Designing a Typeahead Suggestion System on AWS

Designing a Typeahead Suggestion System on AWS
Designing a Typeahead Suggestion System on AWS

CLOUD LABS



Designing a Typeahead Suggestion System on AWS

In this Cloud Lab, you’ll learn to build a typeahead service on AWS and fine-tune an AI model to make the typeahead system more engaging.

11 Tasks

intermediate

2hr

Certificate of Completion

Desktop OnlyDevice is not compatible.
No Setup Required
Amazon Web Services

Learning Objectives

An understanding of how to design and build a typeahead suggestion system
Hands-on experience creating and querying a DynamoDB table
The ability to use Amazon ElastiCache for Redis to cache for low-latency access
Hands-on experience setting up a SageMaker endpoint to integrate AI-powered predictions

Technologies
EC2 logoEC2
ElastiCache
SageMaker
ALB logoALB
Cloud Lab Overview

A typeahead suggestion system enhances user experience by predicting and suggesting possible search queries as a user types in a search bar. This system improves search efficiency and reduces user input effort by leveraging caching, real-time processing, and, in recent cases, AI-based predictions.

You’ll build a scalable and highly responsive typeahead suggestion system in this Cloud Lab using AWS services. You’ll start by setting up a DynamoDB table to store search queries and their results. Then, you’ll configure Amazon ElastiCache for Redis to cache the most frequently searched queries, ensuring low-latency responses.

Additionally, you’ll use a fine-tuned AI model and deploy it using Amazon SageMaker as an endpoint to provide intelligent query suggestions.

By the end of this Cloud Lab, you’ll have a fully functional typeahead suggestion system deployed on AWS, leveraging caching, database storage, scalable compute resources, and AI-powered predictions.

The architecture diagram below illustrates the provisioned infrastructure.

Typeahead system using AWS Services
Typeahead system using AWS Services

Cloud Lab Tasks
1.Introduction
Getting Started
Understand Typeahead Systems
2.Deploy the Fine-Tuned Model
Configure the SageMaker Notebook
3.Configuring the Resources
Configure the ElasticCache
Configure and Populate the DynamoDB Table
Configure EC2 Instances
Configure the Load Balancer
4.Typeahead System
Typeahead Application
AI-Based Typeahead Application
5.Conclusion
Clean Up
Wrap Up
Labs Rules Apply
Stay within resource usage requirements.
Do not engage in cryptocurrency mining.
Do not engage in or encourage activity that is illegal.
Hear what others have to say
Join 1.4 million developers working at companies like