FINANCE
Daily cloud-spend spike → deploy attribution → finance-eng Linear ticket
Each morning it scans yesterday's cloud cost telemetry for spend spikes, correlates the spike window against Axiom deploy and service logs to name the likely culprit.
How it runs
The automated pipeline, trigger to output.
- TriggerDaily schedule after cost export lands
- ActionRead yesterday's per-service cost rows from CUR export in S3AWS S3
- LogicFlag services exceeding 14-day median baseline threshold
- ActionQuery Axiom for deploys/traffic/errors in spike windowAxiom
- LogicRank likeliest deploy/service cause
- OutputOpen joint finance-eng Linear ticket with evidenceLinear
What it does
Every morning this workflow pulls the prior day's cost-and-usage data, flags any service whose spend jumped well above its own trailing baseline, then queries Axiom for deploys and traffic in the exact spike window to attribute the increase to a specific deploy or service. If it finds a credible cause, it files one Linear ticket owned jointly by finance and engineering.
When to use it
Use it when surprise cloud bills keep surfacing days late and nobody can say which deploy caused them. It turns "the bill is up again" into a dated, attributed, actionable ticket before the spend compounds across the billing period.
How it works
- 1A daily schedule fires after the cost export lands.
- 2It reads yesterday's per-service cost rows from the AWS CUR export in S3.
- 3A baseline check compares each service against its 14-day median and isolates spikes past the threshold.
- 4For each spike it queries Axiom logs in the spike window for deploys, request volume, and error bursts.
- 5It assembles an attribution summary ranking the likeliest cause.
- 6It opens a Linear ticket tagged finance + eng with the spend delta, suspect deploy, and log links.
Set it up
What you configure once, before turning it on.
- 1Connect AWS S3Buckets, objects, signed URLs.
- 2Connect AxiomLog streams, queries, dashboards.
- 3Connect LinearIssues, projects, cycles, triage.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Run it inside a business
This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.
Run this workflow in your colony.
14-day trial. No DevOps. No Sales call. Provisioned in under a minute.