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Google Cloud expands AI agent observability and governance across BigQuery and Looker

·2026.11.14 02:17

Key point

The new framework captures telemetry from first-party and custom agents into BigQuery, enabling teams to track reasoning, control token costs, and evaluate accuracy before deployment.

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Details

  • Google Cloud announces expanded AI agent observability and evaluation capabilities across Google Data Cloud, providing unified visibility for first-party agents in BigQuery and Looker and custom third-party agents built with Agent Development Kit (ADK) or LangGraph.
  • A unified telemetry framework captures agent data into customer-owned BigQuery tables, supporting out-of-the-box logging for Conversational Analytics agents and single-line SDK instrumentation for custom agents.
  • Governance features include always-on admin audit logs, VPC Service Controls, customer-managed encryption keys (CMEK), and regional data residency, with privacy guardrails that skip logging when row-level security or dynamic data masking is active.
  • FinOps controls allow teams to track granular token counts and latency, configure per-query BigQuery byte scan caps to block oversized queries, and enforce daily input and output token quotas (in preview) per project, user, or agent.
  • Evaluation tools include Prism, an open-source tool for benchmarking agent accuracy using reusable test suites, and native BigQuery evaluations (in preview) that stream results into day-partitioned tables for side-by-side analysis with production logs.
observabilitygoogle-cloudfinopsai-agentsbigquerylookeragent-analytics
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