Database Scalability and High Availability Questions

Architectural approaches and operational practices for scaling and maintaining database availability. Topics include vertical versus horizontal scaling trade offs; replication topologies, leader and follower roles, read replicas and replica lag; read write splitting and connection pooling; sharding and partitioning strategies including range based, hash based, and consistent hashing approaches; handling hot partitions and data skew; federation and multi database federation patterns; cache layers and cache invalidation; rebalancing and resharding strategies; distributed concurrency control and transactional guarantees across shards; multi region deployment strategies, cross region failover and disaster recovery; monitoring, capacity planning, automation for failover and backups, and cost optimization at scale. Candidates should be able to pick scaling approaches based on read and write patterns and explain operational complexity and trade offs introduced by distributed data.

MediumTechnical

39 practiced

Scenario: You must implement cross-shard money transfers that must be atomic and consistent. Compare implementation options: two-phase commit, distributed transactions with a transaction coordinator, application-level sagas with compensation, and optimistic conflict resolution. Recommend an approach for high throughput and explain failure modes.

HardSystem Design

40 practiced

Design a centralized observability platform for databases across multiple clouds and clusters to support alerting, anomaly detection, and capacity forecasting. Specify which metrics, logs, traces, and events to collect, storage/retention trade-offs, and how machine learning might be used for anomaly detection.

EasyTechnical

44 practiced

List and compare common cache invalidation strategies used with application-level caches and distributed caches: cache-aside, write-through, write-behind, time-to-live, and explicit invalidation. For each strategy describe benefits, consistency trade-offs, typical use-cases and one operational pitfall.

EasyTechnical

46 practiced

Define sharding and explain the difference between partitioning and sharding in a database context. Give simple examples of horizontal partitioning, vertical partitioning, and when sharding becomes necessary versus using partitioning or indexes.

EasyTechnical

41 practiced

What are the most important database health and availability metrics you would monitor for a production relational database cluster? Include metrics for performance, replication, storage, and query-level diagnostics and explain why each is important.

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