Optimizing High-Frequency Polling Architectures

> Introduction

When monitoring critical infrastructure, every millisecond counts. In this log, we detail our transition from centralized polling to a distributed edge-based architecture.

- The Latency Problem

Our initial architecture relied on a single region to dispatch health checks. This introduced significant latency for global endpoints.

// Legacy polling implementation
async function checkHealth(url: string) {
  const start = Date.now();
  await fetch(url);
  return Date.now() - start;
}

- The Edge Solution

By moving the execution logic to the edge, we achieved:

1. Lower TTM (Time To Monitor)
2. Reduced false positives
3. Better geographical coverage

> Implementation Details

We utilized a distributed queue system with worker nodes deployed across 15 regions worldwide. Each node maintains a local cache of monitoring targets and executes health checks independently.

- Architecture Overview

The new system consists of three main components:

1. Edge Workers - Deployed to CDN edge locations
2. Central Coordinator - Manages monitoring schedules
3. Data Pipeline - Aggregates and processes results

- Performance Improvements

After migrating to the edge architecture, we observed:

• 40% reduction in average latency
• 60% fewer false positive alerts
• 99.99% uptime across all regions

> Lessons Learned

The migration taught us valuable lessons about distributed systems, caching strategies, and the importance of proper monitoring of monitoring systems.