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dependabot[bot] 8fc36782c6 Bump gitpython from 3.1.30 to 3.1.34 in /scripts/metrics 
Bumps [gitpython](https://github.com/gitpython-developers/GitPython) from 3.1.30 to 3.1.34.
- [Release notes](https://github.com/gitpython-developers/GitPython/releases)
- [Changelog](https://github.com/gitpython-developers/GitPython/blob/main/CHANGES)
- [Commits](https://github.com/gitpython-developers/GitPython/compare/3.1.30...3.1.34)

---
updated-dependencies:
- dependency-name: gitpython
  dependency-type: direct:production
...

Signed-off-by: dependabot[bot] <support@github.com>
2023-09-07 09:35:01 +02:00
..
SQL_queries added more queries 2021-12-14 11:40:34 +01:00
.gitignore script to get statistics from git repo 2020-02-21 13:19:11 +01:00
analyze_jobs.ipynb rename master to main branch following LLVM 2020-12-10 09:29:24 +01:00
buildbot_monitoring.py use same db for all tables 2021-06-18 12:21:41 +02:00
buildbot_status_emails.py creating tmp dir as needed 2020-05-05 16:54:08 +02:00
buildbots.py fixed initialisation 2020-02-17 14:55:10 +01:00
buildkite_master_stats.py rename master to main branch following LLVM 2020-12-10 09:29:24 +01:00
connect_db.sh cron jobs for buildbot and phab monitoring 2021-05-20 21:44:19 +02:00
download_buildkite_builds_pg.sh invoke script 2023-09-04 18:21:09 +02:00
jenkins.py fixed report writing 2020-05-06 17:24:26 +02:00
load_buildkite.py update buildkite monitoring 2021-06-28 10:16:36 +02:00
Pipfile Cron job to load BK data to DB 2021-05-20 17:30:43 +02:00
Pipfile.lock Bump gitpython from 3.1.30 to 3.1.34 in /scripts/metrics 2023-09-07 09:35:01 +02:00
pull_phab_build_stats.py added more phabricator metrics 2020-08-13 13:14:54 +02:00
README.md rename master to main branch following LLVM 2020-12-10 09:29:24 +01:00
repo.py rename master to main branch following LLVM 2020-12-10 09:29:24 +01:00
repo_hist.py improved git metrics script (#295) 2021-04-27 16:42:38 +02:00
repo_hist_db.py repo_hist_db now using postgres DB 2021-05-11 10:09:51 +02:00
server_monitoring.py use same db for all tables 2021-06-18 12:21:41 +02:00

README.md

Metrics

To measure the impact and usefulness of the pre-merge checks, we want to collect a set of metrics. This doc will summarize the metrics and tools. All of the data shall be collected as time series, so that we can see changes over time.

  • Impact - The metrics we ultimately want to improve

    • Percentage of build-bot build on main failing. (Buildbot_percentage_failing)
    • Time to fix a broken main build: Time between start of failing builds until the build is fixed. (BuildBot_time_to_fix)
    • Percentage of Revisions on Phabricator where a broken build was fixed afterwards. This would indicate that a bug was found and fixed during the code review phase. (Premerge_fixes)
    • Number of reverts on main. This indicates that something was broken on main that slipped through the pre-merge tests or was submitted without any review. (Upstream_reverts)

  • Users and behavior - Interesting to see and useful to adapt our approach.

    • Percentage of commits to main that went through Phabricator.
    • Number of participants in pre-merge tests.
    • Percentage of Revisions with pre-merge tests executed
    • Number of 30-day active committers on main and Phabricator.

  • Builds - See how the infrastructure is doing.

    • Time between upload of diff until build results available.
    • Percentage of Revisions with successful/failed tests
    • Number of pre-merge builds/day.
    • Build queuing time.
    • Individual times for cmake, ninja all, ninja check-all per OS/architecture.
    • Result storage size.
    • Percentage of builds failing.

Requirements

  • Must:
    • Do not collect/store personal data.
  • Should:
    • Minimize the amount of additional tools/scripts we need to maintain.
    • Collect all metrics in a central location for easy evaluation (e.g. database, CSV files).
  • Nice to have:
    • As the data is from an open source project and available anyway, give public access to the metrics (numbers and charts).
    • Send out alerts/notifications.
    • Show live data in charts.

Data sources

This section will explain where we can get the data from.

  • build bot statistics

Solution

We need to find solutions for these parts:

  • Collect the data (regularly).
  • Store the time series somewhere.
  • Create & display charts.

Some ideas for this:

  • bunch of scripts:
    • Run a bunch of scripts manually to generate the metrics every now and then. Phabricator already has a database and most entries there have timestamps. So we could also reconstruct the history from that.
    • TODO: Figure out if we can collect the most important metrics this way. This requires that we can reconstruct historic values from the current logs/git/database/... entries.
  • Jenkins + CSV + Sheets:
    • collect data with jenkins
    • store numbers as CSV in this repo
    • Charts are created manually on Google Sheets
  • do it yourself:
    • Collect data with Jenkins jobs
    • Store the data on Prometheus
    • Visualize with Grafana
    • host all tools ourselves
  • Stackdriver on GCP:
    • TODO: figure out if we can get all the required data into Stackdriver
  • Jupyter notebooks:
    • TODO: figure out how that works