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Elastic Azure Blob Storage connector referenceedit

The Elastic Azure Blob Storage connector is a connector for Azure Blob Storage.

Availability and prerequisitesedit

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.

Usageedit

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

For additional operations, see Usage.

Compatibilityedit

This connector has not been tested with Azure Government. Therefore we cannot guarantee that it will work with Azure Government endpoints. For more information on Azure Government compared to Global Azure, refer to the official Microsoft documentation.

Configurationedit

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:

account_name
Name of Azure Blob Storage account.
account_key
Account key for the Azure Blob Storage account.
blob_endpoint
Endpoint for the Blob Service.
retry_count
Number of retry attempts after a failed call. Default value is 3.
concurrent_downloads
Number of concurrent downloads for fetching content. Default value is 100.

Deployment using Dockeredit

Follow these instructions to deploy the Azure Blob Storage connector using Docker.

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-python/main/config.yml --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 azure_blob_storage as the service_type value. Don’t forget to uncomment "azure_blob_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: azure_blob_storage

sources:
  # UNCOMMENT "azure_blob_storage" below to enable the Azure Blob 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:8.8.2.0-SNAPSHOT \
/app/bin/elastic-ingest \
-c /config/config.yml

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

Documents and syncsedit

The connector will fetch all data available in the container.

Sync rulesedit

  • 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 Elastic Deployment.
  • Filtering rules are not yet available. Currently filtering is controlled via ingest pipelines.

Content extractionedit

See Content extraction.

End-to-end testingedit

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 Azure Blob Storage connector, run the following command:

$ make ftest NAME=azure_blob_storage

For faster tests, add the DATA_SIZE=small flag:

make ftest NAME=azure_blob_storage DATA_SIZE=small

Known issuesedit

This connector has the following known issues:

  • lease data and tier fields are not updated in Elasticsearch indices

    This is because the blob timestamp is not updated. Refer to Github issue.

Troubleshootingedit

See Troubleshooting.

Securityedit

See Security.

Framework and sourceedit

This connector is included in the Python connectors framework.

View the source code for this connector (branch 8.8, compatible with Elastic 8.8)

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