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.
