Google Style Search Autocomplete System - Part 6 Complete Development Roadmap, Commands and Troubleshooting Guide

A complete step-by-step execution plan to build the Google-style autocomplete system from scratch including development order, commands, testing checklist and troubleshooting.

Complete Development Roadmap

This guide explains the exact order in which you should develop the autocomplete platform. Following the correct sequence avoids integration problems and helps you build the project like a real production team.

Phase 1: Setup Development Environment

  • Install Java 21
  • Install Node.js 20
  • Install Docker Desktop
  • Install Git
  • Install IntelliJ IDEA
  • Install Postman

Verify Installation

java -version

node -v

npm -v

docker --version

git --version

Phase 2: Create Git Repository

mkdir search-autocomplete-platform

cd search-autocomplete-platform

git init

mkdir frontend
mkdir services
mkdir infrastructure

Recommended Commit Strategy

  • Initial project structure
  • Docker infrastructure added
  • Spring Boot search service completed
  • Elasticsearch integration completed
  • Redis cache completed
  • Kafka analytics completed
  • React frontend completed
  • AWS deployment completed

Phase 3: Start Infrastructure First

Always start external services before developing application logic.

cd infrastructure

docker compose up -d

Check Running Containers

docker ps

Verify Elasticsearch

curl http://localhost:9200

Verify Redis

docker exec -it search-redis redis-cli

PING

Phase 4: Build Backend Service

  • Create Spring Boot project
  • Configure PostgreSQL
  • Create Keyword entity
  • Create repository layer
  • Create REST API
  • Add Elasticsearch document
  • Create search indexing process
  • Add Redis caching

Backend Testing Order

  • Test database connection
  • Insert sample keywords
  • Verify Elasticsearch indexing
  • Test search API
  • Verify Redis cache response

Run Backend

cd services/search-service

mvn clean install

mvn spring-boot:run

Test Search API

GET http://localhost:8080/api/search?q=spring

Phase 5: Add Kafka Analytics

  • Create analytics-service
  • Create Kafka topic
  • Add producer in search service
  • Create consumer
  • Store search history
  • Calculate trending keywords

Kafka Topic Creation

kafka-topics.sh \
--create \
--topic search-events \
--bootstrap-server localhost:9092

Kafka Testing

kafka-console-producer.sh \
--topic search-events \
--bootstrap-server localhost:9092

Phase 6: Build React Application

  • Create React TypeScript project
  • Create search component
  • Create API client
  • Add debounce logic
  • Create dropdown suggestions
  • Connect backend API

Run Frontend

cd frontend

npm install

npm run dev

Complete Local Testing Flow

Open Browser

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Type: spring

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React calls API

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Spring Boot receives request

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Redis Check

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Elasticsearch Search

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Return Suggestions

Common Problems and Solutions

Production Deployment Checklist

  • Create AWS account
  • Create S3 bucket
  • Deploy React build
  • Create Docker images
  • Push images to AWS ECR
  • Deploy backend containers
  • Create RDS PostgreSQL
  • Create Redis cluster
  • Configure OpenSearch
  • Configure Load Balancer
  • Enable HTTPS

Final Project Checklist

Final Advice for Building This Project

Do not try to build everything together. Build one layer at a time. First make the search API work, then add Elasticsearch, then caching, then analytics, then frontend and finally cloud deployment. This approach matches how production engineering teams develop complex systems.