I'm a distributed cloud infrastructure engineer working across the cloud-native stack. My focus is the infrastructure that keeps modern platforms secure and reliable — secure edge architecture, global traffic routing, and cloud-native platform modernization — and I spend my open-source time upstream, in the CNCF projects that so much of the industry depends on.
- Secure edge & supply chain — signing, policy enforcement, and workload identity
- Traffic routing & networking — service mesh, ingress, and cross-cluster connectivity
- Platform modernization — observability, GitOps, and distributed app runtimes on Kubernetes
I work upstream in CNCF and cloud-native projects, favoring small, correct, well-scoped changes that maintainers can merge with confidence. My live contribution history is right here on GitHub — and, for CNCF projects, in CNCF DevStats.
- contribpolicy: find a repository's rules for AI-assisted contributions (CONTRIBUTING, AGENTS.md, linked AI policies, org-level policies such as Kubernetes') and lint a PR against them before you push. Python, deterministic, no API key.
- ai-contribution-check: the maintainer side. A GitHub Action that checks incoming PRs against your project's AI contribution policy (disclosure,
Assisted-by/ co-author trailers, DCO, signed commits). - radius-recipe-test:
rrtruns the Radius resource-types-contrib recipe tests on a local kind cluster the way CI does, with readiness waits and verified cleanup.
Notes from the trenches, as gists: gh can't reach api.github.com on macOS · Radius recipe tests locally · reclaiming disk on a macOS build box · pre-push AI-policy check
Go · Kubernetes · CNCF ecosystem · distributed systems · eBPF · CI/CD