As of April 10, 2026, Dataplex Universal Catalog is now called Knowledge Catalog. The API, client library, CLI, and IAM names remain unchanged. For more information, see Introducing the Google Cloud Knowledge Catalog.

Monitor Knowledge Catalog logs

This document explains how to access, query, and interpret Knowledge Catalog (formerly Dataplex Universal Catalog) logs using Cloud Logging. Accessing Knowledge Catalog job and service logs helps you troubleshoot issues and monitor data management activities, including AI-powered data discovery and data quality scanning. By centralizing logs in Logging, you can analyze job performance, set up alerts for failures or anomalies, and route logs to other Google Cloud services like BigQuery for long-term retention and analysis.

To understand the costs, see Google Cloud Observability pricing.

For more information about logging retention, see Logs retention periods.

To disable all logs or exclude logs from Logging, see Exclusion filters.

To route logs from Logging to Cloud Storage, BigQuery, or Pub/Sub, see Routing and storage overview.

Use cases

Knowledge Catalog logging supports use cases across different industries:

Troubleshoot data pipeline failures: When a Knowledge Catalog task for data processing fails, process logs provide detailed error messages that help data engineers identify and resolve issues in their Spark jobs or custom tasks.
Monitor data quality: A financial services company can monitor data_quality_scan_rule_result logs to track data quality trends over time, get alerts on quality degradations for critical data assets, and provide auditors with evidence of data quality checks for regulatory compliance.
Track metadata enrichment: A retail company using metadata import jobs to enrich their catalog can use metadata_job logs to verify that imports are completing successfully and that all metadata items are being processed correctly.
Audit data discovery: Organizations can use discovery logs to monitor how and when new data sources are being discovered and registered within Knowledge Catalog, providing an audit trail for data onboarding processes.

How Knowledge Catalog logging works

Knowledge Catalog sends logs for service operations and job executions to Cloud Logging. Each log entry contains details about the operation or job, such as its status, start and end time, associated resources (like a data scan or task), and outcome. Different types of operations, such as data scanning, discovery, metadata import, and data processing, generate different log types, which you can query using logName or the logging query language in Logging.

You can access and analyze these logs using the Logs Explorer in the Google Cloud console or by routing them to other destinations like Cloud Storage buckets or BigQuery tables for further analysis.

Access Knowledge Catalog service logs in Logging

Knowledge Catalog publishes the following service logs to Cloud Logging.

Log type	Log name	`logName` query	Log description
Data scan event logs	`dataplex.googleapis.com/data_scan`	`logName=(projects/$PROJECT_ID/logs/dataplex.googleapis.com%2Fdata_scan)`	Event logs for data scan jobs indicating job state, results, and statistics
Data quality scan rule result logs	`dataplex.googleapis.com/data_quality_scan_rule_result`	`logName=(projects/$PROJECT_ID/logs/dataplex.googleapis.com%2Fdata_quality_scan_rule_result)`	Results of data quality scan rules in a data quality job
Discovery logs	`dataplex.googleapis.com/discovery`	`logName=(projects/$PROJECT_ID/logs/dataplex.googleapis.com%2Fdiscovery)`	Discovery progress and updates over assets in a zone
Metadata job logs	`dataplex.googleapis.com/metadata_job`	`logName=(projects/$PROJECT_ID/logs/dataplex.googleapis.com%2Fmetadata_job)`	Logs about metadata import jobs and import items in the metadata import file
Process logs	`dataplex.googleapis.com/process`	`logName=(projects/$PROJECT_ID/logs/dataplex.googleapis.com%2Fprocess)`	Job runs resulting from data processing tasks

To access Logging, you can use the Logs Explorer in the Google Cloud console, the gcloud logging commands, or the Logging API. You can use the logging query language to build detailed queries.

Query data scan event logs

When you use Knowledge Catalog to create and run a data scan, a data scan event log is produced in Logging for the resulting job.

Console

In the Google Cloud console, go to the Observability > Logging > Logs explorer page.

Go to Logs explorer
Click All resources.
In the Select resource list, click Audited Resource, and then select Cloud Dataplex. Optionally, to filter the logs to a specific method, select the method under Method. Click Apply.
Click All log names.
In the Select log names list, enter dataplex.googleapis.com%2Fdata_scan. Select data_scan to filter logs to data scan event logs, and click Apply.
Optional: For more advanced filtering, use the logging query language to add filters in the log query. For example, to filter to a specific data scan ID or location, add the following filters in the query field, and click Run query:
```
resource.labels.location="LOCATION"
resource.labels.datascan_id="DATA_SCAN_ID"
```

gcloud

To read your data scan event log entries, use the gcloud logging read command with the following query:

gcloud logging read \
    'resource.type="dataplex.googleapis.com/DataScan" AND
    logName=projects/PROJECT_ID/logs/dataplex.googleapis.com%2Fdata_scan AND
    resource.labels.location=LOCATION AND
    resource.labels.datascan_id=DATA_SCAN_ID'
    --limit 10

REST

To list log entries, use the entries.list method.

Query data quality scan rule result logs

When you use Knowledge Catalog to create and run a data quality scan, a data quality scan rule result log is produced in Logging for the resulting job.

Console

In the Google Cloud console, go to the Observability > Logging > Logs explorer page.

