Google Cloud Storage Connector
editGoogle Cloud Storage Connector
editThe Elastic Google Cloud Storage connector is a connector for Google Cloud Storage data sources.
Availability and prerequisites
editThis 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
editThe 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
editWhen 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
editYou 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
editThe 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
editBasic 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
editSee Content extraction.
End-to-end testing
editThe 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
editThere are currently no known issues for this connector.
Troubleshooting
editSee Troubleshooting.
Security
editSee Security.
Framework and source
editThis connector is included in the Python connectors framework.
View the source code for this connector (branch 8.9, compatible with Elastic 8.9).