitesedit

This connector is available as a connector client using the Python connectors framework. This connector client is compatible with Elastic versions 8.7.0+. To use this connector, satisfy all connector client requirements.

This connector is in beta and is subject to change. The design and code is less mature than official GA features and is being provided as-is with no warranties. Beta features are not subject to the support SLA of official GA features.


To use this connector as a native connector, see Native connectors logo cloud (managed service).

To use this connector as a connector client, see Connector clients.

For additional operations, see Using connectors.


  • Confluence Cloud or Confluence Server versions 7 or later.
  • Confluence Data Center editions are not currently supported.


When using the connector client workflow, initially these fields will use the default configuration set in the connector source code. These are set in the get_default_configuration function definition.

These configurable fields will be rendered with their respective labels in the Kibana UI. Once connected, you’ll be able to update these values in Kibana.

The following configuration fields are required to set up the connector:

Dropdown to determine the Confluence platform type: Confluence Cloud or Confluence Server. Default value is Confluence Server.
The username of the account for Confluence server.
The password of the account to be used for the Confluence server.
The account email for the Confluence cloud.
The API Token to authenticate with Confluence cloud.

The domain where the Confluence is hosted. Examples:

  • https://test_user.atlassian.net/

Comma-separated list of Space Keys to fetch data from Confluence server or cloud. If the value is *, the connector will fetch data from all spaces present in the configured spaces. Default value is *. Examples:

  • EC, TP
  • *
Whether SSL verification will be enabled. Default value is False.

Content of SSL certificate. Note: If ssl_enabled is False, the value in this field is ignored. Example certificate:

The number of retry attempts after failed request to Confluence. Default value is 3.
The number of concurrent downloads for fetching the attachment content. This speeds up the content extraction of attachments. Defaults to 50.
Enable document level security

Toggle to enable document level security (DLS). Only available for Atlassian Confluence Cloud. When enabled, full and incremental syncs will fetch access control lists for each document and store them in the _allow_access_control field. Access control syncs will fetch users' access control lists and store them in a separate index.

To access user data in Jira Administration, the account you created must be granted Product Access for Jira Administration. This access needs to be provided by an administrator from the Atlassian Admin, and the access level granted should be Product Admin.

Deployment using Dockeredit

You can deploy the Confluence connector as a self-managed connector client using Docker. Follow these instructions.

Step 1: Download sample configuration file

Download the sample configuration file. You can either download it manually or run the following command:

curl https://raw.githubusercontent.com/elastic/connectors-python/main/config.yml --output ~/connectors-python-config/config.yml

Remember to update the --output argument value if your directory name is different, or you want to use a different config file name.

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

Update the configuration file with the following settings to match your environment:

  • elasticsearch.host
  • elasticsearch.api_key
  • connectors

If you’re running the connector service against a Dockerized version of Elasticsearch and Kibana, your config file will look like this:

# When connecting to your cloud deployment you should edit the host value
elasticsearch.host: http://host.docker.internal:9200
elasticsearch.api_key: <ELASTICSEARCH_API_KEY>

    connector_id: <CONNECTOR_ID_FROM_KIBANA>
    service_type: confluence

Using the elasticsearch.api_key is the recommended authentication method. However, you can also use elasticsearch.username and elasticsearch.password to authenticate with your Elasticsearch instance.

Note: You can change other default configurations by simply uncommenting specific settings in the configuration file and modifying their values.

Step 3: Run the Docker image

Run the Docker image with the Connector Service using the following command:

docker run \
-v ~/connectors-python-config:/config \
--network "elastic" \
--tty \
--rm \
docker.elastic.co/enterprise-search/elastic-connectors: \
/app/bin/elastic-ingest \
-c /config/config.yml

Refer to this guide in the Python framework repository for more details.

Documents and syncsedit

The connector syncs the following Confluence object types:

  • Pages
  • Spaces
  • Blog Posts
  • Attachments
  • Content of files bigger than 10 MB won’t be extracted.
  • Permissions are not synced. All documents indexed to an Elastic deployment will be visible to all users with access to that Elastic Deployment.

Sync rulesedit

Basic sync rules are identical for all connectors and are available by default.

This connector supports advanced sync rules for remote filtering. These rules cover complex query-and-filter scenarios that cannot be expressed with <basic sync rules. Advanced sync rules are defined through a source-specific DSL JSON snippet.

Advanced sync rules examplesedit

Example 1: Query for indexing data that is in a particular Space with key DEV.

    "query": "space = DEV"

Example 2: Queries for indexing data based on created and lastmodified time.

    "query": "created >= now('-5w')"
    "query": "lastmodified < startOfYear()"

Example 3: Query for indexing only given types in a Space with key SD.

    "query": "type in ('page', 'attachment') AND space.key = 'SD'"

Syncing recently created/updated items in Confluence may be delayed when using advanced sync rules, because the search endpoint used for CQL queries returns stale results in the response. For more details refer to the following issue in the Confluence documentation.

Document level securityedit

DLS is only available for Atlassian Confluence Cloud.

Document level security (DLS) enables you to restrict access to documents based on a user’s permissions. Refer to configuration on this page for how to enable DLS for this connector.

Refer to DLS in Search Applications to learn how to ingest data from a connector with DLS enabled, when building a search application. The example uses SharePoint Online as the data source, but the same steps apply to every connector.

Content Extractionedit

See Content extraction.

Connector client operationsedit

End-to-end testingedit

The connector framework enables operators to run functional tests against a real data source. Refer to Connector testing for more details.

To perform E2E testing for the Confluence connector, run the following command:

$ make ftest NAME=confluence

For faster tests, add the DATA_SIZE=small flag:

make ftest NAME=confluence DATA_SIZE=small

Known issuesedit

There are currently no known issues for this connector. Refer to Known issues for a list of known issues for all connectors.


See Troubleshooting.


See Security.

Framework and sourceedit

This connector is included in the Python connectors framework.

View the source code for this connector (branch 8.10, compatible with Elastic 8.10).