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.
To use this connector as a connector client, see Connector clients and frameworks.
For additional operations, see Usage.
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.
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:
- Name of Azure Blob Storage account.
- Account key for the Azure Blob Storage account.
- Endpoint for the Blob Service.
Number of retry attempts after a failed call.
Default value is
Number of concurrent downloads for fetching content.
Default value is
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:
Use azure_blob_storage as the
Don’t forget to uncomment "azure_blob_storage" in the
sources section of the
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
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:22.214.171.124-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.
- 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.
See Content extraction.
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
make ftest NAME=azure_blob_storage DATA_SIZE=small
This connector has the following known issues:
tierfields are not updated in Elasticsearch indices
This is because the blob timestamp is not updated. Refer to Github issue.
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)
Intro to Kibana
ELK for Logs & Metrics