Infrahub is a graph-based data management platform with built-in version control, CI workflows, peer review, and API access. It’s purpose-built to power reliable infrastructure automation at scale.
This week focused on optimizing database queries and improving reliability of artifact file serving. The team reduced unnecessary node lookups in profile operations, fixed checksum validation for artifact files, and improved error reporting when artifacts fail to load. Additionally, work progressed…
Get this in your inbox every Monday →A deterministic 0–100 hygiene score — README, license, CI, tests, docs, and freshness.
Who ships this repo — author concentration and the bus factor across the last 300 mainline commits.
How welcoming this repo is to contributors — issue throughput, close time, responsiveness, and good-first-issue count.
What this project is built on — dependency count by ecosystem, the license mix, and anything worth a legal look before you adopt it.
Whether this project's CI can be trusted — pass rate, run times, flaky runs, and which workflow is the weak link.
Grounded in infrahub's README, structure, and recent commits — answers won't invent code they haven't seen.
A Monday email with what shipped, in plain English — no account needed.
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fix(git): delete removed definitions after their dependents [IFC-2967] (#10822)
test(changelog): build the removed relationship's peer without random properties
A floor, not a guess: counts only commits whose author, co-author trailer, or message explicitly credits an AI tool (Claude, Copilot, Cursor, aider, Codex…). Based on 30 mainline commits. Unattributed AI code isn't counted here — the full audit estimates that separately.
