Systems Architecture & Distributed Systems Topics
Large-scale distributed system design, service architecture, microservices patterns, global distribution strategies, scalability, and fault tolerance at the service/application layer. Covers microservices decomposition, caching strategies, API design, eventual consistency, multi-region systems, and architectural resilience patterns. Excludes storage and database optimization (see Database Engineering & Data Systems), data pipeline infrastructure (see Data Engineering & Analytics Infrastructure), and infrastructure platform design (see Cloud & Infrastructure).
Trade Off Analysis and Decision Frameworks
Covers the practice of structured trade off evaluation and repeatable decision processes across product and technical domains. Topics include enumerating alternatives, defining evaluation criteria such as cost risk time to market and user impact, building scoring matrices and weighted models, running sensitivity or scenario analysis, documenting assumptions, surfacing constraints, and communicating clear recommendations with mitigation plans. Interviewers will assess the candidate's ability to justify choices logically, quantify impacts when possible, and explain governance or escalation mechanisms used to make consistent decisions.
Architecture and Technical Trade Offs
Centers on system and solution design decisions and the trade offs inherent in architecture choices. Candidates should be able to identify alternatives, clarify constraints such as scale cost and team capability, and articulate trade offs like consistency versus availability, latency versus throughput, simplicity versus extensibility, monolith versus microservices, synchronous versus asynchronous patterns, database selection, caching strategies, and operational complexity. This topic covers methods for quantifying or qualitatively evaluating impacts, prototyping and measuring performance, planning incremental migrations, documenting decisions, and proposing mitigation and monitoring plans to manage risk and maintainability.
Scalable System Design and Architecture
Focuses on designing systems that scale to large numbers of users and high load while balancing consistency, availability, and operational concerns. Candidates should discuss application programming interface design, data flow, load distribution and load balancing, caching strategies, database selection and partitioning, indexing, replication, consistency models, microservices boundaries, synchronous and asynchronous communication patterns, message and event architectures, deployment and rollout strategies, and measures for capacity planning and performance optimization. Answers should include trade off analysis, expected bottlenecks, quantification where possible, and rationale for architecture decisions.
Technical Decision Making and Trade Offs
How to evaluate and clearly articulate trade offs when choosing technologies and designing solutions. This includes weighing reliability, performance, cost, development time, and operational complexity; comparing alternatives; identifying risks and mitigation plans; and explaining why a particular approach best meets current constraints and future needs. Strong answers show a metrics oriented mindset, consideration of team capabilities, and a willingness to revise decisions as new data arrives.
Decision Making Under Uncertainty
Focuses on frameworks, heuristics, and judgment used to make timely, defensible choices when information is incomplete, conflicting, or evolving. Topics include diagnosing unknowns, defining decision criteria, weighing probabilities and impacts, expected value and cost benefit thinking, setting contingency and rollback triggers, risk tolerance and mitigation, and communicating uncertainty to stakeholders. This area also covers when to prototype or run experiments versus making an operational decision, how to escalate appropriately, trade off analysis under time pressure, and the ways senior candidates incorporate strategic considerations and organizational constraints into choices.