--- title: "System Design & Architecture: Scalability & Resilience" description: "Master system design: scalability, reliability, performance, trade-offs, distributed systems patterns, and architectural decisions for production systems." author: "Mohammad Abu Mattar" canonical: https://mkabumattar.com/quizzes/post/system-design-architecture-quiz --- # System Design & Architecture: Scalability & Resilience Welcome to the System Design & Architecture quiz! Test your knowledge on scalability, reliability, performance, trade-offs, distributed systems patterns, and architectural decisions for production systems. Each question has a timer and hints to guide you. Good luck! ## Questions ### 1. What is scalability in the context of system design? - The ability of a system to handle increased load by adding resources - The measure of how quickly a system responds to an individual request - The percentage of total uptime a system maintains over a given year - The capacity of a system to automatically recover from a node failure **Hint:** Think about handling growth. ### 2. What is latency? - The total time taken for a request to travel from client to server and back - The number of requests a system can process within a specific timeframe - The delay introduced specifically by the database disk-seek operations - The variance in response times over a large set of user requests **Hint:** Think about response time. ### 3. What is throughput? - The volume of work or number of requests processed in a given period - The maximum capacity of a single network link in a distributed cluster - The average time a user spends waiting for a page to load completely - The amount of data stored in a database divided by the number of nodes **Hint:** Think about requests per second. ### 4. What is availability? - The proportion of time a system remains functional and accessible - The ability of a system to remain consistent during a network partition - The total number of concurrent users a system can support at peak - The speed at which a system can reboot after a catastrophic crash **Hint:** Think about uptime. ### 5. What is consistency in distributed systems? - The requirement that all nodes see the same data at the same time - The guarantee that a system will always return a response to every request - The ability of a database to store data in a strictly normalized format - The process of ensuring that all log files are formatted identically **Hint:** Think about data correctness. ### 6. What is partitioning (sharding)? - Dividing a large dataset into smaller chunks across multiple nodes - Creating exact copies of the same data across multiple geographic regions - The process of grouping multiple API requests into a single batch - A technique for hiding private database fields from the public API **Hint:** Think about dividing data. ### 7. What is a single point of failure (SPOF)? - Any component whose failure causes the entire system to stop functioning - A bug in the source code that causes a single request to fail - The primary bottleneck that limits the total throughput of the system - A hardware node that only processes one type of transaction at a time **Hint:** Think about critical dependencies. ### 8. What is eventual consistency? - A model where data will be consistent across all nodes given enough time - A consistency model that guarantees immediate updates to all replicas - A database feature that prevents any data from ever being overwritten - A guarantee that a system will never return a stale read under any load **Hint:** Think about delayed consistency. ### 9. What is CQRS (Command Query Responsibility Segregation)? - An architectural pattern that uses different models for reading and writing data - A protocol for ensuring that every database write is encrypted at rest - A method for merging multiple microservices into a single deployment - A strategy for caching API queries based on the user identity **Hint:** Think about separate read/write. ### 10. What is event sourcing? - A pattern that stores the state of a system as a sequence of immutable events - A technique for triggering serverless functions based on user clicks - A method for logging application errors to a centralized dashboard - A way to automatically generate unit tests from production logs **Hint:** Think about storing events. ### 11. What is rate limiting? - The practice of controlling the rate of requests sent or received by a network - A mechanism that automatically increases server capacity during high traffic - A compression technique used to reduce the size of large API payloads - The process of assigning priorities to different types of database queries **Hint:** Think about controlling traffic. ### 12. What is bulkhead isolation? - A pattern that partitions resources to prevent a failure in one from affecting others - A security strategy that places all database servers behind a secondary firewall - A method for encrypting data as it travels between internal microservices - The practice of storing all backup files on a physical off-site hard drive **Hint:** Think about fault boundaries. ### 13. What is the circuit breaker pattern? - A mechanism to stop requests to a failing service to allow it to recover - A software tool that automatically restarts a server when it runs out of RAM - A design rule that requires every function to have a try-catch block - A load balancing algorithm that redirects traffic to the fastest available node **Hint:** Prevent cascading failures? ### 14. What is the CAP theorem? - The principle that a distributed system can only provide two of three specific guarantees - A law stating that the speed of a system is limited by its slowest component - A requirement that all cloud providers must maintain three copies of user data - The rule that an API must respond within 100ms to be considered "high performance" **Hint:** Consistency, Availability, Partition tolerance trade-offs? ### 15. What is the BASE model? - A model focusing on availability and eventual consistency over strict ACID rules - A set of rules ensuring that every