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Elastic Confluence connector reference

The Elastic Confluence connector is a connector for Atlassian Confluence. This connector is written in Python using the Elastic connector framework.

View the source code for this connector (branch 8.16, compatible with Elastic 8.16).

Elastic managed connector reference

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View Elastic managed connector reference

Availability and prerequisites

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This connector is available as a managed connector on Elastic Cloud, as of 8.9.1.

Confluence Data Center support was added in 8.13.0 in technical preview 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. Technical preview features are not subject to the support SLA of official GA features.

To use this connector natively in Elastic Cloud, satisfy all managed connector requirements.

Create a Confluence connector

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Use the UI

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To create a new Confluence connector:

In the Kibana UI, navigate to the Search → Content → Connectors page from the main menu, or use the global search field.
Follow the instructions to create a new native Confluence connector.

For additional operations, see Connectors UI in Kibana.

Use the API

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You can use the Elasticsearch Create connector API to create a new native Confluence connector.

For example:

resp = client.connector.put(
    connector_id="my-{service-name-stub}-connector",
    index_name="my-elasticsearch-index",
    name="Content synced from {service-name}",
    service_type="{service-name-stub}",
    is_native=True,
)
print(resp)

PUT _connector/my-confluence-connector
{
  "index_name": "my-elasticsearch-index",
  "name": "Content synced from Confluence",
  "service_type": "confluence",
  "is_native": true
}

You’ll also need to create an API key for the connector to use.

The user needs the cluster privileges manage_api_key, manage_connector and write_connector_secrets to generate API keys programmatically.

To create an API key for the connector:

Run the following command, replacing values where indicated. Note the id and encoded return values from the response:

resp = client.security.create_api_key(
    name="my-connector-api-key",
    role_descriptors={
        "my-connector-connector-role": {
            "cluster": [
                "monitor",
                "manage_connector"
            ],
            "indices": [
                {
                    "names": [
                        "my-index_name",
                        ".search-acl-filter-my-index_name",
                        ".elastic-connectors*"
                    ],
                    "privileges": [
                        "all"
                    ],
                    "allow_restricted_indices": False
                }
            ]
        }
    },
)
print(resp)

const response = await client.security.createApiKey({
  name: "my-connector-api-key",
  role_descriptors: {
    "my-connector-connector-role": {
      cluster: ["monitor", "manage_connector"],
      indices: [
        {
          names: [
            "my-index_name",
            ".search-acl-filter-my-index_name",
            ".elastic-connectors*",
          ],
          privileges: ["all"],
          allow_restricted_indices: false,
        },
      ],
    },
  },
});
console.log(response);

POST /_security/api_key
{
  "name": "my-connector-api-key",
  "role_descriptors": {
    "my-connector-connector-role": {
      "cluster": [
        "monitor",
        "manage_connector"
      ],
      "indices": [
        {
          "names": [
            "my-index_name",
            ".search-acl-filter-my-index_name",
            ".elastic-connectors*"
          ],
          "privileges": [
            "all"
          ],
          "allow_restricted_indices": false
        }
      ]
    }
  }
}

Use the encoded value to store a connector secret, and note the id return value from this response:

resp = client.connector.secret_post(
    body={
        "value": "encoded_api_key"
    },
)
print(resp)

const response = await client.connector.secretPost({
  body: {
    value: "encoded_api_key",
  },
});
console.log(response);

POST _connector/_secret
{
  "value": "encoded_api_key"
}

Use the API key id and the connector secret id to update the connector:

resp = client.connector.update_api_key_id(
    connector_id="my_connector_id>",
    api_key_id="API key_id",
    api_key_secret_id="secret_id",
)
print(resp)

const response = await client.connector.updateApiKeyId({
  connector_id: "my_connector_id>",
  api_key_id: "API key_id",
  api_key_secret_id: "secret_id",
});
console.log(response);

PUT /_connector/my_connector_id>/_api_key_id
{
  "api_key_id": "API key_id",
  "api_key_secret_id": "secret_id"
}

Refer to the Elasticsearch API documentation for details of all available Connector APIs.

Usage

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To use this connector as a managed connector, see Elastic managed connectors .

For additional operations, see Connectors UI in Kibana.

