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Interview Q&A · 102 questions · 20 answered publicly

FAANG / Big Tech Interview Questions

Ordered by how often they're asked. Sign in free to see every answer, rate your confidence and run timed mock interviews.

  1. Most asked Design a URL shortener like bit.ly.

    Summary

    Clarify read/write ratio, generate unique short codes (hash or base62 counter), store mappings in a DB/KV store, add caching, handle collisions, and discuss analytics and redirects.

    Longer Answer

    Clarify read/write ratio, generate unique short codes (hash or base62 counter), store mappings in a DB/KV store, add caching, handle collisions, and discuss analytics and redirects. Classic system design: uniqueness, scale, and caching.

    Key Points

    • Clarify read/write ratio, generate unique short codes (hash or base62 counter), store mappings in a DB/KV store, add caching, handle collisions, and discuss analytics and redirects
    • Classic system design: uniqueness, scale, and caching
    • Relevant areas: System Design, Urls
    • Use the answer to connect the concept back to a realistic production or interview scenario for 'Design a URL shortener like bit.ly.'

    Comparison / Tradeoffs

    Aspect Notes
    Core idea Clarify read/write ratio, generate unique short codes (hash or base62 counter), store mappings in a DB/KV store, add caching, handle collisions, and discuss analytics and redirects.
    Practical tradeoff Classic system design: uniqueness, scale, and caching.

    Permalink

  2. Most asked Design a news feed / timeline.

    Summary

    Discuss fan-out on write vs read, ranking, caching hot users, denormalized feed stores, and pagination.

    Longer Answer

    Discuss fan-out on write vs read, ranking, caching hot users, denormalized feed stores, and pagination. Cover celebrity problem and eventual consistency.

    Key Points

    • Discuss fan-out on write vs read, ranking, caching hot users, denormalized feed stores, and pagination
    • Cover celebrity problem and eventual consistency
    • Core social feed design trade-offs
    • Use the answer to connect the concept back to a realistic production or interview scenario for 'Design a news feed / timeline.'

    Comparison / Tradeoffs

    Aspect Notes
    Core idea Discuss fan-out on write vs read, ranking, caching hot users, denormalized feed stores, and pagination.
    Practical tradeoff Discuss fan-out on write vs read, ranking, caching hot users, denormalized feed stores, and pagination.

    Permalink

  3. Most asked Design a rate limiter.

    Summary

    Cover token bucket/leaky bucket/sliding window, where to enforce (gateway/service), distributed counters (Redis), and client identification.

    Longer Answer

    Cover token bucket/leaky bucket/sliding window, where to enforce (gateway/service), distributed counters (Redis), and client identification. Common infra design question.

    Key Points

    • Cover token bucket/leaky bucket/sliding window, where to enforce (gateway/service), distributed counters (Redis), and client identification
    • Common infra design question
    • Relevant areas: System Design, Rate Limit
    • Use the answer to connect the concept back to a realistic production or interview scenario for 'Design a rate limiter.'

    Comparison / Tradeoffs

    Aspect Notes
    Core idea Cover token bucket/leaky bucket/sliding window, where to enforce (gateway/service), distributed counters (Redis), and client identification.
    Practical tradeoff Common infra design question.

    Permalink

  4. Most asked Design a chat/messaging system.

    Summary

    Discuss online presence, message delivery, fan-out, storage (recent vs history), push vs pull, and ordering/idempotency.

    Longer Answer

    Discuss online presence, message delivery, fan-out, storage (recent vs history), push vs pull, and ordering/idempotency. Realtime systems fundamentals.

    Key Points

    • Discuss online presence, message delivery, fan-out, storage (recent vs history), push vs pull, and ordering/idempotency
    • Realtime systems fundamentals
    • Relevant areas: System Design, Chat
    • Use the answer to connect the concept back to a realistic production or interview scenario for 'Design a chat/messaging system.'

    Comparison / Tradeoffs

    Aspect Notes
    Core idea Discuss online presence, message delivery, fan-out, storage (recent vs history), push vs pull, and ordering/idempotency.
    Practical tradeoff Discuss online presence, message delivery, fan-out, storage (recent vs history), push vs pull, and ordering/idempotency.

