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You design a Rate Limiter backed by Redis, but Redis becomes a single point of failure — if it stalls, the whole API stalls. How do you fix this, and would you fail open or fail closed?

A real Walmart interview scenario testing whether you've thought through what happens when your own fix becomes the new bottleneck.

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You design a Rate Limiter backed by Redis, but Redis becomes a single point of failure — if it stalls, the whole API stalls. How do you fix this, and would you fail open or fail closed?

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Continue to Compare cache penetration, cache breakdown (hot key expiry), and cache avalanche — three distinct ways a cache layer can fail under load.← Back to all Company Round Scenarios questions