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description: A concise overview of core caching concepts for system design, covering eviction policies (LRU, LFU, TTL), the importance of cache hit rate over cache size,...
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# Mastering caching is a game-changer for System Design! If you want to build highly scalable and responsive applications, understanding how to store and retrieve data efficiently is non-negotiable.

**[Sizan](https://daily.dev/sources/e33fy3bk4jcfny1i6g7yy)** · [@sizan5](https://daily.dev/sizan5) · 2 min read · 4 upvotes · 0 comments

## Summary

A concise overview of core caching concepts for system design, covering eviction policies (LRU, LFU, TTL), the importance of cache hit rate over cache size, the challenge of cache invalidation, the thundering herd problem caused by hot key expiration, and request coalescing as a mitigation strategy.

## Content

Here are the core caching concepts every software engineer should know:

1. Eviction Policies (What to remove when the cache is full):

LRU (Least Recently Used): Drops the data that hasn't been accessed in the longest amount of time.

LFU (Least Frequently Used): Drops the data that has the lowest overall access frequency.

TTL (Time To Live): Automatically expires and removes data after a pre-set duration.

1. Hit Rate > Cache Size

A massive cache filled with irrelevant data is useless. A smaller cache equipped with a smart eviction policy that retains highly relevant data will consistently deliver a much higher Cache Hit Rate!

1. The Hard Part: Cache Invalidation

As the famous quote goes, "There are only two hard things in Computer Science: cache invalidation and naming things." Ensuring your cache stays perfectly synchronized with your database when user data is updated remains one of the most complex challenges in backend engineering.

1. Hot Keys & The Thundering Herd

What happens when a highly popular item (a "Hot Key," like a viral post) suddenly reaches its TTL and expires? A "Thundering Herd" of thousands of simultaneous requests will experience a cache miss and smash directly into your database all at once, potentially bringing your servers down.

1. Request Coalescing (The Solution)

To survive a thundering herd, resilient systems use Request Coalescing. Instead of forwarding 10,000 identical queries to the database, the cache server temporarily holds the requests, sends exactly one query to the DB, and then distributes that single response to all 10,000 waiting users simultaneously.

Mastering these concepts will not only help you build crash-proof systems but also crush your next system design interview! 💻✨

---

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