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  5. Most asked Explain CAP theorem and when you choose AP vs CP.

    Summary

    CAP: under partition you trade consistency vs availability.

    Longer Answer

    CAP: under partition you trade consistency vs availability. Choose CP for money/inventory critical paths; AP for feeds/social with reconciliation.

    Key Points

    • CAP: under partition you trade consistency vs availability
    • Choose CP for money/inventory critical paths; AP for feeds/social with reconciliation
    • Foundational distributed systems
    • Use the answer to connect the concept back to a realistic production or interview scenario for 'Explain CAP theorem and when you choose AP vs CP.'

    Comparison / Tradeoffs

    Aspect Notes
    Core idea CAP: under partition you trade consistency vs availability.
    Practical tradeoff CAP: under partition you trade consistency vs availability.

    Permalink

  6. Most asked Walk through time/space complexity of two-sum approaches.

    Summary

    Brute force O(n^2); hash map of complements O(n) time and O(n) space.

    Longer Answer

    Brute force O(n^2); hash map of complements O(n) time and O(n) space. Discuss sorted two-pointer if sorting allowed.

    Key Points

    • Brute force O(n^2); hash map of complements O(n) time and O(n) space
    • Discuss sorted two-pointer if sorting allowed
    • Baseline coding interview
    • Use the answer to connect the concept back to a realistic production or interview scenario for 'Walk through time/space complexity of two-sum approaches.'

    Comparison / Tradeoffs

    Aspect Notes
    Core idea Brute force O(n^2); hash map of complements O(n) time and O(n) space.
    Practical tradeoff Baseline coding interview.

    Permalink

  7. Most asked How do you find the longest substring without repeating characters?

    Summary

    Sliding window with a map of last indices; expand right, shrink left on duplicates; track max length.

    Longer Answer

    Sliding window with a map of last indices; expand right, shrink left on duplicates; track max length. Classic sliding window.

    Key Points

    • Sliding window with a map of last indices; expand right, shrink left on duplicates; track max length
    • Classic sliding window
    • Relevant areas: Dsa, Strings
    • Use the answer to connect the concept back to a realistic production or interview scenario for 'How do you find the longest substring without repeating characters?'

    Comparison / Tradeoffs

    Aspect Notes
    Core idea Sliding window with a map of last indices; expand right, shrink left on duplicates; track max length.
    Practical tradeoff Classic sliding window.

    Permalink

  8. Most asked Explain BFS vs DFS and when to use each.

    Summary

    BFS for shortest path in unweighted graphs/levels; DFS for connectivity, topology, and path existence with lower memory sometimes.

    Longer Answer

    BFS for shortest path in unweighted graphs/levels; DFS for connectivity, topology, and path existence with lower memory sometimes. Graph traversal fundamentals.

    Key Points

    • BFS for shortest path in unweighted graphs/levels; DFS for connectivity, topology, and path existence with lower memory sometimes
    • Graph traversal fundamentals
    • Relevant areas: Dsa, Graphs
    • Use the answer to connect the concept back to a realistic production or interview scenario for 'Explain BFS vs DFS and when to use each.'

    Comparison / Tradeoffs

    Aspect Notes
    Core idea BFS for shortest path in unweighted graphs/levels; DFS for connectivity, topology, and path existence with lower memory sometimes.
    Practical tradeoff Graph traversal fundamentals.

    Permalink

  9. Most asked Explain LRU cache design.

    Summary

    Hash map + doubly linked list (or OrderedDict): O(1) get/put with eviction of least recently used key.

    Longer Answer

    Hash map + doubly linked list (or OrderedDict): O(1) get/put with eviction of least recently used key. Extremely common design+coding hybrid.

    Key Points

    • Hash map + doubly linked list (or OrderedDict): O(1) get/put with eviction of least recently used key
    • Extremely common design+coding hybrid
    • Relevant areas: Dsa, Design
    • Use the answer to connect the concept back to a realistic production or interview scenario for 'Explain LRU cache design.'

    Comparison / Tradeoffs

    Aspect Notes
    Core idea Hash map + doubly linked list (or OrderedDict): O(1) get/put with eviction of least recently used key.
    Practical tradeoff Extremely common design+coding hybrid.

