https://github.com/asubedy/gsoc-2022

This repostory contains all my works that I did at Google Summer of Code 2022
https://github.com/asubedy/gsoc-2022

cncf dashboard gsoc-2022 jekyll project react

Last synced: about 1 month ago
JSON representation

This repostory contains all my works that I did at Google Summer of Code 2022

• Host: GitHub
• URL: https://github.com/asubedy/gsoc-2022
• Owner: asubedy
• Created: 2022-09-10T22:03:45.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2022-09-11T21:47:08.000Z (over 2 years ago)
• Last Synced: 2024-11-08T14:53:05.611Z (3 months ago)
• Topics: cncf, dashboard, gsoc-2022, jekyll, project, react
• Homepage:
• Size: 1.95 KB
• Stars: 1
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# Google Summer of Code 2022 - CNCF at Layer5

#  Project Title: CNCF Cluster: Performance Benchmarking 

A basic aim for this project was to build a benchmarking methodology for different Performance Test that are run on CNCF Cluster using Service Mesh Performance Action. So to achieve this aim, I built a dashboard where users can get a visusal representation of the the test data that are run on the CNCF Cluster. You can read more about the project on the GSoC site [here](https://summerofcode.withgoogle.com/programs/2022/projects/GRLPhiag)

## The final result of the project is situated at https://smp-spec.io/dashboard

## PR's for the project

  1. https://github.com/service-mesh-performance/service-mesh-performance/pull/309

  2. https://github.com/service-mesh-performance/service-mesh-performance/pull/310

  3. https://github.com/service-mesh-performance/service-mesh-performance/pull/315

  4. https://github.com/service-mesh-performance/service-mesh-performance/pull/316

  5. https://github.com/service-mesh-performance/service-mesh-performance/pull/317

  6. https://github.com/service-mesh-performance/service-mesh-performance/pull/324

  7. https://github.com/service-mesh-performance/service-mesh-performance/pull/326

  8. https://github.com/service-mesh-performance/service-mesh-performance/pull/334

  9. https://github.com/service-mesh-performance/service-mesh-performance/pull/342

  10. https://github.com/service-mesh-performance/service-mesh-performance/pull/346

  11. https://github.com/service-mesh-performance/service-mesh-performance/pull/347

  12. https://github.com/service-mesh-performance/service-mesh-performance/pull/352

  13. https://github.com/service-mesh-performance/service-mesh-performance/pull/353

## ScreenShots of the Dashboard:



              Fig: Landing Page of the dashboard. Shows all the performance profiles with all the test parameters 



                            Fig: List of all results that run periodically for a individual performance profile 



        

                                Fig: Graph of the individual test data

  



                         Fig: Test Specifications of the test for users to correcly asses the results and the environment the test is run

# Other Tasks:

Other than my project I got an oppurtunity to contribute on other codebase under Layer5 too. This was really helpful in expanding my knowledge base and I thoroughly enjoyed doing it. Here are some PRs listed below that shows my work during this period:

## Meshery Docs: Compatability Matrix

  1. https://github.com/meshery/meshery/pull/5419

  2. https://github.com/meshery/meshery/pull/5992

## Meshery

  1. https://github.com/meshery/meshery/pull/5670

  2. https://github.com/meshery/meshery/pull/5868

## Meshery.io Website (https://meshery.io)

  1. https://github.com/meshery/meshery.io/pull/736

  2. https://github.com/meshery/meshery.io/pull/744

  3. https://github.com/meshery/meshery.io/pull/756

  4. https://github.com/meshery/meshery.io/pull/765

## Contributions involving GitHub Actions:

  1. https://github.com/meshery/meshery-linkerd/pull/369

# Summary

It gives me immense happiness to say that I got this wonderful oppurtunity to work as GSoC CNCF mentee on the Service Mesh Performance project. I have learnt so much during this period of internship. I would like to thank my mentor [Lee Calcote](https://github.com/leecalcote) who guided me and helped me overcome any hump I might have during the entire period of the GSoC. I would also like to thank all the community members for constantly giving me feedbacks and suggesting ways to improve myself and the project I was working on. As the time for this GSoC has come to an end, but I would never hesitate to say that I would still be contributing to this project and fine tune my work to make it more robust.