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.
Technical Risk Assessment and Problem Solving
Focuses on evaluating technical risk, making trade off decisions, and designing mitigations when systems face complexity or change. Candidates should demonstrate identifying potential failure modes, modeling consequences such as data loss or downtime, weighing alternatives (for example full cutover versus incremental migration), estimating operational complexity and monitoring requirements, and deciding when to involve subject matter experts. Covers decision frameworks, data driven risk assessment, rollback and testing strategies, service level objective considerations, and communicating technical risk to stakeholders while balancing schedule and reliability.
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.
Reliability High Availability and Tradeoffs
Design patterns and decision making for ensuring availability correctness and graceful behavior under failure while balancing technical trade offs. Topics include redundancy and failover strategies active passive and active active deployments; fault isolation using bulkheads and circuit breaker patterns; graceful degradation and feature gating strategies; defining and mapping service level objectives and service level agreements to recovery point and recovery time objectives; multi region and multi availability zone deployment considerations; testing for reliability including chaos engineering and fault injection; and reasoning about consistency versus availability trade offs and the operational cost of stronger guarantees. Candidates should be able to choose reliability patterns to meet business objectives and to explain their implications for cost performance and maintainability.
Fault Tolerance and System Resilience
Designing systems to anticipate, tolerate, contain, and recover from component and network failures while minimizing customer impact and preserving correctness. Topics include identifying common failure modes and single points of failure, redundancy and isolation patterns at hardware, service, and geographic levels, and failover strategies including active active and active passive. Cover retry policies with exponential backoff, timeouts, circuit breaker and bulkhead patterns, graceful degradation, rate limiting, and backpressure techniques to protect systems during overload. Discuss orchestration of node rejoin and state rebuild, replication strategies and consistency trade offs, leader election and consensus implications, and techniques to avoid and mitigate split brain. Explain monitoring, health checks, alerting, and metrics such as mean time to recovery and mean time between failures to guide operational improvements. Include testing for resilience through chaos engineering and fault injection, handling flaky components in test environments, analysis of past failures and refactoring for resiliency, and operational practices that reduce blast radius and speed recovery.
System Design and Architecture Fundamentals
Comprehensive coverage of designing scalable, reliable, and maintainable software systems, combining foundational concepts, common architectural patterns, decomposition techniques, infrastructure design, and operational considerations. Candidates should understand core principles such as horizontal and vertical scaling, caching strategies and placement, data storage trade offs between relational structured query language databases and non relational databases, application programming interface design, load distribution and fault tolerance. They should be familiar with architectural styles and patterns including client server and layered architectures, monolithic and microservices decomposition, service oriented and event driven designs, gateway and proxy patterns, and resilience patterns such as circuit breakers and asynchronous processing. Assessment includes the ability to decompose a problem into logical components and layers, define component responsibilities, map data flows between ingestion processing storage and serving layers, and select appropriate infrastructure elements such as application servers caches message queues and database replication models. Interviewers evaluate estimation of scale and load and reasoning about trade offs such as consistency versus availability and partition tolerance latency versus throughput coupling versus cohesion and cost versus complexity, and the ability to justify architecture decisions. Candidates should be able to sketch high level designs, communicate architecture to technical and non technical stakeholders, propose migration paths such as when to combine or transition between patterns, and describe operational runbooks including failure mode mitigation monitoring observability and incident recovery. Practical topics include caching eviction policies such as least recently used and least frequently used load balancing approaches such as round robin and least connections rate limiting techniques replication and sharding strategies and design choices for synchronous request response versus asynchronous queue based messaging. Emphasis is on clarifying requirements estimating constraints proposing reasonable architectures and articulating trade offs and evolution paths rather than only low level implementation details.
Technical Decision Making and Risk Management
Evaluate the ability to identify technical risks early influence architecture decisions and manage tradeoffs between speed quality and long term maintainability. Topics include dependency risk scalability and reliability risks integration complexity mitigation strategies such as prototypes staged rollouts observability and automated testing frameworks for balancing technical debt against schedule and approaches to track escalate and communicate risk. Interviewers look for how candidates involve engineering teams in risk assessment make defensible technical choices and adapt decisions when new information arises.
Clarifying Scope and System Constraints
Ability to ask targeted questions to understand system requirements: user base, traffic volume (requests per second), latency targets, data consistency requirements, compliance/regulatory constraints. Understanding that different systems have different requirements and that constraints shape architecture decisions.
Technical Depth and System Understanding
Demonstrated ability to quickly grasp complex technical domains and explain system design, architecture, and tradeoffs. Cover distributed systems fundamentals, application programming interfaces, software architecture patterns, performance and scalability concerns, reliability considerations, and approaches to validating technical accuracy. In interviews, present concrete examples from projects that highlight how you diagnosed technical problems, evaluated alternatives, and made design decisions while communicating clearly to non technical stakeholders.