Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Getting Git Right @ Git Merge 2018

135 views

Published on

Presentation at Git Merge 2018

Common pitfalls that organisations fall into when using and experimenting with Git

Published in: Technology
  • Be the first to comment

Getting Git Right @ Git Merge 2018

  1. 1. Getting Git Right Git Merge 2018 Andrey Devyatkin
  2. 2. Andrey Devyatkin Independent consultant Continuous Delivery specialist and coach Whatever-I-can-get-my-hands-on automator Father, runner and traveler
  3. 3. #WEHAVEAPLAN How Git changed what we mean by Continuous Integration Branching strategies - dos and don'ts Structuring repositories - dos and don'ts Git and Scaling Continuous Delivery
  4. 4. To put it into context First encounter in 2008-2009 Moved to Stockholm in 2011 to help with a massive migration to Git Consulted many more other migrations within Ericsson Left Ericsson and went into consulting - helped even more companies to adopt Git Trained 300+ people to use Git
  5. 5. Continuous Integration by Martin Fowler Processes Maintain a Single Source Repository Everyone Commits To the Mainline Every Day Every Commit Should Build the Mainline on an Integration Machine Build automation Automate the Build Keep the Build Fast Make Your Build Self-Testing Fix Broken Builds Immediately Make it Easy for Anyone to Get the Latest Executable
 https://martinfowler.com/articles/continuousIntegration.html
  6. 6. tested
  7. 7. tested tested You have no idea
  8. 8. We needed a branching strategy
  9. 9. A successful Git branching model http://nvie.com/posts/a-successful-git-branching-model/
  10. 10. Cactus branching model https://barro.github.io/2016/02/a-succesful-git-branching-model-considered- harmful/
  11. 11. Trunk based development https://trunkbaseddevelopment.com
  12. 12. Structuring repositories Submodules Git LFS Organisation as well as deliverable dictates the structure Many repos vs mono repo
  13. 13. Continuous Delivery
  14. 14. or
  15. 15. What is the problem with scaling?
  16. 16. Little’s Law The long-term average number of customers in a stable system L is equal to the long-term average effective arrival rate, λ, multiplied by the average time a customer spends in the system, W; or expressed algebraically: L = λW.
  17. 17. Multiple product lines
  18. 18. This how we used to scale CD pipelines before Where are we heading next?
  19. 19. Thanks! @andrey9kin andrey9kin@a59.company github.com/andrey9kin

×