Cache invalidation strategies in HLD - Practice Problems & Coding Challenges

Challenge - 5 Problems

🧠 Conceptual

intermediate

Understanding Cache Invalidation Types

Which cache invalidation strategy immediately removes or updates cached data when the original data changes?

A Lazy invalidation

B Manual cache clearing

C Time-to-live (TTL) expiration

D Write-through caching

💡 Hint

Think about which strategy keeps cache and database synchronized instantly.

Write-through caching updates the cache at the same time as the database, ensuring immediate consistency.

❓ Architecture

intermediate

Choosing Cache Invalidation for a News Website

A news website updates articles frequently but can tolerate slight delays in showing updates. Which cache invalidation strategy best balances freshness and performance?

A Time-to-live (TTL) expiration

B Write-back caching

C Write-through caching

D Manual cache clearing

💡 Hint

Consider a strategy that automatically expires cache after a set time.

TTL expiration allows cached data to live for a set time, balancing freshness and reducing load.

❓ scaling

advanced

Scaling Cache Invalidation in Distributed Systems

In a distributed system with multiple cache nodes, which cache invalidation approach helps maintain consistency without excessive network overhead?

A Each cache node polling the database for changes every second

B No cache invalidation, relying on TTL only

C Using a centralized cache invalidation service with asynchronous notifications

D Broadcasting invalidation messages to all cache nodes synchronously

💡 Hint

Think about reducing network chatter while keeping caches updated.

A centralized invalidation service with async notifications reduces network load and keeps caches consistent efficiently.

❓ tradeoff

advanced

Tradeoffs in Cache Invalidation Strategies

Which statement correctly describes a tradeoff when using lazy invalidation compared to write-through caching?

A Lazy invalidation reduces write latency but risks serving stale data until invalidation occurs.

B Write-through caching may serve stale data longer than lazy invalidation.

C Lazy invalidation guarantees immediate cache consistency but increases write latency.

D Write-through caching reduces read latency by avoiding cache updates on writes.

💡 Hint

Consider how each strategy affects latency and data freshness.

Lazy invalidation delays cache updates, lowering write latency but risking stale reads until invalidation.

❓ estimation

expert

Estimating Cache Expiration Time for Optimal Performance

You manage a cache for a product catalog updated on average every 10 minutes. Cache misses cost 100ms extra latency, and stale data causes 1% user dissatisfaction. Which TTL expiration time balances latency and freshness best?

A 1 minute TTL

B 5 minutes TTL

C 20 minutes TTL

D 10 minutes TTL

💡 Hint

Think about reducing stale data while minimizing cache misses.

5 minutes TTL reduces stale data exposure and limits cache misses, balancing user experience and performance.