IMPORTANT: No additional bug fixes or documentation updates will be released for this version. For the latest information, see the current release documentation.
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Google Cloud Storage Connector

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Google Cloud Storage Connector

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The Elastic Google Cloud Storage connector is a connector for Google Cloud Storage data sources.

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 8.6.0+. 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.

Usage

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The Google Cloud Storage service account must have (at least) the following scopes and roles:

  • resourcemanager.projects.get
  • serviceusage.services.use
  • storage.buckets.list
  • storage.objects.list
  • storage.objects.get

Google Cloud Storage service account credentials are stored in a JSON file.

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:

service_account_credentials
The service account credentials generated from Google Cloud Storage (JSON string). Refer to the Google Cloud documentation for more information.
retry_count
The number of retry attempts after a failed call to Google Cloud Storage. Default value is 3.

Deployment using Docker

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You can deploy the Google Cloud Storage 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 google_cloud_storage as the service_type value. Don’t forget to uncomment "google_cloud_storage" 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: google_cloud_storage

sources:
  # UNCOMMENT "google_cloud_storage" below to enable the Google Cloud Storage 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 will fetch all buckets and paths the service account has access to.

The Owner field is not fetched as read_only scope doesn’t allow the connector to fetch IAM information.

  • Files bigger than 10 MB won’t be extracted.
  • Permission are not synced. All documents indexed to an Elastic deployment will be visible to all users with access to that Elastic Deployment.

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 by ingest pipelines.

Content extraction

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See Content extraction.

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 Google Cloud Storage connector, run the following command:

$ make ftest NAME=google_cloud_storage

For faster tests, add the DATA_SIZE=small flag:

make ftest NAME=google_cloud_storage DATA_SIZE=small

Known issues

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There are currently no known issues for this connector.

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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