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).
Systems Design and Scalability
Focuses on designing scalable distributed systems and marketplace architectures. Topics include core marketplace components such as search and discovery, real time availability, booking and reservation flows, payment processing, and host to guest matching and how those systems interact. Expect to identify scalability bottlenecks, propose caching strategies, database optimization including sharding and replication, horizontal scaling approaches, and reason about consistency versus availability trade offs. Also cover real time synchronization strategies, handling race conditions such as double booking, event driven designs and message based architectures, and considerations for monitoring and operational resilience.
Architecture Decision Documentation and Communication
Covers the practices for capturing, organizing, and communicating architectural decisions and the rationale behind them. Candidates should be able to describe how to create architecture decision records and design documents, record alternatives considered, list pros and cons, and show impacts on scalability, cost, maintainability, security, and operations. This topic also covers techniques for communicating decisions to engineers, product managers, and non technical stakeholders, obtaining buy in, handling feedback and dissent, and evolving documentation as requirements change. Interviewers may probe how candidates link decisions to requirements, trace implications across components, and ensure decisions are discoverable and revisited when assumptions change.
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.
Large Scale System Architecture for Developer Platforms
Practice designing scalable systems that serve thousands or millions of API calls or developer interactions. Understand how to partition the design: API gateway layer, business logic layer, data layer. Discuss scaling strategies: adding replicas, distributing load, isolating traffic types. Know when to add components like caches (Redis), message queues (Kafka), CDNs, and how they affect latency and cost. For developer platforms specifically, consider onboarding experience, quota management, rate limiting, multi-tenancy isolation.
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.
System Design and Architecture
Design large scale reliable systems that meet requirements for scale latency cost and durability. Cover distributed patterns such as publisher subscriber models caching sharding load balancing replication strategies and fault tolerance, trade off analysis among consistency availability and partition tolerance, and selection of storage technologies including relational and nonrelational databases with reasoning about replication and consistency guarantees.
Migration and Modernization Strategy
Covers planning and executing large scale technology transformations such as migrating a monolithic application to microservices, replatforming from on premises to cloud, major framework or database upgrades, and full platform rearchitectures. Includes selection and justification of migration approaches and patterns for different business goals, for example strangler fig, forklift or lift and shift, incremental refactor, big bang replacement, parallel run, and coexistence strategies. Describes phasing and rollout planning to maintain product velocity, sequencing work to maximize business value, and staging and rollback plans to reduce operational and business risk. Addresses data migration planning, validation, consistency and synchronization approaches, testing and verification strategies to minimize downtime and customer impact, and fallback and rollback mechanisms. Covers engineering practices such as deployment automation, continuous integration and continuous delivery, observability and monitoring, and performance and capacity planning. Also includes architectural techniques such as application programming interface wrapping and adapter patterns to enable interoperability between legacy and new systems, governance and compliance considerations, security during migration, cross functional stakeholder communication and coordination, and how to define and measure success through key performance indicators and post migration validation.
Data Consistency and Distributed Transactions
In depth focus on data consistency models and practical approaches to maintaining correctness across distributed components. Covers strong consistency models including linearizability and serializability, causal consistency, eventual consistency, and the implications of each for replication, latency, and user experience. Discusses CAP theorem implications for consistency choices, idempotency, exactly once and at least once semantics, concurrency control and isolation levels, handling race conditions and conflict resolution, and concrete patterns for coordinating updates across services such as two phase commit, three phase commit, and the saga pattern with compensating transactions. Also includes operational challenges like retries, timeouts, ordering, clocks and monotonic timestamps, trade offs between throughput and consistency, and when eventual consistency is acceptable versus when strong consistency is required for correctness (for example financial systems versus social feeds).
Architectural Anti Patterns and Common Pitfalls
Recognize common architectural mistakes: monolithic designs that don't scale, single points of failure, tight coupling, insufficient redundancy, over-engineering, under-engineering. Know why they're problems and how to redesign around them.