DATA OPS

Reject Root-Cause Agent: Explain Failures and Draft a Replay Plan

On a reverse-ETL failure alert, an agent reads the quarantined reject rows from Snowflake, reasons about the root cause across patterns.

CategoryData Ops
Enginepaperclip
Difficultyadvanced
Triggerwebhook
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWebhook alert when reject threshold is crossedHTTP webhook
  • ActionQuery quarantined reject rows and errors from SnowflakeSnowflakeSnowflake
  • LogicCluster errors and reason about shared root cause
  • LogicDecide replay-now, fix-upstream, or escalate
  • OutputPost diagnosis and replay plan to Microsoft TeamsMicrosoft Teams

What it does

This is the analyst layer on top of your quarantine table. When a sync failure alert arrives, an agent pulls the rejected rows from Snowflake, looks for the common thread (one upstream join went null, a vendor changed an enum, a single malformed batch), and writes a human-readable root-cause summary with a concrete recommendation on whether to replay now, fix upstream first, or escalate.

When to use it

Use this when the raw quarantine data is there but nobody has time to read hundreds of error strings. The agent does the first-pass investigation and hands your team a decision, not a spreadsheet.

How it works

  1. 1A webhook alert fires when a reverse-ETL run crosses the reject threshold.
  2. 2The agent queries the matching quarantine rows and error messages from Snowflake.
  3. 3It clusters the errors and reasons about the most likely shared root cause.
  4. 4It drafts a diagnosis with a recommended action: safe-to-replay, fix-upstream, or escalate.
  5. 5It posts the summary and replay plan to the data team's Microsoft Teams channel for sign-off.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect HTTP webhookTrigger any URL on agent actions.
  2. 2
    Connect SnowflakeWarehouses, queries, shares.
  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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