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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.

HardTechnical
0 practiced
Postgres query planner chooses a sequential scan even when an index exists; prepared statement parameterization appears to change the chosen plan (parameter sniffing). How do you diagnose, reproduce, and fix planner misestimates? Consider statistics, extended statistics, query rewriting, and planner configuration options.
EasyTechnical
0 practiced
Design a DynamoDB partition key strategy for a social-media feed system where users have widely varying follower counts (1 to 10M). Explain how you avoid hot partitions, support fan-out reads for feeds, and enable efficient feed generation for both high- and low-fanout users.
MediumTechnical
0 practiced
Compare cost and performance for a read-heavy analytics workload between: DynamoDB on-demand, DynamoDB provisioned with autoscaling, and self-managed Cassandra on EC2. Consider peak vs steady-state traffic, cost predictability, operational effort, and failure modes.
EasyTechnical
0 practiced
Compare relational databases (e.g., PostgreSQL) with column-family and key-value stores (e.g., Cassandra, DynamoDB). For a new system that requires complex joins, strong consistency for transactions, and ad-hoc analytical queries, explain which paradigm you would choose, why, and which trade-offs you'll accept as a Solutions Architect.
HardTechnical
0 practiced
Assess the trade-offs of building a custom search engine, using a managed Elasticsearch service, or adopting a SaaS search provider (e.g., Algolia) for a large e-commerce business. Compare development effort, relevance/control, feature velocity, total cost, data privacy, and scaling characteristics.

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