    Permalink

  10. Most asked What is dynamic programming? Give an interview example.

    Summary

    Solve overlapping subproblems with optimal substructure via memoization/tabulation.

    Longer Answer

    Solve overlapping subproblems with optimal substructure via memoization/tabulation. Example: coin change or LIS.

    Key Points

    • Solve overlapping subproblems with optimal substructure via memoization/tabulation
    • Example: coin change or LIS
    • DP definition + signal
    • Use the answer to connect the concept back to a realistic production or interview scenario for 'What is dynamic programming? Give an interview example.'

    Comparison / Tradeoffs

    Aspect Notes
    Core idea Solve overlapping subproblems with optimal substructure via memoization/tabulation.
    Practical tradeoff DP definition + signal.

    Permalink

  11. Most asked Tell me about a time you disagreed with a technical decision.

    Summary

    Use STAR: state the disagreement, data you brought, how you escalated respectfully, and the outcome/learning.

    Longer Answer

    Use STAR: state the disagreement, data you brought, how you escalated respectfully, and the outcome/learning. Behavioral ownership + conflict.

    Key Points

    • Use STAR: state the disagreement, data you brought, how you escalated respectfully, and the outcome/learning
    • Behavioral ownership + conflict
    • Relevant areas: Behavioral
    • Use the answer to connect the concept back to a realistic production or interview scenario for 'Tell me about a time you disagreed with a technical decision.'

    Comparison / Tradeoffs

    Aspect Notes
    Core idea Use STAR: state the disagreement, data you brought, how you escalated respectfully, and the outcome/learning.
    Practical tradeoff Behavioral ownership + conflict.

    Permalink

  12. Most asked Tell me about a time you took ownership of a production issue.

    Summary

    Cover detection, communication, mitigation, root cause, and prevention.

    Longer Answer

    Cover detection, communication, mitigation, root cause, and prevention. Emphasize accountability.

    Key Points

    • Cover detection, communication, mitigation, root cause, and prevention
    • Emphasize accountability
    • Ownership + ops maturity
    • Use the answer to connect the concept back to a realistic production or interview scenario for 'Tell me about a time you took ownership of a production issue.'

    Comparison / Tradeoffs

    Aspect Notes
    Core idea Cover detection, communication, mitigation, root cause, and prevention.
    Practical tradeoff Ownership + ops maturity.

    Permalink

  13. Most asked What happens when you type a URL in a browser?

    Summary

    DNS lookup, TCP/TLS handshake, HTTP request, server processing, response, rendering (HTML/CSS/JS), and caching layers.

    Longer Answer

    DNS lookup, TCP/TLS handshake, HTTP request, server processing, response, rendering (HTML/CSS/JS), and caching layers. Classic full-stack warm-up.

    Key Points

    • DNS lookup, TCP/TLS handshake, HTTP request, server processing, response, rendering (HTML/CSS/JS), and caching layers
    • Classic full-stack warm-up
    • Relevant areas: Networking, Web
    • Use the answer to connect the concept back to a realistic production or interview scenario for 'What happens when you type a URL in a browser?'

    Comparison / Tradeoffs

    Aspect Notes
    Core idea DNS lookup, TCP/TLS handshake, HTTP request, server processing, response, rendering (HTML/CSS/JS), and caching layers.
    Practical tradeoff Classic full-stack warm-up.

    Permalink

  14. Most asked Explain SQL vs NoSQL trade-offs.

    Summary

    SQL: strong schema, joins, ACID.

    Longer Answer

    SQL: strong schema, joins, ACID. NoSQL: flexible models, horizontal scale patterns, varied consistency. Choose based on access patterns.

    Key Points

    • SQL: strong schema, joins, ACID
    • NoSQL: flexible models, horizontal scale patterns, varied consistency
    • Choose based on access patterns
    • Data store selection

    Comparison / Tradeoffs

    Aspect Notes
    Core idea SQL: strong schema, joins, ACID.
    Practical tradeoff Data store selection.

    Permalink

  15. Most asked How would you approach a coding interview if stuck for 5 minutes?

    Summary

    Restate problem, try examples, propose brute force, ask clarifying constraints, then optimize with interviewer guidance.

