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Kubernetes Analysis
A source code analysis of Kubernetes organization on GitHub
KubeCon US
December 2018
Releases Over time
2
Very consistent release schedule for the past 3 years
Number of files / LoC over time
3
Stabilizing at > 1.75 Millions Line of Code, just under 8K files
Public APIs
4
API endpoints stabilizing at 16K
Drop between versions could mean backward compatibility issues
Number of commits per month
5
Commit velocity slowing down for the core Kubernetes project as
innovation comes from satellite projects in external GitHub Organizations
github.com/kubernetes
Top repositories / number of commits
6
Total number of contributions to the core Kubernetes project is slowing
down in 2018 which highlights the project maturity
github.com/kubernetes
Number of commits per month
7
Growth rate of Contributions to SIGs and Incubator projects also seem to be
slowing down
github.com/kubernetes-sigs
github.com/kubernetes-incubator
Top repositories / number of commits
8
Top contributions from the community directed to container runtimes, HPC
/ ML workloads, cluster federation and AWS ELB ingress controller
github.com/kubernetes-sigs
github.com/kubernetes-incubator
Number of files / LoC over time
9
The projects under kubernetes-sigs and kubernetes-incubator are
far less stable as the # of files and lines varies greatly over time.
github.com/kubernetes-sigs
github.com/kubernetes-incubator
Contributors by number of commits
10
Number of contributions per email Most common emails (size ~ log of #)
Organizations by number of commits
11
Number of contributions per email domain Most common email domains (size ~ log of #)
Number of languages over time
12
High and fluctuating number of languages shows that the community is ok
with “using the right tool for the right job”
13
# of LoC for top 7 programing languages
Go is by far the
dominant language
followed by Python,
YAML and Markdown.
14
Popularity of languages over time
Languages such as
C, Ruby,Gradle
and Lua have been
dropped while
some others like
Assembly, SQL
Java made a
comeback.
sourced.tech
blog.sourced.tech
github.com/src-d
Machine Learning for
Large Scale Code Analysis
Thank you!
Francesc Campoy
Email: francesc@sourced.tech
GitHub: @campoy

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Kubernetes analysis by source{d}

  • 1. Kubernetes Analysis A source code analysis of Kubernetes organization on GitHub KubeCon US December 2018
  • 2. Releases Over time 2 Very consistent release schedule for the past 3 years
  • 3. Number of files / LoC over time 3 Stabilizing at > 1.75 Millions Line of Code, just under 8K files
  • 4. Public APIs 4 API endpoints stabilizing at 16K Drop between versions could mean backward compatibility issues
  • 5. Number of commits per month 5 Commit velocity slowing down for the core Kubernetes project as innovation comes from satellite projects in external GitHub Organizations github.com/kubernetes
  • 6. Top repositories / number of commits 6 Total number of contributions to the core Kubernetes project is slowing down in 2018 which highlights the project maturity github.com/kubernetes
  • 7. Number of commits per month 7 Growth rate of Contributions to SIGs and Incubator projects also seem to be slowing down github.com/kubernetes-sigs github.com/kubernetes-incubator
  • 8. Top repositories / number of commits 8 Top contributions from the community directed to container runtimes, HPC / ML workloads, cluster federation and AWS ELB ingress controller github.com/kubernetes-sigs github.com/kubernetes-incubator
  • 9. Number of files / LoC over time 9 The projects under kubernetes-sigs and kubernetes-incubator are far less stable as the # of files and lines varies greatly over time. github.com/kubernetes-sigs github.com/kubernetes-incubator
  • 10. Contributors by number of commits 10 Number of contributions per email Most common emails (size ~ log of #)
  • 11. Organizations by number of commits 11 Number of contributions per email domain Most common email domains (size ~ log of #)
  • 12. Number of languages over time 12 High and fluctuating number of languages shows that the community is ok with “using the right tool for the right job”
  • 13. 13 # of LoC for top 7 programing languages Go is by far the dominant language followed by Python, YAML and Markdown.
  • 14. 14 Popularity of languages over time Languages such as C, Ruby,Gradle and Lua have been dropped while some others like Assembly, SQL Java made a comeback.
  • 15. sourced.tech blog.sourced.tech github.com/src-d Machine Learning for Large Scale Code Analysis Thank you! Francesc Campoy Email: francesc@sourced.tech GitHub: @campoy