✏️ Explanatory Question

How do you design within a hard cost constraint?

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Answer with Explanation

Cost is the constraint most often ignored in interviews, so raising it scores well.

Levers, roughly in order of impact:

  • Tiered storage - hot data in memory or SSD, warm on standard object storage, cold in archival storage which is roughly 10x cheaper. Most access is to recent data.
  • Retention policy - deleting or aggregating data older than N days often beats any compression scheme.
  • Cache to cut egress - a CDN hit avoids both origin compute and origin bandwidth, usually the largest line item for media.
  • Right-size replication - a replication factor of 3 for critical data, but 2 or erasure coding for data that can be regenerated.
  • Autoscale instead of provisioning for peak - if peak is 3x average, static provisioning wastes about two thirds of capacity.
  • Spot or preemptible instances for stateless batch work.

Then state the trade-off you accepted: "Archived data takes minutes to retrieve, which is acceptable for a compliance export but not for a user facing search."

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