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).
Edge Computing vs. Cloud Processing Trade Offs
Understanding when to process data on embedded devices vs. sending to cloud/servers. Factors: latency requirements, bandwidth constraints, privacy, cost, and computational capability. Designing hybrid systems with intelligent edge processing.
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.
Making Difficult Technical Decisions
Situations where you had to make trade-offs, navigate competing priorities, or choose between technical approaches with real consequences.
Trade-Off Analysis and Justification
Ability to identify key nonfunctional requirements and constraints and to compare alternative designs with clear, quantitative reasoning. Expect discussion of consistency versus availability, latency versus throughput, cost versus performance, operational complexity, and implementation risk. Candidates should demonstrate how to quantify trade offs using metrics such as latency percentiles, throughput, cost per request, and availability targets, how to choose appropriate consistency models and failure modes, and how to document and justify the selected architecture given product and business priorities.
Technical Vision and Strategy
Covers long term technical direction, architecture choices, infrastructure and platform strategy, and how technical roadmaps align with business goals. Interviewers will probe your perspective on where technology is heading, major architectural trade offs, cloud and modernization approaches, and how you would shape the organization or team to meet future needs. At senior levels this includes strategic thinking beyond immediate problems, influencing cross team technical initiatives, prioritization of long term investments, and communicating a coherent technical roadmap.
IoT Systems Architecture and Design
Covers architecture and design of distributed Internet of Things systems and connected embedded devices. Core topics include edge computing patterns, sensor and actuator network topologies, gateway and mesh network architectures, cloud integration and data pipelines, and trade offs between edge processing and cloud processing. Also includes networking protocols commonly used in constrained environments such as WiFi, Bluetooth, ZigBee, and LoRaWAN, plus connectivity strategies for unreliable networks including buffering, retries, offline operation, and data aggregation and filtering. Candidates may be evaluated on device to cloud data flow, scalability considerations from hundreds to millions of devices, performance and power trade offs on resource constrained hardware, deployment patterns for gateways and proxies, and high level fault tolerance and monitoring strategies.
System Architecture and Tradeoffs
Ability to decompose complex systems into components and define clear responsibilities, interfaces, and interactions. Evaluate architectural alternatives and articulate core trade offs such as consistency versus availability, latency versus throughput, simplicity versus extensibility, and cost versus performance. Explain how design choices affect scalability, resilience, failure modes, and operational burden, and justify architecture decisions based on expected load patterns and business requirements.
Algorithm Design & Real-Time System Optimization
Algorithm design techniques and real-time optimization strategies applicable to distributed systems and latency-sensitive architectures. Covers scheduling, resource management, concurrency, distributed algorithms, load balancing, and performance optimization under strict latency requirements.