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Solution Architecture and Design Questions

Designing and architecting end to end technical solutions for enterprise and complex systems, covering both the methodology for approaching architecture problems and the practical component level design work. Candidates should demonstrate a repeatable structured approach to elicit and document functional and non functional requirements, identify constraints and stakeholders, evaluate and compare multiple architectural options, and justify technology choices. They should produce high level and component level designs that show major services, presentation layers, application tiers, data layers, data flows, storage strategies, application programming interfaces, integration points with external and third party systems, and data movement and transformation. Strong responses explicitly address quality attributes such as scalability, performance, availability, fault tolerance, reliability, consistency and security as well as compliance and data protection concerns. Operational concerns must be covered including deployment topology, multi region and hybrid cloud strategies, monitoring and observability, logging, capacity planning, backup and disaster recovery, deployment and release strategies, maintenance, and operational run books. Candidates should discuss communication patterns including synchronous remote procedure calls and asynchronous messaging, storage trade offs between relational and non relational datastores and data warehouses, failure modes and mitigation strategies, incremental evolution and migration paths, and cost and feasibility constraints. Interviewers assess the ability to present clear diagrams, explain interactions and failure modes, reason about trade offs, and justify design decisions against requirements and constraints.

HardSystem Design
17 practiced
Define SLOs and SLIs suitable for dashboard delivery: page load time, time-to-first-byte for visualizations, data freshness, and error rate. Propose alert thresholds, escalation policies, and concrete runbook steps for breaches including temporary mitigation and long-term remediation.
HardTechnical
21 practiced
Case study: A fintech needs near-real-time fraud dashboards and immutable audit trails. Design an architecture ensuring low-latency alerts, secure append-only audit logs, explainability of alerts (why a transaction is flagged), role-based access for reviewers, and regulatory compliance. Cover data flows, storage choices, and operational playbooks.
MediumTechnical
23 practiced
Your product team expects a 10x increase in dashboard users over 6 months. Propose a capacity planning and scaling strategy covering API servers, visualization rendering, cache sizing, and the semantic layer. Discuss horizontal vs vertical scaling, autoscaling triggers, cost trade-offs, and how to validate the plan with load testing.
MediumTechnical
24 practiced
Design an approach to data masking and anonymization for PII used in aggregated BI reports. Describe techniques (tokenization, deterministic hashing, k-anonymity, differential privacy), when to apply each, impact on analytical utility, and how to document residual re-identification risk for compliance stakeholders.
HardTechnical
18 practiced
Create an outline for runbooks and on-call playbooks tailored to BI incidents such as data freshness lag, corrupted materialized views, and failed scheduled reports. For each incident type provide detection signals, immediate mitigation steps, rollback procedures, stakeholder communication templates, and post-incident actions.

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