DATA OPS
Page on-call when a high-tier BigQuery table loses a critical column
When a tier-1 BigQuery table drops or retypes a column marked critical, open a PagerDuty incident and post the blast radius so on-call can decide whether to halt downstream loads.
How it runs
The automated pipeline, trigger to output.
- TriggerScheduled tier-1 schema poll
- ActionDiff tier-1 table columns in BigQueryBigQuery
- LogicExit unless a critical column dropped or retyped
- ActionCount downstream dbt models from GitLab lineageGitLab
- ActionOpen PagerDuty incident sized to blast radiusPagerDuty
- OutputPost impact summary to incident Slack channelSlack
What it does
Treats schema loss on your most important tables as an operational incident, not just a notification. For tables you've tagged tier-1, if a column marked critical disappears or changes type, it pages on-call through PagerDuty, attaches the count of downstream dbt models and dashboards affected, and links the evidence so the responder can decide in seconds whether to pause loads.
When to use it
Use it for the handful of tables that, if they break, take down revenue reporting or customer-facing metrics. A Slack message is too quiet for those — you want a real page with the blast radius already attached so on-call isn't starting from zero at 2am.
How it works
- 1A schedule polls schemas for tier-1 tables in BigQuery.
- 2It diffs columns and isolates changes to any column on the critical list.
- 3A logic gate exits unless a critical column was dropped or retyped.
- 4It counts downstream dbt models from the GitLab lineage to size the impact.
- 5It opens a PagerDuty incident with severity scaled to the blast-radius count.
- 6It posts the same summary into the incident's Slack channel for context.
Set it up
What you configure once, before turning it on.
- 1Connect BigQueryDatasets, queries, schemas.
- 2Connect GitLabRepos, MRs, pipelines, registry.
- 3Connect PagerDutyIncidents, on-call, escalations.
- 4Connect SlackChannels, DMs, threads, mentions.
- 5Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 6Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 7Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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