How I Detect Website Failures 60 Seconds Before They Happen (Without Heavy ML)

Most monitoring tools answer one question: “Is it up?” I wanted to answer a different one: “Is it about to go down?” The Problem with Traditional Uptime Checks Downtime rarely happens instantly. In real-world systems, failure usually looks like this: T-5 minutes → response time slowly climbs (200ms → 400ms) T-2 minutes → latency spikes, occasional timeouts T-1 minute → error rate increases sharply T-0 → service crash Traditional monitoring only checks availability. It completely ignores degradation patterns. The Core Idea: Trend + Volatility > Status Instead of checking: isAlive = true / false I started tracking: Response time trend Slope direction Variance (volatility) Consecutive instability signals Because instability is usually visible before failure. The Lightweight Prediction Model No heavy ML. No TensorFlow. No GPU. Just math. 1️⃣ Exponential Moving Average (EMA) EMA smooths out noise while preserving trend. A single spike doesn’t trigger an alert. But a gradual climb does. 2️⃣