Travala: Crypto-Powered Travel Booking
Contributed to a global travel booking platform enabling users to book hotels, flights, and activities using 100+ cryptocurrencies, with an integrated rewards and loyalty system.
Travala
9 months
Full Stack Engineer
Booking Travel with Crypto, Without the Volatility Risk
Travel bookings involve multi-step confirmation flows: a user books a hotel, the platform confirms with a third-party supplier, the user pays, and all of that needs to complete reliably even when the crypto payment is pending confirmation on-chain. The challenge was building a booking system that felt instant and trustworthy to users, even when the underlying payment confirmation could take seconds to minutes.
The platform also needed to support a loyalty and rewards system (AVA tokens) where every booking earned points redeemable against future bookings, which added another layer of transactional complexity across the payment, booking, and rewards services.
- Crypto payment confirmation latency (seconds to minutes) vs user expectation of instant booking confirmation
- Integration with 10+ third-party travel suppliers, each with different APIs and availability schemas
- Rewards/loyalty calculations that needed to be accurate and consistent across all booking types
- High availability requirements, travel is time-sensitive, downtime means real revenue loss
- Price volatility handling, crypto price between booking and payment completion could shift
Architecture: Queue-Based Booking with Optimistic Confirmation
The booking confirmation flow was built around RabbitMQ. When a user initiated a booking, the system immediately created a pending booking record and sent a confirmation to the user, then queued the actual supplier API calls and payment verification as background jobs. This decoupled the user-facing response time from the supplier integration latency.
Redis was used heavily for two purposes: caching travel availability (supplier API calls are expensive and slow), and storing short-lived booking sessions with price locks. When a user selected a hotel, the current price was locked in Redis for 10 minutes, protecting against price changes during the checkout flow.
PostgreSQL handled the core transactional data: bookings, payments, rewards balances. The rewards system was implemented as a separate service that listened to booking completion events and applied points calculations atomically using database transactions.
Key technical decisions
Decoupled the user response from supplier API calls. If a supplier was slow or temporarily unavailable, the booking job would retry without the user waiting. Dead-letter queues caught failures for manual review.
Travel supplier APIs are rate-limited and slow. Caching availability responses in Redis with short TTLs (5–15 minutes) dramatically reduced supplier API calls and improved search response times.
Crypto price volatility meant a selected price could change between search and checkout. Redis-backed price locks with TTLs protected users from bait-and-switch pricing and simplified payment calculation.
Travel is a high-intent search category. Server-side rendering of destination pages, hotel listings, and landing pages was critical for SEO and Google Travel integration.
Outcome
Helped ship a travel platform that processed bookings across 100+ cryptocurrencies reliably and at scale, with a seamless user experience despite the underlying complexity of crypto payments and third-party supplier integrations.
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