How do you implement the Cache-Aside pattern and Cache Invalidation strategies?

Short answer

The server checks the Cache first and returns the data if present; otherwise it fetches the data from the database, caches it with a time-to-live (TTL), and invalidates it when the data changes.

Explanation

With Cache-Aside (Lazy Loading), the Node.js application directly controls reads and writes to the Cache, often Redis. To avoid serving stale data, set a considered TTL and immediately invalidate the key on updates or deletes, or use strategies such as Write-Through for critical systems.

Code example

const cached = await redis.get(key);
if (cached) return JSON.parse(cached);
const data = await db.fetch(id);
await redis.set(key, JSON.stringify(data), "EX", 300);
return data;

Common mistakes

• Caching objects without a TTL, causing memory growth and stale data to be served indefinitely.

Follow-up questions

• How do you configure --max-old-space-size, and when should you change V8 Garbage Collector options?

Sources

• Microsoft Azure Architecture Center — Cache-Aside pattern