DATA OPS

Schema-Drift Remediation Agent: Quarantine, Propose Rollback, Brief Teams

On a breaking Snowflake column change, an agent quarantines the affected downstream sync, investigates root cause from the warehouse audit history.

CategoryData Ops
Enginepaperclip
Difficultyadvanced
Triggerevent
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerBreaking-change alert received
  • ActionConfirm change + actor from Snowflake historySnowflakeSnowflake
  • LogicQuarantine affected sync; reason over diff
  • ActionOpen PR with rollback/migration SQLGitHubGitHub
  • OutputBrief stakeholders in Microsoft TeamsMicrosoft Teams

What it does

Goes beyond alerting: an agent owns the response to a confirmed breaking schema change. It pauses the at-risk downstream sync to stop bad data from propagating, reconstructs what changed and who ran it, drafts a remediation (rollback DDL or a forward migration), opens a pull request, and posts a plain-English briefing for the team.

When to use it

When your data team is small and a breaking schema change demands containment plus a fix proposal, not just a notification. Use it where the cost of letting drift flow downstream is high and you want a first-draft remediation waiting for a human to approve.

How it works

  1. 1A breaking-change alert (from a detector or webhook) triggers the agent.
  2. 2The agent queries Snowflake history to confirm the change and identify the actor and timestamp.
  3. 3It pauses or flags the affected downstream sync to quarantine the blast radius.
  4. 4It reasons over the diff and drafts rollback or forward-migration SQL.
  5. 5It opens a GitHub PR containing the proposed fix and rationale.
  6. 6It posts a stakeholder briefing to Microsoft Teams summarizing impact, containment, and the proposed remediation awaiting review.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect SnowflakeWarehouses, queries, shares.
  2. 2
    Connect GitHubRepos, issues, pull requests, actions.
  3. 3
    Connect Microsoft TeamsChannels, chats, files.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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