Infrastructure and Database Systems Questions

Fundamental infrastructure and database engineering concepts relevant to analytics platforms and general backend systems. Topics include relational and non relational database architecture indexing strategies query optimization replication and consistency trade offs sharding and partitioning approaches caching systems design message queues and event streaming systems and how these components integrate to meet performance reliability and cost objectives. Candidates should be able to reason about capacity planning high availability disaster recovery backup strategies and operational concerns such as monitoring alerting and graceful degradation under load.

MediumTechnical

26 practiced

Describe how PostgreSQL MVCC works including transaction IDs, snapshots, visibility rules, and how MVCC leads to table and index bloat. Explain how you would detect bloat in production, and remediation steps such as vacuuming, autovacuum tuning, reindexing, and freezing.

EasyTechnical

24 practiced

Explain cache stampede (thundering herd) and three practical mitigation techniques you could implement for a Redis-backed distributed cache in a high-throughput service. For each mitigation, mention operational trade-offs and implementation complexity.

MediumTechnical

32 practiced

Explain sharding strategies: range-based sharding, hash-based sharding, and directory-based sharding. For each, discuss hotspotting risk, resharding complexity, ability to support range queries, and an SRE-friendly evaluation checklist for choosing a shard key.

MediumTechnical

28 practiced

Explain the differences between row-oriented and column-oriented stores (row-store vs column-store). For analytic workloads and OLTP workloads, explain the performance, compression, I/O patterns, and typical operational trade-offs an SRE should consider when selecting a storage engine.

HardTechnical

30 practiced

Explain LSM compaction strategies (levelled vs tiered). For a write-heavy workload, describe how compaction affects read amplification, write amplification, and space amplification. Propose tuning knobs and operational processes to reduce compaction impact while maintaining acceptable read latency.

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