Search Architecture: Zero to Scale

Build production search from Postgres full-text to Elasticsearch at scale

Search Architecture: Zero to Scale is a 180-page engineering guide covering every layer of search — from Postgres tsvector to Elasticsearch clusters, query analysis, ranking tuning, and zero-downtime re-indexing.

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Inside the guide

What You'll Learn

01

180-Page Deep Dive

From Postgres full-text search through Typesense, Meilisearch, and Elasticsearch with code examples in Python and TypeScript.

02

Architecture Decision Trees

Decision trees for choosing the right search engine at each scale tier based on latency, budget, and team size.

03

Ranking & Relevance Chapter

BM25 tuning, semantic re-ranking with embeddings, and A/B testing search quality with NDCG metrics.

04

Production Runbooks

Zero-downtime re-indexing, shard allocation strategies, and incident runbooks for common search outages.

Table of Contents

01180-Page Deep DiveFrom Postgres full-text...
02Architecture Decision TreesDecision trees for...
03Ranking & Relevance ChapterBM25 tuning, semantic...
04Production RunbooksZero-downtime re-indexing, shard...

Who This Is For

Written by engineers, for engineers

Senior Engineer

Building production systems and tired of re-inventing the wheel on every project.

Software Architect

Needs battle-tested patterns to back architectural decisions with evidence.

Startup CTO

Must ship fast without accumulating technical debt that kills you later.

See Inside

A sample from the guide

The Problem

Engineering teams ship basic LIKE queries that fail at 100K records and then panic-migrate

Elasticsearch documentation is vast but lacks opinionated guidance on mapping design and shard strategy

Search quality degrades silently — teams have no framework for measuring and improving relevance

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Guide

$149one-time
  • 180-page PDF
  • Code examples
  • Architecture diagrams
Best Value

Guide + Templates

$199one-time
  • Everything in Guide
  • Terraform modules
  • Docker Compose stacks
  • Slack community access
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Frequently Asked Questions

What experience level is this for?

Mid to senior engineers who have shipped at least one production database-backed app. Basics are not covered.

Is the code in a specific language?

Primary examples use Python (FastAPI) and TypeScript (Node.js). Concepts and configs apply to any language.