transaction is Atomic, Consistent, Isolated, and Durable - A standard for building APIs that only return data in a binary-serialized format - A database design where all tables are derived from a single "Base" table **Hint:** Basically Available, Soft state, Eventually consistent? ### 16. What is database sharding? - The horizontal partitioning of data across multiple independent database instances - The process of combining small tables into one large table to reduce joins - A method for compressing database indexes to save on-disk storage space - Creating read-only copies of a database to handle high query volume **Hint:** Partition data horizontally? ### 17. What is database denormalization? - Adding redundant data to a schema to improve read performance by avoiding joins - Removing all duplicate fields from a table to ensure data integrity - The process of converting a relational database into a NoSQL document store - A security practice where sensitive data is replaced with random tokens **Hint:** Duplicate data for query performance? ### 18. What is the Cache-Aside strategy? - A pattern where the application code is responsible for managing the cache state - A strategy where the database automatically updates the cache on every write - A method of caching that only stores data for the duration of a single user session - A hardware-level cache that sits directly between the CPU and the system RAM **Hint:** When to populate and flush cache? ### 19. What are Bloom Filters? - A space-efficient probabilistic data structure used to test if an element is in a set - A type of filter used to remove duplicate entries from a distributed log - A specialized algorithm for compressing high-resolution images for the web - A security mechanism that blocks incoming traffic from suspicious IP ranges **Hint:** Probabilistic set membership test? ### 20. What is consistent hashing? - A hashing technique that minimizes key remapping when the number of slots changes - A requirement that all nodes in a cluster use the exact same hashing algorithm - A method for ensuring that a hash value never changes even if the input data changes - A security protocol that verifies the hash of a file before it is executed **Hint:** Distribute cache keys with minimal remapping? ### 21. What is the Saga pattern? - A sequence of local transactions where each updates data and triggers the next - A monolithic database transaction that locks all tables until completion - A storytelling technique used by architects to explain system requirements - A load testing tool that simulates millions of users over a long duration **Hint:** Coordinate multi-service transactions? ### 22. What is the difference between Token Bucket and Leaky Bucket? - Token Bucket allows for bursts of traffic, while Leaky Bucket enforces a steady rate - Leaky Bucket is used for hardware, while Token Bucket is used for software - Token Bucket consumes more memory than Leaky Bucket due to token storage - Leaky Bucket allows for priority-based requests, while Token Bucket does not **Hint:** Control request rate and burst capacity? ### 23. What is Hexagonal Architecture? - A pattern that isolates core logic from external concerns using ports and adapters - A network topology where every server is connected to exactly six other servers - A database schema where every table has exactly six defined relationships - A project management style that organizes developers into six-person squads **Hint:** Core logic isolated from external dependencies? ### 24. What are Bounded Contexts in DDD? - Explicit boundaries within which a specific domain model is defined and applicable - A limit on the number of microservices that can belong to a single team - A technical constraint that prevents a database from growing beyond a certain size - The scope of a single transaction within a relational database system **Hint:** Separate domain models by boundaries? ### 25. What are the three pillars of Observability? - Logs, Metrics, and Traces - Uptime, Latency, and Throughput - Compute, Storage, and Networking - Alerts, Dashboards, and Reports **Hint:** Understand system behavior via three pillars? ### 26. When is a Time-Series Database (TSDB) most appropriate? - For handling massive volumes of timestamped data like metrics or sensor readings - For storing complex relational data with many many-to-many relationships - For managing high-speed transactional data in a banking application - For hosting static assets like images and videos for a global audience **Hint:** High-volume timestamp data patterns? ### 27. What is Semantic Versioning (SemVer)? - A versioning scheme using MAJOR.MINOR.PATCH to signal the nature of changes - A way of naming software versions after famous scientists or cities - A requirement that all API versions must be written in a specific human language - A method for versioning database rows using a timestamp column **Hint:** Breaking changes and backward compatibility? ### 28. What is an idempotency key? - A unique value sent by a client to ensure a request is only processed once - A secret key used to sign API requests for security and authentication - A primary key in a database that is generated using a random number - A key used to compress repetitive data in a JSON payload **Hint:** Prevent double-charging on retries? ### 29. Why is Average Latency often a misleading metric? - It hides outliers (tail latency) that significantly affect user experience - It is mathematically impossible to calculate an average in distributed systems - It requires significantly more CPU power to calculate than the median - It only considers successful requests and ignores all failed ones **Hint:** Why average is misleading? ### 30. What is Distributed Consensus (e.g., Raft)? - An algorithm for achieving agreement on a single data value across a cluster - A method for distributing load equally across all web servers in a region - A legal agreement between cloud providers to share user data in emergencies - A technique for reducing the total size of a distributed database **Hint:** Achieve agreement across replicas?