    Longer Answer

    Restate problem, try examples, propose brute force, ask clarifying constraints, then optimize with interviewer guidance. Meta-skill interviewers evaluate.

    Key Points

    • Restate problem, try examples, propose brute force, ask clarifying constraints, then optimize with interviewer guidance
    • Meta-skill interviewers evaluate
    • Relevant areas: Coding, Process
    • Use the answer to connect the concept back to a realistic production or interview scenario for 'How would you approach a coding interview if stuck for 5 minutes?'

    Comparison / Tradeoffs

    Aspect Notes
    Core idea Restate problem, try examples, propose brute force, ask clarifying constraints, then optimize with interviewer guidance.
    Practical tradeoff Meta-skill interviewers evaluate.

    Permalink

  16. Most asked What is consistent hashing and why use it?

    Summary

    Maps keys and nodes onto a ring so adding/removing nodes moves only a fraction of keys; used for caches and sharded stores.

    Longer Answer

    Maps keys and nodes onto a ring so adding/removing nodes moves only a fraction of keys; used for caches and sharded stores. Scaling storage/cache fleets.

    Key Points

    • Maps keys and nodes onto a ring so adding/removing nodes moves only a fraction of keys; used for caches and sharded stores
    • Scaling storage/cache fleets
    • Relevant areas: Distributed Systems, Hashing
    • Use the answer to connect the concept back to a realistic production or interview scenario for 'What is consistent hashing and why use it?'

    Comparison / Tradeoffs

    Aspect Notes
    Core idea Maps keys and nodes onto a ring so adding/removing nodes moves only a fraction of keys; used for caches and sharded stores.
    Practical tradeoff Scaling storage/cache fleets.

    Permalink

  17. Most asked Explain ACID vs BASE.

    Summary

    ACID: transactional guarantees.

    Longer Answer

    ACID: transactional guarantees. BASE: basically available, soft state, eventual consistency—common in distributed NoSQL.

    Key Points

    • ACID: transactional guarantees
    • BASE: basically available, soft state, eventual consistency—common in distributed NoSQL
    • Consistency vocabulary
    • Use the answer to connect the concept back to a realistic production or interview scenario for 'Explain ACID vs BASE.'

    Comparison / Tradeoffs

    Aspect Notes
    Core idea ACID: transactional guarantees.
    Practical tradeoff Consistency vocabulary.

    Permalink

  18. Most asked What is idempotency in APIs?

    Summary

    Repeating the same request yields the same effect.

    Longer Answer

    Repeating the same request yields the same effect. Use idempotency keys for payments/retries.

    Key Points

    • Repeating the same request yields the same effect
    • Use idempotency keys for payments/retries
    • Reliable distributed APIs
    • Use the answer to connect the concept back to a realistic production or interview scenario for 'What is idempotency in APIs?'

    Comparison / Tradeoffs

    Aspect Notes
    Core idea Repeating the same request yields the same effect.
    Practical tradeoff Reliable distributed APIs.

    Permalink

  19. Most asked Explain microservices vs monolith trade-offs.

    Summary

    Monolith: simpler ops early.

    Longer Answer

    Monolith: simpler ops early. Microservices: independent deploy/scale with higher distributed complexity. Split on clear domain boundaries.

    Key Points

    • Monolith: simpler ops early
    • Microservices: independent deploy/scale with higher distributed complexity
    • Split on clear domain boundaries
    • Architecture judgment

    Comparison / Tradeoffs

    Aspect Notes
    Core idea Monolith: simpler ops early.
    Practical tradeoff Architecture judgment.

    Permalink

  20. Most asked What is a load balancer L4 vs L7?

    Summary

    L4 routes on IP/port; L7 understands HTTP and can route by path/host and terminate TLS.

    Longer Answer

    L4 routes on IP/port; L7 understands HTTP and can route by path/host and terminate TLS. Traffic management.

    Key Points

    • L4 routes on IP/port; L7 understands HTTP and can route by path/host and terminate TLS
    • Traffic management
    • Relevant areas: Networking
    • Use the answer to connect the concept back to a realistic production or interview scenario for 'What is a load balancer L4 vs L7?'

