Put every asset in the right place
Large-file planning starts with a lifecycle question: does the asset need to follow source history, or does it need independent storage and delivery? An editable design file, a generated installer, and a customer upload may be equally large while requiring very different workflows. Classify them before choosing a storage tool.
Git Large File Storage records text pointers in Git while keeping the file contents in separate storage. It can suit binary assets whose versions need to remain associated with particular commits. Both the Git history and the corresponding large-file objects matter when checking out or recovering the project.
Establish which file patterns use LFS and commit the relevant attributes. Check that the remote, local tools, and build environment support the workflow. Our Git LFS guide walks through these choices and the difference between tracking future files and migrating existing history.
Object storage organizes data as separately addressable objects. Amazon's S3 introduction provides one concrete example: objects contain file data and metadata within buckets. Evaluate the chosen service's access controls, versioning options, lifecycle behavior, and retrieval requirements for the application you are building.
Consider this approach when uploads, media libraries, exports, or public downloads change independently of source commits. Keep the application code and storage references understandable, and define who can create, replace, or delete an object. A stable filename should not silently mean different content when reproducibility matters.
Keep a small manifest in source when it helps connect externally stored assets to a build. Record identifiers or checksums that your tooling can verify, while keeping real access credentials outside the committed manifest.
Reproduce a checkout and build in a fresh environment. Confirm that required assets arrive as usable files, not unresolved references. Test the credentials used by automation, including the case where an asset cannot be fetched. The failure should explain what is missing rather than leaving a broken page or an ambiguous build.
For assets delivered to browsers, check file types, caching, filenames, and access behavior. The Nginx and CDN deployment guide connects storage decisions with delivery. Keep private assets out of an intentionally public publishing path.
Define which historical versions must remain available and how they will be recovered. Coordinate cleanup with releases that still reference the assets. A storage-saving change can break an older checkout if it removes an object that checkout needs. Include separate asset storage in the project recovery plan, and rehearse restoration with a representative build.
GitFile answers
Common questions about large files.
No. Adding tracking rules does not itself migrate existing history. Treat any history migration as a separate task, coordinate it with collaborators, and verify the new remote and fresh checkouts before relying on the result.
Its purpose is to connect large-file versions with Git workflows. Evaluate end-user download delivery separately, including access, caching, availability, and usage limits. A file's development storage location does not automatically make it the right distribution endpoint.
Continue reading
Large files need a storage decision before they need a Git command. Learn which assets belong in ordinary Git, which fit Git LFS, and which should stay in artifact storage or application backups.
Understand how a Git release reaches visitors through Nginx and a CDN. Set explicit routing and cache policies, keep private source outside the web root, and verify changes at the public edge.
A ZIP, a clone, and a working backup preserve different things. Learn how to protect repository history, recover large-file objects, retain application state, and rehearse restoration without depending on the original host.