DATA OPS
CSV Header-Drift Sentinel that Quarantines Mismatched S3 Drop Files
Triggered when a new file lands in an S3 ingest bucket, it checks the CSV header against the expected column contract and moves any file whose headers drifted to a quarantine…
How it runs
The automated pipeline, trigger to output.
- TriggerNew CSV file created in S3 landing bucketAWS S3
- ActionRead CSV header row from S3AWS S3
- LogicCompare headers to contract; branch on drift
- ActionMove mismatched file to S3 quarantine prefixAWS S3
- OutputAlert source owner in Slack with header diffSlack
What it does
This sentinel guards a file-drop ingestion path. Every time a partner or upstream job writes a CSV to your S3 landing bucket, it reads just the header row, compares the column names and order to the agreed contract, and lets clean files proceed. Files with renamed, missing, reordered, or extra columns are moved to a `quarantine/` prefix so the loader never ingests a misaligned file, and the owner is notified to fix the export.
When to use it
Use it for partner or vendor CSV feeds where a column rename or reordering silently shifts every value into the wrong field. Quarantine-on-drift turns a data-corruption incident into a routine bounced file.
How it works
- 1An S3 object-created event in the landing bucket triggers the flow.
- 2Read the header line of the new CSV from S3.
- 3Compare header names and order to the stored column contract.
- 4Branch: matches -> leave the file for normal loading; drift -> continue to quarantine.
- 5Move the offending object to the quarantine prefix in S3.
- 6Notify the source owner in Slack with the expected vs received headers.
Set it up
What you configure once, before turning it on.
- 1Connect AWS S3Buckets, objects, signed URLs.
- 2Connect SlackChannels, DMs, threads, mentions.
- 3Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 4Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 5Test, 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.