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.

EasyTechnical

0 practiced

Explain the CAP theorem and its implications for distributed databases. As a Solutions Architect, describe how CAP influences your recommendations when choosing a strongly consistent database versus an eventually consistent one for a given application.

MediumTechnical

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Explain quorum reads and writes in distributed stores (e.g., Cassandra). How do read and write quorums affect consistency, latency, and availability? Provide example configurations (e.g., RF=3, W=2, R=2) and describe trade-offs for read-heavy and write-heavy workloads.

EasyTechnical

0 practiced

Explain the purpose of leader election in distributed databases. Describe common algorithms/systems used (Raft, Paxos, ZooKeeper/etcd), how leader election impacts availability, and what architects must consider during network partitions and leader churn.

EasyTechnical

0 practiced

Explain how read replicas work in both traditional RDBMS and distributed database systems. Describe causes of replica lag, how lag affects read consistency and user-facing behavior, monitoring signals to detect lag, and practical mitigation strategies you would recommend to a customer.

MediumSystem Design

0 practiced

A customer demands RPO=1 hour and RTO=2 hours for an OLTP database with peak 20K TPS. Propose backup, snapshot, and recovery strategies (full/incremental backups, WAL shipping, point-in-time recovery), retention policy, and testing cadence to meet those SLAs with minimal production impact.

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