DEVOPS

Axiom Budget Triage Agent

An agent investigates a projected Axiom overage end to end — diagnoses the noisy source, decides whether to auto-throttle via Cloudflare or escalate to a Linear ticket.

CategoryDevOps
Enginepaperclip
Difficultyadvanced
Triggerschedule
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerEvery 2 hours with current projection
  • ActionAgent investigates top Axiom sourcesAxiom
  • LogicAgent decides throttle vs. escalate
  • ActionThrottle source via Cloudflare samplingCloudflareCloudflare
  • ActionOr open Linear ticket for reviewLinearLinear
  • OutputPost rationale and action to SlackSlack

What it does

Instead of a fixed rule, this agent triages a projected Axiom overage like an engineer would. It investigates which source is driving spend, judges whether the spike is a safe-to-throttle nuisance (verbose debug logs, health-check chatter) or a real signal that needs human review, then either tightens Cloudflare sampling or files a Linear ticket — and explains why.

When to use it

Use it when overage causes are varied enough that a single deterministic rule misfires. The agent's judgment handles the gray-area cases: throttle the obviously noisy, escalate the ambiguous.

How it works

  1. 1A schedule fires every 2 hours and hands the agent the current Axiom projection.
  2. 2The agent queries Axiom to identify and characterize the top contributing sources.
  3. 3It reasons over whether each top source is safe to throttle or needs human eyes.
  4. 4Decision branch: auto-throttle the source via Cloudflare sampling, or open a Linear ticket for review.
  5. 5Execute the chosen action.
  6. 6Post a written rationale and the action taken to Slack.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect AxiomLog streams, queries, dashboards.
  2. 2
    Connect CloudflareWorkers, Pages, R2, KV — the edge stack.
  3. 3
    Connect LinearIssues, projects, cycles, triage.
  4. 4
    Connect SlackChannels, DMs, threads, mentions.
  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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