Elastic Confluence connector reference

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

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

To create a new Confluence connector:

For additional operations, see Connectors UI in Kibana.

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)

const response = await 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,
});
console.log(response);

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

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

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

For additional operations, see Connectors UI in Kibana.

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

The connector syncs the following Confluence object types:

Full syncs are supported by default for all connectors.

This connector also supports incremental syncs.

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.

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 (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.

See Content extraction.

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.

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.

To create a new Confluence connector:

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)

const response = await 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}",
});
console.log(response);

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

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

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

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

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

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

# 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

docker run \
-v ~/connectors-config:/config \
--network "elastic" \
--tty \
--rm \
docker.elastic.co/enterprise-search/elastic-connectors:8.17.0.0 \
/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.

The connector syncs the following Confluence object types:

Full syncs are supported by default for all connectors.

This connector also supports incremental syncs.

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.

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 (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.

See Content extraction.

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

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.