DATA OPS
Quarantine Replay for Warehouse-to-Salesforce Sync
On a schedule, replays previously quarantined Snowflake rows back into Salesforce, releases the ones that now succeed.
How it runs
The automated pipeline, trigger to output.
- TriggerScheduled quarantine drain (hourly/nightly)
- ActionRead pending rows from Snowflake quarantine tableSnowflake
- ActionReplay rows into SalesforceSalesforce
- LogicClear successes, bump retry count on failures
- ActionUpdate retry counters in quarantine tableSnowflake
- OutputEscalate over-budget rows as PagerDuty incidentPagerDuty
What it does
Quarantined rows aren't always permanently broken — a missing parent account gets created, a malformed field gets fixed upstream. This workflow periodically re-attempts every row sitting in your quarantine table, pushing it back into Salesforce. Rows that finally succeed are cleared; rows that have failed too many times get escalated so a human looks at them instead of looping forever.
When to use it
Use it alongside a reverse-ETL pipeline that quarantines bad rows. Schedule it hourly or nightly to drain the backlog automatically, so transient upstream fixes resolve without anyone manually re-running anything.
How it works
A schedule trigger reads all pending rows from the Snowflake quarantine table. Each row is re-pushed to Salesforce. A logic step inspects the result and increments a retry counter: successes are deleted from quarantine, failures have their attempt count bumped. Rows whose attempts exceed the configured budget are branched off and raised as a PagerDuty incident with the record id and last error, so they leave the automatic loop and get human ownership.
Set it up
What you configure once, before turning it on.
- 1Connect SnowflakeWarehouses, queries, shares.
- 2Connect SalesforceAccounts, opportunities, cases.
- 3Connect PagerDutyIncidents, on-call, escalations.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
More Data Ops workflows
BigQuery Per-Team Budget Breach Alert to PagerDuty
Tracks month-to-date BigQuery scheduled-query spend per team and, when a team crosses its monthly budget, pages the team's on-call in PagerDuty and snapshots the spend breakdown…
dbt orphan model detector with Linear cleanup tickets
Scans your dbt manifest for models that no other model, exposure, or BI tool consumes.
Weekly BigQuery Cost Trend Sheet and Exec Digest
Compiles week-over-week BigQuery scheduled-query cost by owner and dataset into a Google Sheet with trend columns.
Backfill Missing Owner Labels on BigQuery Scheduled Queries
Finds scheduled queries with no owner label, infers the likely owner from creator metadata and target-table lineage, proposes a label.
Daily BigQuery Scheduled-Query Cost Attribution to Owners
Each morning, totals the prior day's on-demand bytes-billed per scheduled query, maps each query to its owner from a label, and posts a per-owner cost leaderboard to Slack.
dbt source freshness watcher with severity-routed alerts
Checks Snowflake loaded-at timestamps against each dbt source's freshness SLA, then routes warnings to Slack and hard breaches to a PagerDuty incident so stale data never…
Run it inside a business
This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.

Run this workflow in your colony.
14-day trial. No DevOps. No Sales call. Provisioned in under a minute.
