kernelci / kernelci/dashboard

Deliver scoped metrics reports from metrics rules

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notifications
Dominant language
Python
Stars
9
Forks
31
Avg merge
3d 19h
Merged PRs (30d)
16

Description

Goal

On the weekly metrics job, send scoped metrics reports per rule in backend/data/notifications/metrics/. Keep the global weekly community mail unchanged.

Depends on: #2114

(Can be implemented in parallel with subscription new-issues delivery; does not depend on that issue.)

Today vs after

Today After
Metrics report One global weekly mail (fixed To/Cc in cron) Same default, plus scoped reports per metrics rule

Community delivery (unchanged)

Default weekly send: To kernelci@lists.linux.dev, Cc kernelci-results@groups.io, Saturday cron, existing cache warm.

Subscription delivery

For each rule in metrics/, filter get_metrics_data() by rule trees, hardware, origins; render metrics_report.txt.j2 for period_days; send to rule recipients. One rule spanning multiple trees → one email.

Note: Tree scoping requires SQL joins (incidents/builds/checkouts); extend cache warm for configured scopes.

Acceptance criteria

  • Default config → single global weekly metrics mail unchanged
  • At least one metrics rule sends scoped report to its recipients only
  • Query/cache impact documented; warm covers subscribed scopes
  • docs/notifications.md updated

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start in backend/data/notifications/metrics/ and inspect the metrics rules and metrics_report.txt.j2 flow, then review docs/notifications.md and the existing weekly job behavior. Verify that the default global mail is unchanged, scoped reports reach only each rule's recipients, configured scopes are covered by cache warm-up, and the query/cache impact is documented.

Written by the indexing model from the issue text.

Assessment

Tech stack
python, sql
Domain
backend, databases, documentation
Issue type
Feature
Difficulty
4/5
Estimated time
3-5 days
Activity status
Active
Clarity
Mostly clear
Newbie friendliness
64/100

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