Design two systems. You can assume a large-scale production environment; focus on clear APIs, data models, scaling, reliability, and trade-offs.

Part A) Design an asynchronous Job/Task system (service-oriented)

Design a service that lets clients submit background jobs and later query results.

Requirements

• Clients can create jobs and poll/subscribe for status.
• Jobs move through well-defined states (e.g., pending/running/succeeded/failed/canceled).
• Support retries with exponential backoff.
• Ensure idempotency (no duplicate execution for the same logical request).
• Choose storage (RDBMS vs NoSQL) and justify.

Discuss explicitly

• API design and state transitions
• Worker model / scheduling
• Retry + backoff, dead-letter handling
• Idempotency strategy
• Observability (metrics/logging/tracing)

Part B) Design a high-throughput cache system (Redis-like / in-memory layer)

Design a caching layer in front of a database to reduce latency and increase throughput.

Requirements

• Very high QPS, low latency reads, concurrent reads/writes.
• Cache key design, eviction (LRU/LFU/TTL).
• Multi-node scaling and sharding.
• Cache consistency and invalidation strategy; explain trade-offs vs DB consistency.
• Handle hot keys.
• High availability and performance under failures.

Discuss explicitly

• Consistency model and write/read paths
• Invalidation strategies and failure modes
• Sharding/replication and rebalancing
• Hot key mitigation and rate limiting
• Capacity planning and SLOs