The merge was clean. Your branch was ready. But something broke when it hit production—access denied from AWS S3.
When Git rebase meets AWS S3 read-only roles, precision matters. Rebasing rewrites commit history. This can alter who touches what data and when. In environments where S3 is locked down by IAM read-only roles, even small shifts in commit provenance can cause permission mismatches that halt your deployment pipeline.
AWS S3 read-only roles grant strict access: fetch objects, list buckets, nothing more. They block writes, deletes, and metadata updates. This prevents destructive changes but also means tools depending on write access will fail. If your build or deploy scripts try to update manifests or upload artifacts after a rebase, the IAM policy will stop them cold.
The fix starts with clarity in both Git and IAM. When performing git rebase on feature branches that interact with S3 resources, map exactly which commands will run after merge. Check CI/CD steps for any S3 write actions—aws s3 cp with --acl or aws s3 sync without --exclude flags can trigger policy violations.
Version control best practice: run git rebase --interactive to squash commits before merging to main. This cuts noise in history and keeps your branch clean. Access best practice: attach IAM policies with explicit s3:GetObject and s3:ListBucket only. Use bucket policies with restrictive principals to ensure your deployment service role remains read-only regardless of upstream merges.
When teams mix these disciplines—precise rebases, locked-down S3 roles—they get reproducible builds. The system becomes predictable. Every run consumes artifacts from S3 without risking modification. This is how you secure cloud storage while keeping Git history free of merge clutter.
Test it now. Hook up your repo, apply AWS S3 read-only roles, and run a controlled git rebase with hoop.dev. You’ll see it work end-to-end in minutes.