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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.

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

Availability and prerequisites

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This connector is available as a connector client from the Python connectors framework. This connector client is compatible with Elastic versions 8.9.0+. To use this connector, satisfy all connector client 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.

Usage

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

For additional operations, see Using connectors.

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 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:

username
The username of the account for SharePoint Server.
password
The password of the account to be used for the SharePoint Server.
host_url

The server host url where the SharePoint 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. 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 failed request to the SharePoint. Default value is 3.

Deployment using Docker

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You can deploy the SharePoint Server 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/main/config.yml.example --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.password
  • connector_id
  • service_type

Use sharepoint_server as the service_type value. Don’t forget to uncomment "sharepoint_server" in the sources section of the yaml file.

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

elasticsearch:
  host: http://host.docker.internal:9200
  username: elastic
  password: <YOUR_PASSWORD>

connector_id: <CONNECTOR_ID_FROM_KIBANA>
service_type: sharepoint_server

sources:
  # UNCOMMENT "sharepoint_server" below to enable the SharePoint Server connector

  #mongodb: connectors.sources.mongo:MongoDataSource
  #s3: connectors.sources.s3:S3DataSource
  #dir: connectors.sources.directory:DirectoryDataSource
  #mysql: connectors.sources.mysql:MySqlDataSource
  #network_drive: connectors.sources.network_drive:NASDataSource
  #google_cloud_storage: connectors.sources.google_cloud_storage:GoogleCloudStorageDataSource
  #azure_blob_storage: connectors.sources.azure_blob_storage:AzureBlobStorageDataSource
  #postgresql: connectors.sources.postgresql:PostgreSQLDataSource
  #oracle: connectors.sources.oracle:OracleDataSource
  #mssql: connectors.sources.mssql:MSSQLDataSource

Note that the config file you downloaded might contain more entries, so you will need to manually copy/change the settings that apply to you. Normally you’ll only need to update elasticsearch.host, elasticsearch.password, connector_id and service_type to run the connector service.

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:8.9.2.0-SNAPSHOT \
/app/bin/elastic-ingest \
-c /config/config.yml

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

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 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 Elasticsearch Index.

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.

Connector client 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 included in the Python connectors framework.

View the source code for this connector (branch 8.9, compatible with Elastic 8.9).

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