    Comparison / Tradeoffs

    Aspect Notes
    Core idea L4 routes on IP/port; L7 understands HTTP and can route by path/host and terminate TLS.
    Practical tradeoff Traffic management.

    Permalink

  21. Design a distributed cache.
  22. Describe a time you delivered under ambiguity.
  23. Give an example of customer obsession (Amazon LP).
  24. How do indexes work and when do they hurt?
  25. Design a key-value store.
  26. Tell me about a time you improved performance.
  27. Design Apple's Find My network at a high level.
  28. How would you design iMessage delivery and encryption?
  29. Design a photo library sync service like iCloud Photos.
  30. Design a push notification system for mobile apps.
  31. What is the CAP theorem and how do you apply it in practice?
  32. Explain consistent hashing and why it matters for caches.
  33. Design a video streaming CDN architecture.
  34. Design YouTube / video streaming at a high level.
  35. Design a ride-sharing matching system.
  36. How would you design autocomplete / typeahead?
  37. Design a notification system.
  38. Explain eventual consistency with an example.
  39. How do you detect a cycle in a linked list?
  40. Describe merge intervals.
  41. How do you serialize/deserialize a binary tree?
  42. How do you find median from a data stream?
  43. How do you topologically sort a graph?
  44. Describe diving deep into a metric that looked wrong.
  45. Tell me about inventing and simplifying a process.
  46. How do you earn trust with a cross-functional partner?
  47. Describe a time you had to say no to a stakeholder.
  48. Tell me about mentoring someone.
  49. What is Googleyness to you?
  50. How do you handle bias for action vs needing more data?
  51. Explain HTTP vs HTTPS and TLS briefly.
  52. How do you design for multi-region?
  53. What is a CDN and when do you need one?
  54. How do you observe a production service?
  55. Describe a cross-team project you led.
  56. How do you prioritize a backlog under pressure?
  57. How would you A/B test a ranking change?
  58. Design a search autocomplete backend for Amazon product search.
  59. What is a good behavioral example for Meta's Move Fast?
  60. How do you secure secrets in cloud apps?
  61. How would you estimate storage for a messaging app?
  62. What metrics define a healthy API?
  63. Design a distributed job queue.
  64. What questions would you ask your interviewers at FAANG?
  65. Explain App Store review and content distribution challenges.
  66. How do you design on-device ML inference with cloud fallback?
  67. Compare optimistic vs pessimistic locking in concurrent edits.
  68. How would you design a feature store for ML models?
  69. Design a distributed lock service.
  70. Explain how you would A/B test a ranking change safely.
  71. Design a searchable encrypted document store for consumer backups.
  72. How do you debug intermittent production latency spikes?
  73. Design an API gateway for a large microservices fleet.
  74. Design a real-time collaborative document editor.
  75. How would you migrate a monolith to services without downtime?
  76. Design a content moderation pipeline for user uploads.
  77. How do you secure secrets in a large engineering org?
  78. Design a metrics and alerting platform.
  79. What tradeoffs exist between SQL and NoSQL for a shopping cart?
  80. How would you interview-design a battery-efficient background sync?
  81. Design Uber-style surge pricing / marketplace matching at high level.
  82. How do you detect and resolve split-brain?
  83. Explain quickselect for kth largest.
  84. How would you design an API for a parking garage?
  85. Explain optimistic vs pessimistic locking.
  86. Explain container orchestration basics (Kubernetes).
  87. How do you handle hot keys in a cache?
  88. Explain OAuth2 authorization code flow briefly.
  89. What privacy considerations matter for mobile apps?
  90. Explain MapReduce at a high level.
  91. What is backpressure in streaming systems?
  92. How does Netflix think about chaos engineering?
  93. Explain Apple's emphasis on craftsmanship in interviews.
  94. Compare REST and gRPC for internal services.
  95. Explain blue/green vs canary deployments.
  96. Tell me about a time you gave critical feedback.
  97. How do you prepare for a bar-raiser interview?
  98. Explain pagination strategies (offset vs cursor).
  99. What is feature flagging and why use it?
  100. How do you approach object-oriented design for an elevator system?
  101. Explain garbage collection at a high level.
  102. Explain bloom filters and a production use case.