reliability-engineering

🛠️ Document systems that commit to irreversible decisions and explore their behaviors under immense scale and pressure in technical archives.

Production-grade assurance framework for safe, human-centered AI: evaluation, human calibration, adaptive routing, resilience, and release gates.

IAES — Industrial Asset Event Standard. A vendor-neutral event specification for industrial asset measurements, diagnoses, and maintenance intents.

Standard-library research laboratory for deterministic state, evidence, reliability boundaries, agent action integrity, reproducible ledgers, and edge-native execution.

Yusef Syed — University of Toronto student. Projects, apps, AI evaluation experiments, and open-source contributions.

Break AWS safely before reality does: enterprise-grade FIS orchestration, GovCloud guardrails, rollback, and audit-ready evidence in one Python file.

Personal portfolio showcasing my work in platform engineering, cloud infrastructure, reliability, Kubernetes, GCP, Terraform, observability, and distributed systems.

GitHub profile README for Patrick Araujo, Backend Software Engineer focused on AI systems, automation, API integrations, and internal platforms.

Reproducible benchmark harness for MoFlux admission control, with deterministic paired seed sweeps measuring latency, goodput, overload protection, token accounting, and policy trade-offs across Tyr and Latchflo.

Hands on implementations of real world distributed systems with runnable code, load tests, benchmarks, failure testing and production inspired architecture.

A terraform provider for Concourse

AI platform reference architecture for LLM serving on Kubernetes, with reliability, observability, failure testing, and evidence-bound engineering claims.

Homebrew tap for internal GDS command-line tools

🚀 This repository serves as a centralized collection of Helm charts for deploying and managing Kubernetes applications. 🎯

Production AI inference infrastructure platform for reliable LLM serving, provider routing, resilience, rate limiting, observability, and scalable API integration.

Terraform provider for Nobl9

Replay and regression infrastructure for AI agents. Capture, seal, replay and turn recorded executions into reproducible regression tests.

Turn your AI into a penetration tester with a security MCP server for offensive testing and attack simulation