OTHER

Datadog untagged spend cleanup tickets

Finds Datadog cost that lacks a team or service tag, identifies the likely owner from related resources, and files Linear tickets so the spend gets properly attributed.

CategoryOther
Enginesim
Difficultyadvanced
Triggerschedule
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWeekly schedule
  • ActionPull untagged Datadog cost and resourcesDatadogDatadog
  • LogicInfer likely owner and rank by cost
  • LogicFilter out low-cost sources
  • ActionFile Linear cleanup ticketsLinearLinear
  • OutputPost weekly cleanup summary to SlackSlack

What it does

This workflow drives down your "unattributed" cost bucket. Weekly it surfaces Datadog spend with no `team` or `service` tag, infers the probable owner from co-located resources and host metadata, and files a Linear cleanup ticket per orphaned cost source so someone tags it. Over time the unattributed pool shrinks and showback gets accurate.

When to use it

Use it when a meaningful slice of your Datadog bill can't be charged back because resources are untagged, and you want a steady, tracked cleanup loop instead of a one-off tagging sprint.

How it works

  1. 1A weekly schedule triggers the audit.
  2. 2The Datadog action pulls cost and resources where the ownership tags are missing.
  3. 3A logic step groups orphaned spend by resource and infers a likely owning team from neighboring tagged resources, ranking by dollar impact.
  4. 4A logic filter drops sources below a cost threshold to avoid ticket noise.
  5. 5A Linear action files a cleanup ticket per significant source with the suggested owner and the cost at stake.
  6. 6The output step posts a weekly summary of opened tickets and total unattributed spend to Slack.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect DatadogMetrics, traces, log search.
  2. 2
    Connect LinearIssues, projects, cycles, triage.
  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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