GCP Release Notes: March 09, 2026

BigQuery

Feature

Updates to conversational analytics include the following improvements:

• ObjectRef support: BigQuery conversational analytics now integrates with Google Cloud Storage through ObjectRef functions. This lets you reference and interact with unstructured data such as images and PDFs in Cloud Storage buckets in your conversational analysis.
• BQML support: BigQuery conversational analytics now supports a set of BigQuery ML functions, including AI.FORECAST, AI.DETECT_ANOMALIES, and AI.GENERATE. These functions let you perform advanced analytics tasks with simple conversational prompts.
• Chat with BigQuery results: You can now start conversations and chat with query results in BigQuery Studio (SQL editor).
• Enhanced support for partitioned tables: BigQuery conversational analytics can now use BigQuery table partitioning. The agent can optimize SQL queries by using partitioned columns such as date ranges on a date-partitioned table. This can improve query performance and reduce costs.
• Labels for agent-generated queries: BigQuery jobs initiated by the conversational analytics agent are now labeled in BigQuery Job History in the Google Cloud Console. You can identify, filter, and analyze the jobs run by the conversational analytics agent by referencing labels similar to {‘ca-bq-job’: ‘true’}. These labels can help with the following tasks:
  • Monitor and attribute cost.
  • Audit agent activity.
  • Analyze agent-generated query performance.
• Suggest next questions (clickable): When working with BigQuery conversational analytics, the agent now suggests questions that are directly clickable in the Google Cloud console.

This feature is available in Preview.

Cloud Monitoring

Feature

You can configure legend templates for PromQL-formatted charts. To learn more, see Configure the name of a legend column.

Cloud Trace

Change

You can send trace data to your Google Cloud project by using the Cloud Trace API or the Telemetry API. These two APIs are enabled individually.

If you send trace data to the Telemetry API endpoint, then Google Cloud Observability requires that the Cloud Trace API be enabled on your Google Cloud project before it stores the trace data. If the Cloud Trace API is disabled, then Google Cloud Observability discards the trace data.

To learn more, see APIs that ingest trace data.

Looker

Feature

It is no longer necessary to manually configure OAuth credentials when creating a Looker (Google Cloud core) instance that uses only public secure connections and no custom domain. For these instances, Looker (Google Cloud core) now automatically manages OAuth client and secret information, simplifying the setup process. Manual OAuth configuration is still required for instances that use private connections, hybrid connections, or a custom domain.

Security Command Center

Announcement

In March 2026, Risk Engine will launch enhanced heuristics to more accurately identify default high-value resources.

No action is required. As a result of this enhancement, customers using the default high-value resource set may observe changes in the exposure scores of their findings, resources, and issues. Customers using custom resource value configurations are not affected.

Storage Transfer Service

Change

The size limit for manifest files used in agent-based transfers has been removed.

For more information, see Transfer specific files or objects using a manifest.

Source: Google Cloud Platform