IT OPS

Axiom Runaway-Emitter Agent Investigator with Sampling Proposal

An agent investigates an Axiom cost spike end to end — pinpointing the noisy service, sampling its log lines to find the repeating pattern.

CategoryIT Ops
Enginepaperclip
Difficultyadvanced
Triggerwebhook
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerCost-monitor webhook opens investigationHTTP webhook
  • ActionAgent ranks Axiom services, isolates emitterAxiom
  • ActionAgent samples + clusters offending log linesAxiom
  • ActionAgent opens scoped GitLab sampling-rule MRGitLabGitLab
  • OutputPost root-cause summary + MR to SlackSlack

What it does

Runs the full investigation a senior on-call would do. An agent queries Axiom to find which service spiked, samples that service's actual log lines to identify the dominant repeating message or log-loop, reasons about root cause, and produces both a human-readable Slack writeup and a concrete GitLab sampling-rule proposal scoped to the offending pattern.

When to use it

Use it when a raw "service X is noisy" alert isn't enough and you want the *why* — the specific log statement driving cost — plus a targeted fix that won't blind you to the logs that actually matter.

How it works

  1. 1A webhook from the cost monitor opens the investigation with the spike window.
  2. 2The agent queries Axiom to rank services and isolate the top emitter.
  3. 3The agent samples that service's log lines and clusters them to find the dominant pattern.
  4. 4The agent drafts a targeted sampling rule and opens a GitLab MR scoped to that pattern.
  5. 5It posts a Slack summary with root cause, evidence, and the MR link for sign-off.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect AxiomLog streams, queries, dashboards.
  2. 2
    Connect GitLabRepos, MRs, pipelines, registry.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  4. 4
    Connect HTTP webhookTrigger any URL on agent actions.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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