AWS architecture for a homesharing app with listings, search, applications, messaging, reviews, saved rooms, and renter ...
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AWS architecture for a homesharing app with listings, search, applications, messaging, reviews, saved rooms, and renter education badges. Uses ALB/EC2, API/Lambda, RDS/DynamoDB, S3, and OpenSearch.
"Build a homesharing platform connecting homeowners with renters" Create a platform for a city that matches homeowners who have spare rooms with vetted renters: Core Features: Listings: Homeowners create room listings with photos, amenities, house rules, and pricing Search & Browse: Renters can browse available rooms with filters (price, location, amenities) Applications: Renters apply to listings; homeowners review and accept/reject Messaging: In-app messaging between homeowners and renters Reviews: Mutual rating system after completed stays (1-5 stars) Saved Listings: Renters can bookmark rooms they're interested in Education Pipeline: 4 learning modules (Financial Basics, Credit Building, Renter Responsibilities, Housing Readiness) Progress tracking with completion badges displayed on profiles Badge count shown on applications so homeowners see renter preparedness User Types: Homeowners: List rooms, review applications, message renters Renters: Browse listings, apply, complete education modules, leave reviews
Our Team Yellow presented a home sharing platform during the Launchathon in Stamford, CT, in January 2026. The pitch concept secured second place at the Launchathon. This is an AWS representation of such a platform.
about 2 months ago
7 days ago
I appreciate the effort put into designing the homesharing platform architecture, but I have significant concerns regarding the reliance on multiple database instances for various services. Specifically, using both RDS and multiple DynamoDB tables could lead to data consistency issues, especially with features like messaging and saved listings. The architecture does not clearly address how transactional integrity will be maintained between these services. For instance, if a renter saves a listing while also messaging a homeowner, ensuring these actions are consistent and up-to-date could be problematic without a robust strategy for eventual consistency or data synchronization. Additionally, the duplication of components like the ALB and RDS instances raises concerns about operational complexity and potential single points of failure. This could lead to increased latency and complicate maintenance. In a production environment, these factors could lead to a poor user experience or even data loss during peak usage times. I recommend consolidating some of the components and implementing clear strategies for data consistency to mitigate these risks. Overall, thoughtful reevaluation of the data management strategy is essential for the platform's success.
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