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).
Marketplace Core Systems
Core marketplace systems architecture covering the Booking, Search, and Listings subsystems. Includes service decomposition into microservices, API design and inter-service communication, data consistency models (strong vs eventual), search indexing and relevance, catalog/listing management, booking workflows and orchestration, cross-service transactions, caching strategies, scalability, fault tolerance, and multi-region/global distribution considerations in a marketplace platform.
Full Stack Architecture and Feature Design
Ability to design complete features considering frontend UX, backend API design, database schema, and data flow. Understanding of separation of concerns and communication between layers. API-first design thinking. Discussing trade-offs (e.g., complex queries on backend vs post-processing on frontend). Designing for extensibility and maintainability.
System Architecture Communication and Documentation
Assess the candidate ability to describe, document, and communicate system architecture both visually and verbally. Candidates should present what a system does and who uses it, identify major components and how they interact, show data flow and integration points, and explain critical architectural decisions and trade offs. Interviewers expect clear diagrams using standard conventions that show high level views, component interactions, and deployment topology, accompanied by concise narrative documentation. Strong answers include multiple views tailored to the audience, labeled diagrams, and justification of design choices while avoiding unnecessary implementation detail. Candidates should be able to discuss scaling strategies, reliability and operational considerations including failure modes, migration paths, observability, and deployment considerations. The scope includes common architectural building blocks such as microservices, application programming interfaces, databases, caching layers, and message buses, as well as consistency and availability implications and service to service communication patterns, and the connection between technical choices and business context.
Network Architecture and Communication Patterns
Design and analysis of network architectures and service communication patterns for reliable, performant, and secure distributed systems. Topics include network topology and capacity planning, load balancing strategies, content delivery networks, caching and edge delivery, application programming interface gateway design, service to service communication patterns including synchronous and asynchronous messaging, message queues, publish subscribe, request routing, retries and backoff, timeouts, idempotency, circuit breakers, bulkheads, and service mesh considerations. Also covers latency optimization, failure modes and resilience, observability and monitoring, network security principles such as encryption and segmentation, and how architectural choices affect scalability and operational complexity.
Backend Layered Architecture and API Design
Covers server side layering patterns and API design best practices. Topics include controller or handler layers, service and business logic layers, data access layers, repository patterns, dependency injection, API design (RESTful, gRPC), versioning, authentication and authorization patterns, pagination and rate limiting, and when to apply specific patterns to improve maintainability and testability.
CAP Theorem and Consistency Models
Understand the CAP theorem and how Consistency, Availability, and Partition Tolerance interact in distributed systems. Know different consistency models including strong consistency such as linearizability, eventual consistency, causal consistency, and session consistency, and how to apply them to different use cases. Be familiar with consensus protocols and distributed coordination primitives such as Raft and Paxos, quorum reads and writes, two phase commit and when to use them. Understand trade offs between consistency and availability under network partitions, patterns for hybrid approaches where different data uses different guarantees, and the product and developer experience implications such as latency, stale reads, and API contract clarity.
Caching Strategies and Patterns
Comprehensive knowledge of caching principles, architectures, patterns, and operational practices used to improve latency, throughput, and scalability. Covers multi level caching across browser or client, edge content delivery networks, application in memory caches, dedicated distributed caches such as Redis and Memcached, and database or query caches. Includes cache design and selection of technologies, defining cache boundaries to match access patterns, and deciding when caching is appropriate such as read heavy workloads or expensive computations versus when it is harmful such as highly write heavy or rapidly changing data. Candidates should understand and compare cache patterns including cache aside, read through, write through, write behind, lazy loading, proactive refresh, and prepopulation. Invalidation and freshness strategies include time to live based expiration, explicit eviction and purge, versioned keys, event driven or messaging based invalidation, background refresh, and cache warming. Discuss consistency and correctness trade offs such as stale reads, race conditions, eventual consistency versus strong consistency, and tactics to maintain correctness including invalidate on write, versioning, conditional updates, and careful ordering of writes. Operational concerns include eviction policies such as least recently used and least frequently used, hot key mitigation, partitioning and sharding of cache data, replication, cache stampede prevention techniques such as request coalescing and locking, fallback to origin and graceful degradation, monitoring and metrics such as hit ratio, eviction rates, and tail latency, alerting and instrumentation, and failure and recovery strategies. At senior levels interviewers may probe distributed cache design, cross layer consistency trade offs, global versus regional content delivery choices, measuring end to end impact on user facing latency and backend load, incident handling, rollbacks and migrations, and operational runbooks.
Technical Innovation and Modernization
Covers leading and executing technical change that raises the engineering bar while preserving operational stability. Topics include identifying and prioritizing innovation opportunities, sponsoring research and experimentation, running proofs of concept and pilots, and introducing new tools or frameworks. Also includes strategies for modernizing legacy systems and architecture with minimal business disruption, managing technical debt, migration planning, rollback and cutover approaches, and maintaining reliability and continuity. Evaluated skills include optimizing performance and cost at scale, establishing engineering standards and best practices, governance and risk management, stakeholder alignment and communication, measuring impact and return on investment, and balancing long term innovation with short term pragmatism.
Full Stack Architecture and Integration
Designing end to end application architecture across presentation, application programming interface layer, business logic, persistence, and infrastructure. Candidates should be able to reason about trade offs across frontend state management, client side processing versus server side work, API contract design, data modeling and database selection, caching strategies, offline and real time update mechanisms, observability and operational concerns, and how infrastructure choices constrain or enable patterns at each layer. Emphasis is on separation of concerns while recognizing when tighter integration is needed for performance, consistency, or reduced latency.