DATA OPS

Post-ingestion freshness verification on pipeline webhook

On a pipeline-completion webhook, verifies the expected Snowflake tables actually advanced their load timestamps and row counts; if any did not move, it flags a silent-failure…

CategoryData Ops
Enginesim
Difficultyintermediate
Triggerwebhook
Steps4
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerPipeline-completion webhookHTTP webhook
  • ActionRead loaded_at + row_count for expected tablesSnowflakeSnowflake
  • LogicDetect tables that did not advance (silent failure)
  • OutputAlert owning team on silent failuresSlack

What it does

A pipeline can report success while silently writing zero rows or skipping a table. This workflow catches that: when your orchestrator fires its done webhook, it immediately checks that each expected table's load timestamp and row count actually advanced since the previous run, and raises a silent-failure alert when they didn't.

When to use it

Use it right after batch loads where green pipeline status is not enough proof, especially when downstream SLAs depend on the load truly landing data this cycle.

How it works

  1. 1An HTTP webhook from your orchestrator triggers the run with the batch's table list and prior watermark.
  2. 2A Snowflake query reads current `loaded_at` and `row_count` for each expected table.
  3. 3A logic step compares against the supplied watermark to detect tables that did not advance or whose row delta is zero.
  4. 4If everything advanced, the run records success and exits quietly.
  5. 5For any silent failures, a Slack alert tags the owning team with the offending tables and deltas.

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 SlackChannels, DMs, threads, mentions.
  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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