Published 10/2022MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 ChGenre: eLearning | Language: English | Duration: 15 lectures (1h) | Size: 197.3 MB
Learn how to deal with big files with Git.
Analyze and convert repositories with big files to small repository using Git LFS.
Work in a team using Git LFS.
Explore services that provide Git LFS support.
To learn about Git LFS it is recommended to have Git experience.
In this Git LFS Training course, you will learn everything you need to know about Git LFS (Git Large File Storage).
You will learn about
Git data model and the problem with big files. What is a DAG (Directed Acyclic Graph) and Git internal objects.
How a big file affects a Git repository when you work in a team.
How Git LFS internally works (filter and data storing).
Install Git LFS in your development computer (on different OS like Windows, Linux, MacOS, ...).
Configure a new repository to start using it (".gitattributes" file).
Analyze and convert an existing big repository.
Valuable tools like BFG Repo-Cleaner to work with Git repositories and understand what large objects are and how can we decrease the size of the repository.
Different Git LFS providers (cloud and on-prem) including a cost comparative table.
Collaboration when using Git LFS (including resolve a conflict, lock a file and exclude/include specific paths).
Alternatives to Git LFS (like git-annex, git-bigfiles, ...).
Because I know that consolidating knowledge is important for the student, I include a practical exercise, also a cheatsheet with all the commands that are frequently used with a detailed explanation, and a glossary with the most commonly used terms in Git LFS.
Highly interesting if you work with big files (like Unity projects) and operations in Git start to take longer than normal (in your daily workflow and also in D tools).
Developers who are constantly working with large files like textures, binaries, videos and want to know how to have version control.
Focused on DevOps eeers who work with Git on a daily basis and want to know how to optimize the build and release pipeline.
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Code:
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