Compatibility

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Confluence Cloud or Confluence Server/Data Center versions 7 or later.

Configuration

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

Confluence data source

Dropdown to determine the Confluence platform type: Confluence Cloud, Confluence Server, or Confluence Data Center. Default value is Confluence Server.

Confluence Data Center username

The username of the account for Confluence Data Center.

Confluence Data Center password

The password of the account to be used for the Confluence Data Center.

Confluence Server username

The username of the account for Confluence server.

Confluence Server password

The password of the account to be used for Confluence Server.

Confluence Cloud account email

The account email for Confluence Cloud.

Confluence Cloud API token

The API Token to authenticate with Confluence cloud.

Confluence URL label

The domain where the Confluence is hosted. Examples:

https://192.158.1.38:8080/
https://test_user.atlassian.net/

Confluence space keys

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
*

Enable indexing labels

Toggle to enable syncing of labels from pages. NOTE: This will increase the amount of network calls to the source, and may decrease performance.

Enable SSL

Whether SSL verification will be enabled. Default value is False.

SSL certificate

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

-----BEGIN CERTIFICATE-----
MIID+jCCAuKgAwIBAgIGAJJMzlxLMA0GCSqGSIb3DQEBCwUAMHoxCzAJBgNVBAYT
...
7RhLQyWn2u00L7/9Omw=
-----END CERTIFICATE-----

Enable document level security

Toggle to enable document level security (DLS). When enabled, full 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.

Documents and syncs

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The connector syncs the following Confluence object types:

Pages
Spaces
Blog Posts
Attachments

Content from files bigger than 10 MB won’t be extracted. (Self-managed connectors can use the self-managed local extraction service to handle larger binary files.)
Permissions are not synced by default. You must first enable DLS. Otherwise, all documents indexed to an Elastic deployment will be visible to all users with access to that Elastic Deployment.

Sync types

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Full syncs are supported by default for all connectors.

This connector also supports incremental syncs.

Sync rules

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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 examples

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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 security

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DLS is automatically available for Atlassian Confluence Cloud since 8.9.0. DLS is available since 8.14.0 for Confluence Server and Confluence Data Center, but requires installing Extender for Confluence.

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.

When the data_source is set to Confluence Data Center or Server, the connector will only fetch 1000 users for access control syncs, due a limitation in the API used.

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 Extraction

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See Content extraction.

Known issues

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

View self-managed connector reference

Availability and prerequisites

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This connector is available as a self-managed connector using the Elastic connector framework. This self-managed connector is compatible with Elastic versions 8.7.0+.

To use this connector, satisfy all self-managed connector requirements.

Create a Confluence connector

edit

Use the UI

edit

To create a new Confluence connector:

In the Kibana UI, navigate to the Search → Content → Connectors page from the main menu, or use the global search field.
Follow the instructions to create a new Confluence self-managed connector.

Use the API

edit

You can use the Elasticsearch Create connector API to create a new self-managed Confluence self-managed connector.

For example:

resp = client.connector.put(
    connector_id="my-{service-name-stub}-connector",
    index_name="my-elasticsearch-index",
    name="Content synced from {service-name}",
    service_type="{service-name-stub}",
)
print(resp)

PUT _connector/my-confluence-connector
{
  "index_name": "my-elasticsearch-index",
  "name": "Content synced from Confluence",
  "service_type": "confluence"
}

You’ll also need to create an API key for the connector to use.

The user needs the cluster privileges manage_api_key, manage_connector and write_connector_secrets to generate API keys programmatically.

To create an API key for the connector:

Run the following command, replacing values where indicated. Note the encoded return values from the response:

resp = client.security.create_api_key(
    name="connector_name-connector-api-key",
    role_descriptors={
        "connector_name-connector-role": {
            "cluster": [
                "monitor",
                "manage_connector"
            ],
            "indices": [
                {
                    "names": [
                        "index_name",
                        ".search-acl-filter-index_name",
                        ".elastic-connectors*"
                    ],
                    "privileges": [
                        "all"
                    ],
                    "allow_restricted_indices": False
                }
            ]
        }
    },
)
print(resp)

const response = await client.security.createApiKey({
  name: "connector_name-connector-api-key",
  role_descriptors: {
    "connector_name-connector-role": {
      cluster: ["monitor", "manage_connector"],
      indices: [
        {
          names: [
            "index_name",
            ".search-acl-filter-index_name",
            ".elastic-connectors*",
          ],
          privileges: ["all"],
          allow_restricted_indices: false,
        },
      ],
    },
  },
});
console.log(response);

