Technology Selection & Deep Technical Knowledge Questions
Deep understanding of specific technologies relevant to complex system design. Master databases (PostgreSQL, Cassandra, DynamoDB, Elasticsearch), message queues (Kafka, RabbitMQ), caching systems (Redis), search engines, and frameworks. Understand their strengths, weaknesses, trade-offs, operational characteristics, scaling patterns, and common pitfalls. Be able to justify technology choices based on specific system requirements.
MediumTechnical
0 practiced
Compare Postgres full-text search and Elasticsearch for a product search system requiring relevance ranking, typo tolerance, analytics, and metrics. Discuss feature differences, scaling, indexing complexity, developer velocity, and operational cost trade-offs.
EasyTechnical
0 practiced
Explain Redis eviction policies (volatile-lru, allkeys-lru, volatile-ttl, volatile-random, allkeys-random, noeviction). For a cache storing session tokens with strict TTLs, which policy would you choose and why? Discuss operational pitfalls (memory spikes, key importance, persistence).
HardSystem Design
0 practiced
Design an Elasticsearch architecture for a global product catalog that must support 10B documents, per-document analytics scoring, and per-region search latency under 100ms. Address index/shard strategy, cross-cluster replication (CCR), cold/warm architecture, routing, and hardware sizing considerations.
HardTechnical
0 practiced
A managed database service used by a sales-critical pilot has a high-severity CVE. As the Solutions Architect, create a risk assessment and mitigation plan that covers immediate containment, customer communication, short-term workarounds, and long-term remediation while minimizing impact to the pilot.
EasyTechnical
0 practiced
Compare Kafka and RabbitMQ for decoupling microservices. Cover delivery semantics (at-most-once, at-least-once, exactly-once), ordering guarantees, scaling characteristics, operational complexity, and typical use cases where one is favored over the other.
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