Guided Lab Brief

Full-Text Search with Elasticsearch

Build a search feature with Elasticsearch for fast, fuzzy, full-text search across your content.

Start LabReview ChapterBrowse Guided Labs

Overview

Build a search feature with Elasticsearch for fast, fuzzy, full-text search across your content.

Users expect instant search.

You will build 4 architecture steps that model production dependencies.

You will run 1 failure experiment to observe bottlenecks and recovery behavior.

Success target: Search queries complete in <50ms, database and search index stay in sync.

Learning Objectives

  • Understand how inverted indexes enable fast full-text search
  • Know when to use Elasticsearch vs SQL queries
  • Learned about sharding for search parallelism
  • Experienced the difference between search-optimized and brute-force querying

Experiments

  1. Increase Elasticsearch query latency to simulate poor index configuration

Failure Modes to Trigger

  • Trigger: Increase Elasticsearch query latency to simulate poor index configuration

    Observe: 500ms search latency makes the search feel painfully slow. Users abandon searches that take more than 200ms. Autocomplete is completely broken at this latency.

Next Guided LabReinforce with Quizzes