Lead Bank·Software Engineer·Onsite - System Design / Architecture·Senior

SeniorPrefer not to say

Apr 2026

Summary

System design round at Lead Bank for a software engineer role. The whole thing was focused on a hotel reservation system and the interviewer kept pushing on failure scenarios, which apparently went well enough.

Questions Asked (1)

Design a hotel reservation system. Walk through the architecture and handle various failure scenarios in depth.

System DesignTechnical Trade-offsRoot Cause Analysis

Author's notes

The base design part felt manageable but the failure cases are where it got real.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints, then design a scalable, highly available architecture that handles concurrency and failures. Walk through failure scenarios systematically, explaining detection, mitigation, and recovery strategies.

Pro tip: Emphasize idempotency and exactly-once processing for reservations to prevent double-booking, and discuss how you'd monitor and alert on key metrics like booking success rate and latency.

1. Clarify Requirements

Ask about scale (e.g., number of hotels, rooms, bookings per second), consistency needs, and key features like search, booking, payment, and cancellation.

2. High-Level Architecture

Outline components: API gateway, load balancer, microservices (search, booking, payment, inventory), databases (SQL for transactions, NoSQL for search), caching, and message queues.

3. Data Model and Consistency

Design schemas for hotels, rooms, reservations, and users. Discuss ACID transactions for booking, optimistic/pessimistic locking, and distributed transactions if sharded.

4. Failure Scenarios

Identify potential failures: database outages, network partitions, service crashes, double bookings, payment failures. For each, explain detection, mitigation (e.g., retries, circuit breakers, fallbacks), and recovery.

5. Scalability and Trade-offs

Discuss scaling strategies (horizontal scaling, sharding, caching), trade-offs between consistency and availability, and how to handle peak loads.

Key Points to Mention

Idempotency keys for booking requests to prevent duplicate reservations
Database sharding and replication strategies for scalability and fault tolerance
Use of message queues for asynchronous processing (e.g., payment, notifications)
Circuit breakers and retries with exponential backoff for resilience
Monitoring and alerting on key metrics (latency, error rates, booking success rate)
Handling race conditions with optimistic concurrency control or distributed locks

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.