Making document search faster
A fictional enterprise case study focused on measurement and tradeoffs.
The scenario
A fictional publishing team says document search feels slow as its content grows. The first task is to find out which part of the journey is responsible.
Start with evidence
Measure the full request path: client behavior, API processing, authorization, queries, and result rendering. Choose a representative test set before changing the architecture.
Options to explore
Compare improvements to query shape and indexes with caching or a separate search index. Each option introduces different operational and freshness costs.
Protect correctness
A fast result is not useful if it exposes a restricted document or stays stale after an update. Include access rules, deletions, and index freshness in the design.
How I would validate it
Compare the same workloads before and after a change. Report latency percentiles, relevance, freshness, operational cost, and the limits of the test. Publish actual numbers only after measuring them.