POST /_security/api_key
{
  "name": "connector_name-connector-api-key",
  "role_descriptors": {
    "connector_name-connector-role": {
      "cluster": [
        "monitor",
        "manage_connector"
      ],
      "indices": [
        {
          "names": [
            "index_name",
            ".search-acl-filter-index_name",
            ".elastic-connectors*"
          ],
          "privileges": [
            "all"
          ],
          "allow_restricted_indices": false
        }
      ]
    }
  }
}

Update your config.yml file with the API key encoded value.

Refer to the Elasticsearch API documentation for details of all available Connector APIs.

Usage

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To use this connector as a self-managed connector, see Self-managed connectors For additional usage operations, see Connectors UI in Kibana.

Compatibility

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Confluence Cloud or Confluence Server/Data Center versions 7 or later

Configuration

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When using the self-managed connector 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:

data_source

Dropdown to determine the Confluence platform type: Confluence Cloud, Confluence Server, or Confluence Data Center. Default value is Confluence Server.

data_center_username

The username of the account for Confluence Data Center.

data_center_password

The password of the account to be used for the Confluence Data Center.

username

The username of the account for Confluence Server.

password

The password of the account to be used for the Confluence server.

account_email

The account email for the Confluence Cloud.

api_token

The API Token to authenticate with Confluence Cloud.

confluence_url

The domain where the Confluence instance is hosted. Examples:

https://192.158.1.38:8080/
https://test_user.atlassian.net/

spaces

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

EC, TP
*

index_labels

Toggle to enable syncing of labels from pages. NOTE: This will increase the amount of network calls to the source, and may decrease performance.

ssl_enabled

Whether SSL verification will be enabled. Default value is False.

ssl_ca

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

-----BEGIN CERTIFICATE-----
MIID+jCCAuKgAwIBAgIGAJJMzlxLMA0GCSqGSIb3DQEBCwUAMHoxCzAJBgNVBAYT
...
7RhLQyWn2u00L7/9Omw=
-----END CERTIFICATE-----

retry_count

The number of retry attempts after failed request to Confluence. Default value is 3.

concurrent_downloads

The number of concurrent downloads for fetching the attachment content. This speeds up the content extraction of attachments. Defaults to 50.

use_document_level_security

Toggle to enable document level security (DLS).

When enabled, full 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.

use_text_extraction_service

Toggle to enable the local text extraction service. Default value is False. Requires a separate deployment of the Elastic Text Extraction Service. Requires that ingest pipeline settings disable text extraction.

Deployment using Docker

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You can deploy the Confluence connector as a self-managed connector 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/main/config.yml.example --output ~/connectors-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>

connectors:
  -
    connector_id: <CONNECTOR_ID_FROM_KIBANA>
    service_type: confluence
    api_key: <CONNECTOR_API_KEY_FROM_KIBANA> # Optional. If not provided, the connector will use the elasticsearch.api_key instead

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-config:/config \
--network "elastic" \
--tty \
--rm \
docker.elastic.co/integrations/elastic-connectors:8.16.0.0 \
/app/bin/elastic-ingest \
-c /config/config.yml

Refer to DOCKER.md in the elastic/connectors repo for more details.

Find all available Docker images in the official registry.

We also have a quickstart self-managed option using Docker Compose, so you can spin up all required services at once: Elasticsearch, Kibana, and the connectors service. Refer to this README in the elastic/connectors repo for more information.

Documents and syncs

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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 types

edit

Full syncs are supported by default for all connectors.

This connector also supports incremental syncs.

Sync rules

edit

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

Advanced sync rules examples

edit

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'"
  }
]

Document level security

edit

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.

When the data_source is set to Confluence Data Center or Server, the connector will only fetch 1000 users for access control syncs, due a limitation in the API used.

Content Extraction

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See Content extraction.

Self-managed connector operations

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End-to-end testing

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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 issues

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

Troubleshooting

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See Troubleshooting.

Security

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See Security.

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