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Elastic SharePoint Server connector reference

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Elastic SharePoint Server connector reference

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The Elastic SharePoint Server connector is a connector for Microsoft SharePoint Server.

This connector is written in Python using the open code Elastic connector framework. View the source code for this connector.

Looking for the SharePoint Online connector? See the SharePoint Online reference.

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 service since Elastic 8.15.0. To use this connector, satisfy all managed connector requirements.

This connector is in beta and is subject to change. Beta features are subject to change and are not covered by the support SLA of generally available (GA) features. Elastic plans to promote this feature to GA in a future release.

Create a SharePoint Server connector
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Use the UI

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To create a new SharePoint Server connector:

  1. In the Kibana UI, navigate to the Search → Content → Connectors page from the main menu, or use the global search field.
  2. Follow the instructions to create a new native SharePoint Server 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 SharePoint Server 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-sharepoint_server-connector
{
  "index_name": "my-elasticsearch-index",
  "name": "Content synced from SharePoint Server",
  "service_type": "sharepoint_server",
  "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:

  1. 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
        }
      ]
    }
  }
}

  2. 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"
}

  3. 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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See Elastic managed connectors.

For additional operations, see Connectors UI in Kibana.

Compatibility
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The following SharePoint Server versions are compatible:

  • SharePoint 2013
  • SharePoint 2016
  • SharePoint 2019
Configuration
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The following configuration fields are required to set up the connector:

authentication
Authentication mode, either Basic or NTLM.
username
The username of the account for the SharePoint Server instance.
password
The password of the account.
host_url

The server host url where the SharePoint Server instance is hosted. Examples:

  • https://192.158.1.38:8080
  • https://<tenant_name>.sharepoint.com
site_collections

Comma-separated list of site collections to fetch from SharePoint Server. Examples:

  • collection1
  • collection1, collection2
ssl_enabled
Whether SSL verification will be enabled. Default value is False.
ssl_ca

Content of SSL certificate needed for SharePoint Server. Keep this field empty, if ssl_enabled is set to False.

Example certificate:

-----BEGIN CERTIFICATE-----
MIID+jCCAuKgAwIBAgIGAJJMzlxLMA0GCSqGSIb3DQEBCwUAMHoxCzAJBgNVBAYT
...
7RhLQyWn2u00L7/9Omw=
-----END CERTIFICATE-----
retry_count
The number of retry attempts after a failed request to the SharePoint Server instance. Default value is 3.
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 fetch users' access control lists and store them in a separate index.

Once enabled, the following granular permissions toggles will be available:

  • Fetch unique list permissions: Enable this option to fetch unique list permissions. If this setting is disabled a list will inherit permissions from its parent site.

  • Fetch unique list item permissions: Enable this option to fetch unique list item permissions. If this setting is disabled a list item will inherit permissions from its parent site.

    If left empty the default value true will be used for these granular permissions toggles. Note that these settings may increase sync times.

Documents and syncs
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The connector syncs the following SharePoint object types:

  • Sites and Subsites
  • Lists
  • List Items and its attachment content
  • Document Libraries and its attachment content(include Web Pages)
Sync types
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Full syncs are supported by default for all connectors.

This connector also supports incremental syncs.

Document level security
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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.

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

Advanced sync rules are not available for this connector in the present version. Currently filtering is controlled via ingest pipelines.

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.

Troubleshooting
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See Troubleshooting.

Security
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See Security.

Framework and source
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This connector is written in Python using the Elastic connector framework.

View the source code for this connector (branch main, compatible with Elastic 9.0).

Self-managed connector reference

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View self-managed connector reference
Availability and prerequisites
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This connector is available as a self-managed self-managed connector. This self-managed connector is compatible with Elastic versions 8.9.0+. To use this connector, satisfy all self-managed connector requirements.

This connector is in beta and is subject to change. Beta features are subject to change and are not covered by the support SLA of generally available (GA) features. Elastic plans to promote this feature to GA in a future release.

Create a SharePoint Server connector
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Use the UI

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To create a new SharePoint Server connector:

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

Use the API

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You can use the Elasticsearch Create connector API to create a new self-managed SharePoint Server 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-sharepoint_server-connector
{
  "index_name": "my-elasticsearch-index",
  "name": "Content synced from SharePoint Server",
  "service_type": "sharepoint_server"
}
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:

  1. 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
        }
      ]
    }
  }
}
  2. 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 operations, see Connectors UI in Kibana.

Compatibility
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The following SharePoint Server versions are compatible with the Elastic connector framework:

  • SharePoint 2013
  • SharePoint 2016
  • SharePoint 2019
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:

authentication
Authentication mode, either Basic or NTLM.
username
The username of the account for the SharePoint Server instance.
password
The password of the account.
host_url

The server host url where the SharePoint Server instance is hosted. Examples:

  • https://192.158.1.38:8080
  • https://<tenant_name>.sharepoint.com
site_collections

Comma-separated list of site collections to fetch from SharePoint Server. Examples:

  • collection1
  • collection1, collection2
ssl_enabled
Whether SSL verification will be enabled. Default value is False.
ssl_ca

Content of SSL certificate needed for the SharePoint Server instance. Keep this field empty, if ssl_enabled is set to False.

Example certificate:

-----BEGIN CERTIFICATE-----
MIID+jCCAuKgAwIBAgIGAJJMzlxLMA0GCSqGSIb3DQEBCwUAMHoxCzAJBgNVBAYT
...
7RhLQyWn2u00L7/9Omw=
-----END CERTIFICATE-----
retry_count
The number of retry attempts after failed request to the SharePoint Server instance. Default value is 3.
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 fetch users' access control lists and store them in a separate index.

Once enabled, the following granular permissions toggles will be available:

  • Fetch unique list permissions: Enable this option to fetch unique list permissions. If this setting is disabled a list will inherit permissions from its parent site.

  • Fetch unique list item permissions: Enable this option to fetch unique list item permissions. If this setting is disabled a list item will inherit permissions from its parent site.

    If left empty the default value true will be used for these granular permissions toggles. Note that these settings may increase sync times.

Deployment using Docker
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You can deploy the SharePoint Server 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: sharepoint_server
    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:9.0.0-beta1.0 \
/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 SharePoint object types:

  • Sites and Subsites
  • Lists
  • List Items and its attachment content
  • Document Libraries and its attachment content(include Web Pages)
  • Content from files bigger than 10 MB won’t be extracted by default. Use the self-managed local extraction service to handle larger binary files.
  • Permissions are not synced. All documents indexed to an Elastic deployment will be visible to all users with access to that Elasticsearch Index.
Sync types
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Full syncs are supported by default for all connectors.

This connector also supports incremental syncs, but this feature is currently disabled by default. Refer to the linked documentation for enabling incremental syncs.

Document level security
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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.

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

Advanced sync rules are not available for this connector in the present version. Currently filtering is controlled via ingest pipelines.

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 sharepoint connector, run the following command:

$ make ftest NAME=sharepoint_server

For faster tests, add the DATA_SIZE=small flag:

make ftest NAME=sharepoint_server 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.

Framework and source
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This connector is written in Python using the Elastic connector framework.

View the source code for this connector (branch main, compatible with Elastic 9.0).

« Elastic SharePoint Online connector reference Elastic Slack connector reference »