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Caching Strategy

To reduce database load and improve response times, we implement caching at multiple layers.

1. Application Cache (Redis)​

We use a wrapper service CacheService to handle GET/SET operations with standardized keys.

Usage​

We prefer the Get-Or-Set pattern:

const stats = await CacheService.remember(
  `stats:camera:${id}`, // Key
  60, // TTL (Seconds)
  async () => await StatsService.compute(id), // Computation (only runs if miss)
);

2. Invalidation​

When data changes (e.g., User updates profile), we must clear the stale cache. We use CacheInvalidationService which supports Wildcard Deletion (Scanning Redis keys).

// When a camera is updated
await CacheInvalidationService.clear(`stats:camera:${camera.id}:*`);

3. HTTP Caching​

For static assets or highly cacheable API responses, we attach ETag or Cache-Control headers via the metrics middleware.