Getting Git Right @ Git Merge 2018
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The document discusses best practices for using Git in the context of continuous integration and delivery, including branching strategies and repository structuring. It highlights the author's experience in helping companies adopt Git and emphasizes the importance of maintaining a single source repository and automating builds. Key concepts such as trunk-based development and the challenges of scaling continuous delivery pipelines are also explored.
Getting Git Right @ Git Merge 2018
- 1. Getting Git Right Git Merge 2018 Andrey Devyatkin
- 3. Andrey Devyatkin Independent consultant Continuous Delivery specialist and coach Whatever-I-can-get-my-hands-on automator Father, runner and traveler
- 4. #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
- 5. 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
- 6. 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
- 11. tested
- 12. tested tested You have no idea
- 14. We needed a branching strategy
- 15. A successful Git branching model http://nvie.com/posts/a-successful-git-branching-model/
- 18. Structuring repositories Submodules Git LFS Organisation as well as deliverable dictates the structure Many repos vs mono repo
- 20. or
- 21. What is the problem with scaling?
- 22. 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.
- 27. This how we used to scale CD pipelines before Where are we heading next?