AI AGENTS

Axiom Runaway-Ingest Auto-Sampling Guard

On a severe Axiom ingest spike, an agent confirms a true runaway logger, applies an emergency sampling rule to cap the bleeding.

CategoryAI Agents
Enginepaperclip
Difficultyadvanced
Triggerwebhook
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerAxiom severe ingest-rate webhookHTTP webhook
  • ActionConfirm offending dataset and rule out traffic surgeAxiom
  • LogicProceed only if runaway-logger pattern confirmed
  • ActionApply scoped emergency sampling rule via AxiomAxiom
  • OutputPage on-call with action and revert stepsPagerDutyPagerDuty

What it does

Acts as a fast guardrail against runaway loggers that can burn a month of budget in hours. On a severe spike the agent verifies the pattern is a genuine flood (not a legitimate traffic surge), applies a pre-scoped emergency sampling rule to the offending dataset to cap ingest, then pages on-call with a clear record of the action and the option to revert.

When to use it

Use it when a single bad deploy or log loop can rack up serious cost before a human notices. The automatic cap buys time; on-call stays in control via the page and can roll back immediately.

How it works

  1. 1An Axiom monitor webhook fires on a severe ingest-rate breach.
  2. 2The agent queries Axiom to confirm a single dataset/field is responsible and rules out a broad traffic surge.
  3. 3A logic gate proceeds only if the runaway-logger pattern is confirmed.
  4. 4The agent applies a scoped emergency sampling rule via the Axiom API to cap ingest.
  5. 5PagerDuty is triggered for on-call with the action taken, the evidence, and revert instructions.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect AxiomLog streams, queries, dashboards.
  2. 2
    Connect PagerDutyIncidents, on-call, escalations.
  3. 3
    Connect HTTP webhookTrigger any URL on agent actions.
  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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