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Today's Question

2 in a row

Caching

You're caching API responses. Reads dominate; data updates every 5 minutes. What's the right invalidation strategy?

ATTL-based expiration

BWrite-through cache, no expiry

CNo caching, hit the DB every time

DManual purge on every request

✓ Correct. TTL keeps reads cheap, bounds staleness to 5 min.

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Mini Lesson

Caching

Fast reads, cheaper cloud bill

What it is

At its core, caching is about temporarily storing frequently-accessed data in a fast, in-memory store so future reads don't have to hit a slower underlying system.

Done well, caching makes slow operations feel instant. It cuts latency for your users, reduces load on your database, and shrinks your cloud bill. Done poorly, it causes stale data, hard-to-reproduce bugs, and system-wide inconsistencies.

There are 2 hard problems in computer science: cache invalidation, naming things, and off-by-one errors.

Answer a new question every day

One real system design tradeoff lands in your feed each day. Multiple choice, ordering, matching.

Take mini lessons on new skills, get quizzed on the results

Short, focused lessons introduce a new concept, then quiz you on the spot so it actually sticks.

Review failed questions

Every question you miss comes back later. Spaced repetition makes sure the gaps in your knowledge get filled in.

What you'll master

The full system design surface.

CachingLoad BalancingDatabasesShardingReplicationMessage QueuesConsistencyRate LimitingCDNsAPI DesignSearchStorageMicroservicesObservability

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