This effort is born out of a collaboration between Bitergia and Toscalix Consulting. It would not have been possible without the active collaboration and input from AGL contributors, specially Jan-Simon Möller. The consulting team is:

• Igor Zubiaurre (Bitergia): data science and data engineering

• Luis Cañas (Bitergia): data engineering and data analysis

• Agustín Benito Bethencourt (Toscalix): data analysis and business intelligence

This team of consultants has been supported by software engineers, data engineers and staff from Bitergia.

To get in contact with the people involved in the study, you can attend to the CIAT open meetings or ping any of the named participants directly.

Check additional information about Bitergia. Read this blog post to learn more about Bitergia’s effort to bring Business Intelligence to software production at scale: Advanced Data Analytics for Delivery Performance Excellence.

Check additional information about Toscalix Consulting. Read about how Agustín is collaborating with Bitergia in bringing Business Intelligence to the production of software at scale: Introduction to Delivery Performance Analytics.

• AGL Content

  • AGL website

  • AGL documentation

    • AGL system overview

    • AGL layers: meta-agl, meta-agl-demo, meta-agl-devel,

    • AGL supported hardware

    • AGL components

    • Available demo images

  • AGL wiki

    • Release notes

    • CIAT group. Minutes of Meetings.

• AGL delivery tools

  • Gerrit. Working at AGL with Gerrit. Recommended practices at AGL. General guidelines.

  • Jenkins at AGL

  • Testing at AGL

    • LAVA at AGL

  • Bugs at Jira

• AGL channels

  • Meetings: AGL meetings calendar

    • Find the authors of this study in the CIAT Meeting (every other Wednesday at 13:00 UTC)

  • AGL mailing list

  • AGL at Discord

• AGL events

• AGL Schedule and Milestones

• AGL's delivery process performance analysis

• Contribution checklist

• The Yocto Project releases

References related with the community section

• The Contributor’s Behavior Metric

References related with code review process:

• Blog post of the series Metric of the Month By Bitergia

The process followed the the part of the study referred to deliver process performance is a simplification of the one described in these articles:

• Improve your software product delivery process performance using metrics (I)

• Improve your software product delivery process performance using metrics (II)

• This slide deck (in English) summarises these two articles.

The above references are simplifications, evolution or simply copies of processes and content published by others. These references has been essential for those involved in the study:

• Title: Measuring Continuous Delivery

  • Authors: Steve Smith

  • Publisher: Leanpub. 2020

• Title: Accelerate. The Science of Lean Software and DevOps: Building and Scaling High Performing Technology Organizations

  • Authors: Nicole Forsgren, Jez Humble and Gene Kim

  • Publisher: IT Revolution Press. 2018

• Title: Continuous Delivery

  • Author: Jez Humble and David Farley

  • Publisher: Addison Wesley: 2010

• Title: The Principles of Product Development Flow: Second Generation Lean Product Development.

  • Authors: Donald G. Reinerstsen.

  • Publisher: Celebritas 2009

• AGL AMM 2025 Summer talk, by Luis Cañas, summarising some aspects of this study

• Linaro Connect, May´24. Madrid, ES. “Improving Delivery Process Performance for SW-Defined Products Helped by Data Analytics”. Slides. Video

• Metrics

  • CHAOSS Project. CHAOSS metrics

  • Bitergia metrics

  • DORA metrics

These are terms that are referred in this study that should be clarified:

• UCB: Unified Code Base, the main AGL output, which has meta-agl repository as main source

• jjb: Jenkins Job Build

• CIB: continuous integration build

• YCL: Yocto Continuous Loop

• ci-platform-: continuous integration platform

• sstate: shared state. sstate is a cache mechanism used by the Yocto Project to reuse previously built artifacts, so that builds don’t have to start from scratch every time.

• pre-fetch-mirror-: scripted task used in AGL’s Jenkins setup top pre-download source code from mirrors (downloads of source tarballs or Git repos), pre-dowload sstate artifacts (shared-state cache) and warm up the build environment to reduce build time and network load during the actual build.#

• IQR: InterQuartile Range