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.

MediumSystem Design

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Describe a safe plan for rebalancing data when adding capacity to a sharded relational database with live traffic. Cover chunk selection, throttling, routing updates during migration, consistency verification, and rollback strategies in case of failures mid-reshard.

MediumTechnical

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Compare range-based sharding vs hash-based sharding for a time-series logging database that stores billions of rows. Discuss which approach better supports time-range queries, compaction/TTL, rebalancing costs, and how TTL/archival interacts with each approach.

HardTechnical

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Provide a cost-optimization plan for a multi-region distributed database running 24/7 under variable load. Consider compute vs storage vs network egress costs, replication factor choices, storage tiering, reserved instances vs on-demand, and autoscaling policies. Identify short-term wins and longer-term architectural changes to reduce TCO.

HardSystem Design

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Design a multi-master replication system across three regions allowing writes in any region that must deterministically resolve conflicting writes and converge. Include conflict-resolution policies (last-write-wins, CRDTs, application-level merge), metadata required (vector clocks), and operational considerations for partitions and eventual convergence.

EasyTechnical

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As a Solutions Architect, explain the differences between vertical scaling (scale-up) and horizontal scaling (scale-out) for databases. Describe pros and cons, operational impacts (maintenance, backups, failover), typical triggers to choose each approach, and two real-world examples where one is preferable over the other.

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