AI AGENTS

Axiom log correlation for CDN cost root-cause

On a daily run, an agent queries Axiom request logs to find which route saw an abnormal jump in cache-miss volume, correlates it to the deploy or referrer that triggered it.

CategoryAI Agents
Enginepaperclip
Difficultyadvanced
Triggerschedule
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerDaily scheduled analysis
  • ActionQuery per-route cache-miss counts (Axiom APL)Axiom
  • LogicKeep routes above anomaly multiplier
  • ActionPull first-seen and top referrers per route (Axiom)Axiom
  • ActionRank drivers and draft cache rulesOpenAI
  • OutputPost ranked cost-driver report to SlackSlack

What it does

Uses your Axiom request logs as the source of truth to explain a CDN cost jump. It finds routes whose cache-miss count surged day-over-day, ties the surge to a specific deploy timestamp or top referrer, and proposes the cache change that would have absorbed it.

When to use it

When you ship logs to Axiom and want log-grounded attribution of a cost spike (which path, since when, driven by whom) rather than aggregate CDN counters that hide the cause.

How it works

  1. 1A scheduled trigger runs the daily analysis.
  2. 2The agent runs an Axiom APL query for per-route cache-miss counts and bytes over the last two days.
  3. 3A logic step keeps only routes whose miss volume rose beyond the anomaly multiplier.
  4. 4A follow-up Axiom query pulls the first-seen timestamp and top referrers for each flagged route to pin the trigger (a deploy, a scraper, a new embed).
  5. 5An OpenAI step ranks drivers by wasted bytes and drafts a cache rule per offender.
  6. 6The ranked report posts to Slack.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect AxiomLog streams, queries, dashboards.
  2. 2
    Connect OpenAIModels, embeddings, files.
  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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