Go to Logs explorer
Click All resources.
In the Select resource list, click Audited Resource, and then select Cloud Dataplex. Optionally, to filter the logs to a specific method, select the method under Method. Click Apply.
Click All log names.
In the Select log names list, enter dataplex.googleapis.com%2Fdata_quality_scan_rule_result. Select data_quality_scan_rule_result to filter logs to data quality scan rule result logs, and click Apply.
Optional: For more advanced filtering, use the logging query language to add filters in the log query. For example, to filter to a specific data scan ID or location, add the following filters in the query field, and click Run query:
```
resource.labels.location="LOCATION"
resource.labels.datascan_id="DATA_SCAN_ID"
```

gcloud

To read your data quality scan rule result log entries, use the gcloud logging read command with the following query:

gcloud logging read \
    'resource.type="dataplex.googleapis.com/DataScan" AND
    logName=projects/PROJECT_ID/logs/dataplex.googleapis.com%2Fdata_quality_scan_rule_result AND
    resource.labels.location=LOCATION AND
    resource.labels.datascan_id=DATA_SCAN_ID'
    --limit 10

REST

To list log entries, use the entries.list method.

Query discovery logs

When you use Knowledge Catalog to discover data in assets, a discovery log is produced in Logging.

Console

In the Google Cloud console, go to the Observability > Logging > Logs explorer page.

Go to Logs explorer
Click All resources.
In the Select resource list, click Cloud Dataplex Zone to filter logs to Knowledge Catalog zone resources. Optionally, to filter the logs to a specific asset, select the location, lake, and zone. Click Apply.
Click All log names.
In the Select log names list, enter dataplex.googleapis.com%2Fdiscovery. Select discovery to filter logs to discovery logs, and click Apply.
Optional: For more advanced filtering, use the logging query language to add filters in the log query. For example, to filter to a specific asset, add the following filters in the query field, and click Run query:
```
resource.labels.location="LOCATION"
resource.labels.lake_id="LAKE_ID"
resource.labels.zone_id="ZONE_ID"
jsonPayload.assetId="ASSET_ID"
```

gcloud

To read your discovery log entries, use the gcloud logging read command with the following query:

gcloud logging read \
    'resource.type="dataplex.googleapis.com/Zone" AND
    logName=projects/PROJECT_ID/logs/dataplex.googleapis.com%2Fdiscovery AND
    resource.labels.location=LOCATION AND
    resource.labels.lake_id=LAKE_ID AND
    resource.labels.zone_id=ZONE_ID AND
    jsonPayload.assetId=ASSET_ID'
    --limit 10

REST

To list log entries, use the entries.list method.

Query metadata job logs

When you run a metadata import job, metadata job logs are produced in Logging.

Console

In the Google Cloud console, go to the Observability > Logging > Logs explorer page.

Go to Logs explorer
Click All resources.
In the Select resource list, click Cloud Dataplex Metadata Job to filter logs to metadata job resources. Optionally, to filter the logs to a specific location or metadata job ID, select the location and metadata job ID. Click Apply.
Click All log names.
In the Select log names list, enter dataplex.googleapis.com%2Fmetadata_job. Select metadata_job to filter logs to metadata job logs, and click Apply.
Optional: For more advanced filtering, use the logging query language to add filters in the log query. For more information, see View job logs and troubleshoot.

gcloud

To read your metadata job log entries, use the gcloud logging read command with the following query:

gcloud logging read \
    'resource.type="dataplex.googleapis.com/MetadataJob" AND
    logName=projects/PROJECT_ID/logs/dataplex.googleapis.com%2Fmetadata_job AND
    resource.labels.location=LOCATION AND
    resource.labels.metadata_job_id=METADATA_JOB_ID'
    --limit 10

REST

To list log entries, use the entries.list method.

Query process logs

When you use Knowledge Catalog to schedule and run tasks, a process log is produced in Logging for the resulting job.

Console

In the Google Cloud console, go to the Observability > Logging > Logs explorer page.

Go to Logs explorer
Click All resources.
In the Select resource list, click Cloud Dataplex Task to filter logs to task resources. Optionally, to filter the logs to a specific task or location, select the location, lake, and task. Click Apply.
Click All log names.
In the Select log names list, enter dataplex.googleapis.com%2Fprocess. Select process to filter logs to process logs, and click Apply.
Optional: For more advanced filtering, use the logging query language to add filters in the log query. For example, to filter to a specific task, add the following filters in the query field, and click Run query:
```
resource.labels.location="LOCATION"
resource.labels.lake_id="LAKE_ID"
resource.labels.task_id="TASK_ID"
```

gcloud

To read your process log entries, use the gcloud logging read command with the following query:

gcloud logging read \
    'resource.type="dataplex.googleapis.com/Task" AND
    logName=projects/PROJECT_ID/logs/dataplex.googleapis.com%2Fprocess AND
    resource.labels.location=LOCATION AND
    resource.labels.lake_id=LAKE_ID AND
    resource.labels.task_id=TASK_ID'
    --limit 10

REST

To list log entries, use the entries.list method.

What's next

Learn more about Cloud Logging.
Learn about Knowledge Catalog monitoring.

Monitor Knowledge Catalog logs Stay organized with collections Save and categorize content based on your preferences.

Use cases

How Knowledge Catalog logging works

Access Knowledge Catalog service logs in Logging

Query data scan event logs

Console

gcloud

REST

Query data quality scan rule result logs

Console

gcloud

REST

Query discovery logs

Console

gcloud

REST

Query metadata job logs

Console

gcloud

REST

Query process logs

Console

gcloud

REST

What's next

Monitor Knowledge Catalog logs