Google Adds Cloud Logging for BigQuery Python Functions

Developers can now route Python UDF logs directly to Google Cloud Logging for improved monitoring.

Updated on Oct. 29, 2026 in Quantum Computing

Isometric editorial illustration of a single large architectural server cube, symbolizing cloud data logging infrastructure. — Google has enabled Cloud Logging for Python User-Defined Functions in BigQuery, allowing developers to route and monitor structured logs for complex data tasks. AI Illustration. Upload story photo >

Live Poll

Do you find that new automated monitoring features make your data pipelines easier to manage?

Google has introduced cloud logging support for Python User-Defined Functions (UDFs) within BigQuery. This feature allows developers to use standard Python logging libraries to route structured logs to Cloud Logging for easier operational monitoring.

Why it matters

The integration allows data pipelines to continue running by isolating malformed records for triage instead of halting the entire workload. It provides developers with a streamlined way to debug code and monitor complex data processing tasks in real time.

The logging workflow consists of 3 stages, including inline validation, real-time alerting via Cloud Monitoring, and SQL-based triage. Developers enable the capability by setting specific UDF properties within a session.

The players

Google

Google is a global technology corporation that specializes in internet-related services, including cloud computing and data analytics.

BigQuery

BigQuery is a fully managed, serverless enterprise data warehouse that enables scalable analysis over petabytes of data.

Cloud Logging

Cloud Logging is a fully managed service that performs at scale and can ingest application and system log data from thousands of virtual machine instances.

The details

Logs from Python UDFs are now visible in Logs Explorer, searchable by resource type and severity. Furthermore, these logs can be queried directly through an _AllLogs view within BigQuery, provided the user has appropriate Logging Viewer permissions.

Google announced the new cloud logging feature on October 29, 2026.

The Tech Race

This update represents an evolution of Google Cloud's BigQuery service by integrating deeper observability into serverless data pipelines. By standardizing logging, Google is positioning its platform to compete against other enterprise-grade data warehouse providers that offer integrated developer tools.

Developers can now debug complex data transformation pipelines without the need for cumbersome manual workarounds. This change reduces downtime by allowing individual errors to be isolated and addressed without stopping production-level data workflows.

The takeaway

Developers should update their UDF properties to enable this visibility for all active data processing sessions. Implementing structured logs early in the development lifecycle will significantly reduce the time required to triage malformed data records in production.