DATA OPS

Weekly Axiom Top-Talker Cleanup Report to Notion

Every Monday it ranks the highest-volume Axiom services and log fields for the past week, estimates each one's ingest cost.

CategoryData Ops
Enginesim
Difficultyintermediate
Triggerschedule
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWeekly Monday schedule
  • ActionQuery Axiom per-service weekly ingestAxiom
  • ActionDrill into top services for noisy fieldsAxiom
  • LogicEstimate cost and rank by savings
  • ActionPublish ranked report to NotionNotionNotion
  • OutputPost weekly digest to SlackSlack

What it does

Turns a week of Axiom ingest into a prioritized cleanup backlog. It finds the top-talking services and the specific fields or messages inflating their volume, converts bytes to estimated dollars, and writes a ranked report so the team always knows the single highest-ROI logging change to make next.

When to use it

Use it for a recurring cost-hygiene ritual rather than one-off firefighting. It is the standing input to a weekly observability or platform review where you decide which noisy logs to drop or sample down.

How it works

  1. 1A weekly schedule runs early Monday.
  2. 2It queries Axiom for per-service ingest bytes over the trailing seven days.
  3. 3For the top services it runs a drill-down query to attribute volume to specific fields or log messages.
  4. 4A logic step converts bytes to estimated cost and ranks all candidates by savings potential.
  5. 5It writes or updates a Notion page with the ranked table, week-over-week change, and a suggested action per row.
  6. 6It posts a Slack digest linking the Notion report and naming the top three savings opportunities.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect AxiomLog streams, queries, dashboards.
  2. 2
    Connect NotionPages, databases, comments.
  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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