Lesson 71: Runtime Guardrails & Security
Module 5: Enterprise MLOps and Productionizing VAIAs | Lesson 71 of 90
A. Highlights
What We Build
A multi-layer guardrail engine that intercepts LLM inputs and outputs before they reach users or downstream systems
A regex + heuristic PII detector with automatic redaction and configurable sensitivity levels
A topic restriction validator using Gemini-powered semantic judgment — no separate embedding model required
A real-time violation dashboard with per-guardrail breach counters, audit trails, and L70-wired Slack alerts on critical violations
A watchdog daemon that monitors guardrail pass-rates and auto-escalates to L70’s incident pipeline when policy adherence degrades
Connection to L70 (Alerting & Incident Response) L70 built a Prometheus + Slack alerting stack that fires when MLOps metrics cross thresholds. L71 plugs directly into that pipeline: guardrail violations become first-class metrics, and any guardrail breach-rate spike triggers the same Slack webhook and incident protocol you wired in L70 — no new alerting infrastructure needed.
Enables L72 (Cost Optimization) The guardrail engine exposes a
complexity_scoreon every validated request — a byproduct of the topic-check LLM call. L72 will consume this score to route simple, low-risk queries to a local SLM and complex, high-risk ones to a cloud GFM, giving you both safety and cost control simultaneously.
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