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).
Real-Time and Streaming System Design
Designing client-facing, always-on live delivery systems: real-time communication transports (WebSockets, server-sent events, long-polling, WebRTC, MQTT), connection lifecycle and scaling for millions of persistent connections, presence, pub/sub fan-out to online users, chat and notifications, live feeds and tickers, real-time collaboration (CRDT vs OT, offline sync and reconciliation), and live and on-demand video delivery (ingest, transcoding, adaptive bitrate, CDN delivery, low-latency protocols, playback entitlement and content protection). Covers latency budgets, per-client ordering, delivery guarantees across disconnect and reconnect, per-client backpressure, capacity estimation for connection fleets, authentication, authorization, and revocation for real-time channels and premium content, and operational readiness (SLOs and error budgets, observability and incident response, rate limiting, safe rollout, and load and chaos testing) for live-delivery platforms. Data-pipeline stream processing (Kafka or Flink jobs, windowed aggregation, exactly-once pipelines, real-time analytics ingestion) is out of scope.
Caching Strategies and Distributed Caching
Using caches to reduce latency and load: cache-aside, read-through, write-through, and write-behind patterns, TTLs, eviction policies, and distributed caches such as Redis or Memcached. Covers cache invalidation, stampede and thundering-herd protection, and the consistency tradeoffs of caching. Focuses on where and how to cache across tiers.
End-to-End Feature Design and Development
The integrated "build a complete feature" interview format: taking one feature from user-facing flow through API design, backend logic, data model, and storage in a single coherent walkthrough. Tests the ability to connect the layers and make consistent trade-offs across them, rather than depth in any single layer.
Mobile System Architecture and Offline-First Design
Architecting the mobile side of a distributed system: client-server sync, offline-first storage and conflict resolution, background processing, push notifications, and modular mobile architecture at scale. Covers syncing state across intermittent connectivity and designing backends for millions of mobile clients. The mobile-specific slice of distributed design.
Architectural Patterns and Anti-Patterns
Architecture-level patterns and the anti-patterns that signal a wrong turn. Patterns: layered and n-tier architecture, including where cross-cutting concerns like authentication, rate-limiting and tracing belong, dependency injection trade-offs, and thin-versus-fat controller design; hexagonal (ports and adapters) and clean architecture; CQRS and event sourcing; backend-for-frontend; plugin (microkernel) extension models; and the coupling, cohesion, encapsulation and separation-of-concerns principles behind them, including when each applies and what it costs. Anti-patterns: distributed monolith, chatty services, shared-database coupling, cyclic service dependencies, leaky abstractions that expose internal schemas, and golden-hammer pattern adoption. Covers the detection signals (deploy coupling, call-graph fan-out, change amplification, trace evidence), incremental remediation, and architecture governance that keeps smells from recurring. This is about diagnosing and fixing the smell in an existing design, not the monolith-versus-microservices decision itself.
API and Interface Design for Distributed Services
Designing the contracts between services and clients: REST, gRPC, and GraphQL tradeoffs, versioning and backward compatibility, pagination, rate limiting, and idempotent endpoints. Covers request/response modeling, error contracts, and API gateway responsibilities. Focuses on the interface layer that ties distributed components together, not internal data schemas.
System Design Methodology and Trade-off Analysis
The end-to-end approach to an open-ended design problem and the judgment that resolves it: clarifying scope and constraints, gathering functional and non-functional requirements, capacity and back-of-envelope estimation, and mapping requirements to a high-level architecture, then reasoning explicitly about competing options on cost, complexity, latency, and reliability to defend a choice. Covers driving a design interview from ambiguity to a proposal, trade-off frameworks, decision-making under uncertainty and incomplete information, reversible-versus-irreversible decisions, and defending choices under scrutiny. The process-and-judgment skill underneath every system-design case study.
Architecture Documentation and Communication
Making an architecture legible to others: architecture decision records (templates, alternatives and consequences, lifecycle, supersession, tagging and discoverability), diagramming and visualization (C4, sequence, deployment, data-flow and trust-boundary diagrams, notation conventions), and communicating designs to technical and non-technical stakeholders. Covers capturing rationale, documenting what a system does under failure, load and consistency trade-offs, recording observability, SLO and security content, running design reviews, keeping docs and diagrams current, and presenting a system clearly under time pressure. The communication skill that separates a good design from an understood one.
Content Delivery and Edge Networking
Serving content and computation close to users: CDN architecture, edge caching, cache-control and purge strategies, and edge computing versus centralized cloud processing. Covers origin shielding, geo-routing, and the tradeoffs of pushing logic to the edge for latency-sensitive workloads. Application-layer content distribution rather than raw network engineering.