Day 17 – Building SaaS-Grade Analytics for My AI Phishing Defense Platform

Today I focused entirely on backend robustness. Instead of jumping to UI, I strengthened the analytics layer. What I Added 1️⃣ API Usage Monitoring Status codes Request latency (ms) Per-API-key tracking Error rate calculation 2️⃣ Risk Intelligence Metrics High / Medium / Low distribution Risk percentage breakdown 7-day usage trends Average risk score over time 3️⃣ Performance Metrics Average latency Error rate (%) Per-plan breakdown Real Bug I Faced I hit this error: sqlite3.OperationalError: no such column: analyzer_apiusage.latency_ms The model was updated, but the database schema wasn’t. Classic migration issue. The fix: Run makemigrations Run migrate Ensure correct module imports in models/init.py Lesson: Your ORM and your DB schema must always stay aligned. Why This Matters Before building UI, backend must be stable. Now the system: Tracks performance Measures abuse Prepares for production Supports SaaS analytics dashboards Next step: Backend hardening before frontend. Security is