How do caching layers improve system design?
When interviewers ask “How would you make this system faster?”, the best one-word answer is: cache. Caching is the simplest and most effective way to boost performance, reduce cost, and handle high traffic — all at once.
1️⃣ What is caching and why it matters
Caching stores frequently accessed data in faster storage (memory or edge) so that future requests can be served instantly. Instead of hitting the database on every request, you retrieve data from RAM, SSD, or a CDN node — reducing latency from milliseconds to microseconds.
👉 Example: Instead of querying SELECT * FROM users WHERE id=123 each time, store the user record in Redis or Memcached.
🔗 Learn the basics: Caching System Design Interview
2️⃣ Different layers of caching in a modern system
| Cache Layer | Description | Example Use |
|---|---|---|
| Browser Cache | Stores static resources locally | CSS, JS, Images |
| CDN (Edge Cache) | Delivers content from the nearest node | Cloudflare, Akamai |
| Service Cache | Stores API responses in memory | Redis, Memcached |
| Database Cache | Keeps query results near DB | MySQL Query Cache |
| Application Cache | Stores computed data or sessions | User sessions, JWT tokens |
Each layer removes load from deeper layers and drastically reduces latency.
3️⃣ Key caching strategies to mention in interviews
- Cache Aside (Lazy Loading): Application reads from cache; if not found, fetches from DB and stores it. (most common)
- Write-Through: Writes go to both cache and database simultaneously.
- Write-Back: Writes go first to cache and update DB later asynchronously.
- Read-Through: Cache retrieves data from DB on a miss automatically.
Each choice involves trade-offs between freshness, latency, and complexity.
🔗 Deep dive: Cache Invalidation Strategies
4️⃣ How caching supports scalability
Caching improves scalability by:
- Reducing database QPS by 80-90%.
- Allowing app servers to serve thousands of concurrent users.
- Shielding slow services during spikes.
- Acting as a temporary buffer during outages.
🔗 Read: How to Handle High Traffic in a System Design Interview
5️⃣ What to mention about cache invalidation
This is where most candidates fail. Say clearly:
“I’d use TTLs or versioned cache keys to prevent stale data.”
And always mention the golden rule:
“There are only two hard problems in computer science — cache invalidation and naming things.”
That line always earns a smile from interviewers.
💡 Interview Tip
If asked “How would you reduce database load?”, start with:
“I’d add a caching layer in front of the database using Redis or Memcached, with cache-aside strategy and TTLs for freshness.”
This concise, flow-based explanation wins points for clarity and senior-level thinking.
🎓 Learn More
To master caching and related patterns like rate limiting and CDNs, explore:
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