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Performance Engineering for Large Git Repos

Large Git repositories can slow development and reduce productivity. This course will teach you how to measure repository performance, reduce local footprint with Sparse Checkout and Partial Clone, and maintain speed at scale.

Intermediate
1h 24m

Created by Zachary Bennett

Last Updated Jun 23, 2026

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  • Course

Performance Engineering for Large Git Repos

Large Git repositories can slow development and reduce productivity. This course will teach you how to measure repository performance, reduce local footprint with Sparse Checkout and Partial Clone, and maintain speed at scale.

Intermediate
1h 24m

Created by Zachary Bennett

Last Updated Jun 23, 2026

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What you'll learn

Large Git repositories can become difficult to manage, leading to slower workflows, increased storage costs, and reduced developer productivity. In this course, Performance Engineering for Large Git Repos, you’ll gain the ability to diagnose, tune, and sustain Git performance in massive enterprise codebases. First, you’ll explore how to measure repository bloat using git-sizer and git rev-list to identify oversized objects, deep histories, and structural bottlenecks. Next, you’ll discover how to implement Sparse Checkouts, Partial Clones, Scalar, and Git LFS to dramatically reduce local disk usage and network latency. Finally, you’ll learn how to configure background maintenance with git gc and git repack to sustain long-term repository health and assess your tooling’s readiness for the Git 3.0 reftable backend. When you’re finished with this course, you’ll have the skills and knowledge of Git performance engineering needed to keep large repositories fast, healthy, and ready for the future.

Performance Engineering for Large Git Repos
Intermediate
1h 24m
Table of contents

About the author
Zachary Bennett - Pluralsight course - Performance Engineering for Large Git Repos
Zachary Bennett
55 courses 4.4 author rating 260 ratings

Zach is currently a Senior Software Engineer at VMware where he uses tools such as Python, Docker, Node, and Angular along with various Machine Learning and Data Science techniques/principles. Prior to his current role, Zach worked on submarine software and has a passion for GIS programming along with open-source software.

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