DATA OPS
Load-Job Failure to Freshness Correlator
Triggers on an ingestion-job failure event in Axiom, immediately checks which downstream Snowflake tables that job feeds.
How it runs
The automated pipeline, trigger to output.
- TriggerWebhook: Axiom load-job failure alertHTTP webhook
- ActionResolve downstream tables + SLA deadlinesSnowflake
- LogicEstimate time-to-breach per table
- LogicKeep tables within at-risk horizon
- OutputPost early-warning to SlackSlack
What it does
This flips the usual order: instead of waiting for a table to go stale and then tracing back, it reacts the instant a load job fails. On a job-failure event it resolves which tables that job populates, estimates each table's next SLA deadline, and posts an early warning naming the tables that will breach if the job is not rerun in time. It is preventive rather than reactive.
When to use it
Use it when your load jobs emit failure events and you would rather get ahead of a breach than discover it after the fact. It buys the on-call lead time to rerun or backfill before any dashboard goes stale.
How it works
- 1An Axiom alert webhook fires on a load-job failure.
- 2It looks up the affected downstream tables and their SLA deadlines in Snowflake.
- 3A logic step estimates time-to-breach for each table.
- 4It keeps tables whose deadline falls within the at-risk horizon.
- 5It posts an early-warning message to Slack listing tables and deadlines.
Set it up
What you configure once, before turning it on.
- 1Connect AxiomLog streams, queries, dashboards.
- 2Connect SnowflakeWarehouses, queries, shares.
- 3Connect SlackChannels, DMs, threads, mentions.
- 4Connect HTTP webhookTrigger any URL on agent actions.
- 5Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 6Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 7Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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