Build-time monitoring across lecture repos, with published benchmarks

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#186 0 comentarios 0 reacciones 0 asignados Ver en GitHub

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Evaluación

Dificultad
4/5
Tiempo estimado
3-5 días
Aptitud para principiantes
45/100
Tipo de issue
Nueva funcionalidad
Claridad
Bastante claro
Estado de actividad
Activo
Stack tecnológico
github-actions, shell
Área
ci-cd, observability, performance

Línea de trabajo

Review the repository's existing GitHub Actions workflows to understand the build process. Examine issue #30 for the environment manifest structure and #92 for baseline timings. Determine where to inject timing collection (e.g., using time commands or Action steps) and where to store the data (e.g., as an artifact or in a database). A proof of concept in one lecture repo is the first step.

Escrito por el modelo de indexación a partir del texto del issue.

Descripción

infrastructure

Why

Nothing records how long lecture builds take over time. Regressions surface only when someone happens to notice them. The measured baselines in #92 were collected by hand from individual runs. The idea was recorded in docs/FUTURE-DEVELOPMENT.md, which #178 removed (build monitoring, performance benchmarks).

Proposal

  • Record timings for setup, build and the whole job, per repository and per runner type (container, standard runner, RunsOn AMI).
  • Detect regressions through the job summaries.
  • Publish comparisons: a periodic report or dashboard comparing runner types and tracking each repo over time.

Related

  • #30 covers the publish-time environment manifest: what a build ran with. This issue covers how long it took. Both could share a data store.
  • #92 would use these numbers to confirm its expected savings.

Checklist

  • Decide where timings are collected: job summaries, the #30 manifest, or a separate artifact
  • Decide where they are stored and reported
  • Pick the first repos to instrument
Lenguaje dominante
Shell
Estrellas
0
Forks
1
Merge medio
18 h 51 min
PR fusionados (30 d)
58

Preparar el entorno

Primeros pasos

  1. Lee el issue completo y luego la guía de contribución del proyecto.
  2. Comenta en el issue que vas a ocuparte — evita que dos personas hagan lo mismo.
  3. Haz un fork del repositorio y trabaja en una rama.
  4. Abre un pull request que haga referencia al número del issue.

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