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Things I've built

Production-grade ML infrastructure projects — each one a real system running on real hardware, not a tutorial clone. Built to demonstrate SRE discipline applied to machine learning.

4 projects
4 in progress
0 live
Projects
🏗️ In progress
MLOps Homelab Platform
Production-grade MLOps stack on Kubernetes — 16 GB homelab, 11 phases, real security constraints. GitOps-first, observable by default.
k3sFluxCDMLflowArgo
🔄 In progress
Self-Healing ML Pipelines
Event-driven retraining loop — drift alert triggers Argo Events, quality gates control promotion. An SRE runbook that runs itself.
Argo EventsEvidentlyPrometheus
🔒 In progress
Zero-Trust ML Infrastructure
OPA/Gatekeeper policies, Vault-backed secrets, default-deny NetworkPolicies, and a CIS Kubernetes Benchmark self-assessment log.
OPAVaultkube-bench
📡 In progress
ML Observability Stack
Custom Prometheus metrics from inference services, Grafana dashboards for model drift, and Evidently reports on schedule.
EvidentlyGrafanaFluent Bit