I started with the data model, which felt natural: a users table with a balance column, a reservations table keyed on job ID, and a usage log for reporting.
Start by clarifying requirements and scale, then design a data model with user balances and a ledger for auditability. Propose a two-phase commit-like flow: reserve credits at job start, deduct on completion, and handle failures with refunds. Discuss trade-offs between consistency, latency, and complexity.
Pro tip: Emphasize idempotency and atomicity in credit operations to prevent double-spending or lost refunds, especially in distributed systems. Mention that using a ledger (append-only log) simplifies auditing and reconciliation.
Ask about expected QPS, number of users, job types, and consistency requirements. Determine if real-time balance updates are needed or if eventual consistency is acceptable.
Propose tables for users (balance), jobs (status, GPU type, duration, cost), and a ledger for credit transactions. Consider using a relational database for ACID guarantees.
Outline APIs for granting, reserving, deducting, refunding, and reporting. Ensure each operation is idempotent and atomic, using transactions or distributed locks.
Describe the flow: job submission checks balance, reserves credits, runs job, then deducts or refunds based on outcome. Include error handling for insufficient funds and job failures.
Discuss partitioning, caching, and asynchronous processing. Compare strong vs. eventual consistency, and how to handle concurrent reservations.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.