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).
High Availability and Disaster Recovery
Designing systems to remain available and recoverable in the face of infrastructure failures, outages, and disasters. Candidates should be able to define and reason about Recovery Time Objective and Recovery Point Objective targets and translate service level agreement goals such as 99.9 percent to 99.999 percent into architecture choices. Core topics include redundancy strategies such as N plus one and N plus two, active active and active passive deployment patterns, multi availability zone and multi region topologies, and the trade offs between same region high availability and cross region disaster recovery. Discuss load balancing and traffic shaping, redundant load balancer design, and algorithms such as round robin, least connections, and consistent hashing. Explain failover detection, health checks, automated versus manual failover, convergence and recovery timing, and orchestration of failover and reroute. Cover backup, snapshot, and restore strategies, replication and consistency trade offs for stateful components, leader election and split brain mitigation, runbooks and recovery playbooks, disaster recovery testing and drills, and cost and operational trade offs. Include capacity planning, autoscaling, network redundancy, and considerations for security and infrastructure hardening so that identity, key management, and logging remain available and recoverable. Emphasize monitoring, observability, alerting for availability signals, and validation through chaos engineering and regular failover exercises.
System Design for Apple Platforms
Architectural patterns and system design considerations for building software on Apple platforms (iOS, macOS, watchOS, tvOS). Includes architecture styles (MVC, MVVM, VIPER, Clean Architecture), data flow and separation of concerns, offline caching and synchronization, caching strategies, performance optimization, platform constraints, and patterns for scalable, maintainable Apple ecosystem applications.
System Architecture Principles
Core principles and patterns for designing and evaluating high level and system architectures for distributed and cloud based systems. Candidates should understand high availability and redundancy, fault tolerance and graceful degradation, and how to design stateless and stateful components. They should be able to explain scalability and capacity planning strategies including horizontal and vertical scaling, partitioning and sharding, load balancing, caching and replication, and the trade offs involved. The topic covers consistency models and the trade offs between consistency, availability and partition tolerance, performance and latency optimization, reliability and durability, security for data and access control, and cost efficiency. Candidates should be able to discuss fault domains and why critical components are replicated across availability zones and regions, as well as backup, recovery and disaster recovery approaches. Common architectural patterns such as monolithic and microservice architectures, layered design, event driven and message based systems, and command query responsibility segregation are relevant. Monitoring and observability practices including metrics, logging, distributed tracing and alerting are part of assessments, together with the ability to justify architecture decisions based on functional and nonfunctional requirements, constraints, expected load and operational complexity.
Architectural Decision Making
Assess how a candidate thinks through major system and technical decisions, including selecting architectures, technologies, and technical strategies. Expect discussion of evaluation criteria such as performance, reliability, scalability, complexity, cost, development velocity, team capability, maintenance burden, and long term evolution. Candidates should explain specific past decisions with clear articulation of the options considered, trade offs accepted, risk mitigation, observed consequences over time, what they would change with current knowledge, and evidence of nuanced judgment when balancing competing priorities. For senior and staff levels, this includes demonstrating influence across teams when making architecture calls, recognizing organization level costs of choices, and surfacing hidden operational or people costs.
Technical Leadership and Architectural Influence
Demonstrating leadership in technical decisions at the architecture or system level. Candidates should prepare concrete examples where they identified architectural problems, evaluated alternative solutions and trade offs, proposed a preferred design, gained buy in from engineers and stakeholders, and drove implementation. Discuss systems thinking and long term impact on team velocity, code quality, reliability, and product features. Include examples of championing new tools or frameworks, leading migrations or refactors, negotiating trade offs between time to market and technical debt, and occasions when you reversed a decision based on new data. Emphasize communication of complex technical ideas, consensus building with peers, and measurable outcomes.
Lyft ETA & Routing System Architecture
Design and architecture of large-scale ride-hailing ETA and routing systems, covering distributed system design, real-time data processing, routing algorithms, fault tolerance, geo-distributed services, data consistency considerations, and integration with external mapping and traffic data sources.
Fault Tolerance and Failure Scenarios
Designing systems resilient to component failures: timeouts, retries with exponential backoff, circuit breakers, bulkheads. Discuss cascading failure prevention and graceful degradation. At Staff level, demonstrate thinking about multi-layer failures (service failures, database failures, network partitions) and how to detect and recover from them.
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.
Caching and Asynchronous Processing
Design and operational patterns for reducing latency and decoupling components using caching layers and asynchronous communication. For caching, understand when to introduce caches, cache placement, eviction policies, cache coherence, cache invalidation strategies, read through and write through and write behind patterns, cache warming, and trade offs between consistency and freshness. For asynchronous processing and message driven systems, understand producer consumer and publish subscribe patterns, event streaming architectures, common brokers and systems such as Kafka, RabbitMQ, and Amazon Simple Queue Service, and the difference between queues and streams. Be able to reason about delivery semantics including at most once, at least once, and exactly once delivery, and mitigation techniques such as idempotency, deduplication, acknowledgements, retries, and dead letter queues. Know how to handle ordering, partitioning, consumer groups, batching, and throughput tuning. Cover reliability and operational concerns such as backpressure and flow control, rate limiting, monitoring and alerting, failure modes and retry strategies, eventual consistency and how to design for it, and when to choose synchronous versus asynchronous approaches to meet performance, scalability, and correctness goals.