BigQuery is Google Cloud’s serverless data warehouse - the analytical backbone for dashboards, scheduled pipelines, and increasingly the feature stores behind ML. BigQuery incidents rarely lose data; they surface as query failures, jobs stuck in PENDING, or streaming-insert latency in one region, which quietly breaks every dashboard and dbt run downstream.
Queries returning internal errors or running far slower than normal in one region
Jobs stuck in PENDING as scheduling capacity degrades
Streaming inserts / Storage Write API latency and backlog growth
Downstream tools (Looker, dbt, scheduled queries) failing en masse while other GCP services stay green
BigQuery questions
Is BigQuery down right now?+
The live pill above shows our latest check. BigQuery problems tend to be regional and workload-shaped - if ad-hoc queries work but scheduled jobs fail, check the specific job type and region before assuming a full outage.
Why are my BigQuery jobs queued but not failing?+
During capacity or scheduler incidents, BigQuery often degrades by queueing rather than erroring - jobs sit in PENDING. Retrying makes queues worse; if this page shows an active incident, wait for it to clear before re-running pipelines.
Does BigQuery have an SLA?+
Yes - 99.99% monthly uptime. Below that, tiered financial credits apply against the month’s BigQuery charges, claimed within 30 days and capped at 50%.
Get alerted when BigQuery breaks
Instant email the moment we detect an incident - affected services and regions included.
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