ADLS Connector

This page contains the setup guide and reference information for the ADLS connector. Configure and schedule ADLS metadata workflows from the Collate UI:

• Requirements
• Metadata Ingestion
• Troubleshooting

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Requirements

We need the following permissions in Azure Data Lake Storage:

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ADLS Permissions

To extract metadata from Azure ADLS (Storage Account - StorageV2), you will need an App Registration with the following permissions on the Storage Account:

• Storage Blob Data Contributor
• Storage Queue Data Contributor

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Collate Manifest

In any other connector, extracting metadata happens automatically. In this case, we will be able to extract high-level metadata from buckets, but in order to understand their internal structure we need users to provide an openmetadata.json file at the bucket root. Supported File Formats: [ "csv", "tsv", "avro", "parquet", "json", "json.gz", "json.zip" ] You can learn more about this here. Keep reading for an example on the shape of the manifest file.

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Collate Manifest

Our manifest file is defined as a JSON Schema, and can look like this:

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Global Manifest

You can also manage a single manifest file to centralize the ingestion process for any container, named openmetadata_storage_manifest.json. You can also keep local manifests openmetadata.json in each container, but if possible, we will always try to pick up the global manifest during the ingestion.

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Metadata Ingestion

To ingest metadata from ADLS, you need to create a service connection. The service connects ADLS with Collate. Once you create a service, Collate automatically starts ingesting metadata.

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Step 1: Add New Service

1. In the left navigation, click Connections.
2. On the Connections page, click Add New Service.

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Step 2: Select a Service and Connector

From the service type dropdown, select Storage Services, then click the ADLS connector tile.

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Step 3: Add Service Name and Description

• Enter a unique, descriptive Service Name. Collate identifies services by their service name. Enter a name that distinguishes this deployment from other ADLS services you are ingesting metadata from.
• Optional: Enter a Description for the service.

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Step 4: Configure Connection Options

Specify where ingestion runs, provide your source credentials, and verify the connection.

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Select Ingestion Runner

Select an Ingestion Runner: the runner where the ingestion pipeline will execute.

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Enter Connection Details

Enter the connection details for ADLS. The right-hand panel in the UI displays inline help for each field.

• Client ID: This unique identifier is assigned to your Azure Service Principal App, serving as a key for authentication and authorization.
• Client Secret: This confidential password is associated with the Service Principal, safeguarding access to Azure resources and ensuring secure communication.
• Tenant ID: Identifying your Azure Subscription, the Tenant ID links your resources to a specific organization or account within the Azure Active Directory.
• Storage Account Name: This is the user-defined name for your Azure Storage Account, providing a globally unique namespace for your data.
• Key Vault Name: Azure Key Vault serves as a centralized secrets manager, securely storing and managing sensitive information, such as connection strings and cryptographic keys.

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Test Connection

Once the credentials have been added, click on Test Connection and Save the changes.

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Step 5: Configure Ingestion Options

In the What to Ingest step, use filter patterns to control which assets Collate ingests from your storage service. Filter patterns use regular expressions applied to container names.

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How Filter Patterns Work

• Include: Add one or more comma-separated regular expressions. Collate ingests only containers whose names match at least one expression. Leave blank to include all containers.
• Exclude: Add one or more comma-separated regular expressions. Collate skips any container whose name matches an expression. Leave blank to exclude nothing.

Rules match asset names using one of five expressions:

• contains: matches any name containing the value. For example, sales matches my_sales_data and sales_2024.
• starts with: matches names beginning with the value. For example, prod_ matches prod_db and prod_schema.
• ends with: matches names ending with the value. For example, _raw matches events_raw and logs_raw.
• is exactly: matches the exact name only. For example, analytics matches only analytics.
• matches regex: matches names using a regular expression. For example, ^prod_.*_v\d+$ matches prod_events_v1.

When both Include and Exclude are set, Exclude takes priority. Filter Options The Container section includes the following filter options:

• Container: Controls which top-level storage containers (S3 buckets, ADLS containers, or GCS buckets) Collate ingests from the source.

Each section provides the following controls:

• Scan Mode: You can choose between the following scan modes:
  • Scan all: Ingests every asset of that type the connector can access. This is the default.
  • Only specific: Enables include rules so only assets matching at least one rule are ingested.
• Exclude system toggle: Use this toggle to automatically filter out system-reserved names defined by the connector — for example, Exclude system databases for the Databases section.
• Always exclude: Add permanent exclusion rules (shown in red). Assets matching these rules are never ingested, regardless of include rules.
• Preview: Shows a real-time summary of what will be in scope based on your current rules.
• Include rules (available only in Only specific mode): Click + Add to define a rule. Added rules appear as chips; an asset is included if it matches any rule.

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Step 6: Create & Deploy

Click Create & Deploy to deploy the agent and start the first metadata ingestion run. Collate saves the service configuration and immediately begins pulling metadata from the source. To monitor ingestion progress or view the service you just added, go to Connections in the left navigation and select your service.

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Configure Metadata Agent and Schedule Ingestion

The Metadata Agent extracts containers, objects, and other structural metadata from your source and keeps your Collate catalog in sync. It powers discovery, lineage, and governance across your data assets. When you click Create & Deploy, Collate automatically deploys a Metadata Agent for this service and triggers the first ingestion run. View its status and run history from the Agents tab on the service detail page. To configure the additional Metadata Agent and schedule ingestion, follow these steps:

1. In the left navigation, click Connections and select your service.
2. Click the Agents tab.
3. Click Add Agent and select Metadata from the dropdown. For some services, the dropdown is not available and clicking Add Agent takes you directly to the agent configuration page.
4. On the Configure Ingestion page, do the following and click Next.
   • Name this Ingestion: Enter a unique recognizable name for this ingestion pipeline.
   • Filter Patterns: Apply include or exclude rules to scope which containers this agent ingests. These follow the same filter options described in Step 5.
   • Scope & Behaviour: Control how the agent handles metadata during ingestion. Toggle each option on or off based on your needs:

     Toggle	Default	Description
     Mark Deleted Containers	On	Soft-delete containers in Collate when they are removed from the source.
     Include Tags	Off	Ingest tags from the source.
     Override Metadata	Off	When on, source values overwrite existing descriptions, tags, owners, and display names in Collate. When off, Collate only updates fields that have no existing value.
     Enable Debug Log	Off	Sets the ingestion log level to DEBUG. Useful for troubleshooting.

5. On the Schedule Interval page, set when the agent runs:
   • Schedule: Choose a preset interval (Hourly, Daily, Weekly, Monthly) or enter a custom cron expression.
   • On-Demand: No automatic schedule; trigger the agent manually when needed.
   
6. Click Add to deploy the agent.

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Troubleshooting