Started with the happy path and worked backwards, which felt backwards in retrospect.
Start by clarifying the resource and its use case, then walk through the endpoint design, request/response schemas, validation rules, and status codes. Emphasize RESTful principles, idempotency, and error handling, and conclude with trade-offs and scalability considerations.
Pro tip: At Apple, attention to detail and user privacy are paramount; mention how you'd handle sensitive data (e.g., encryption, minimal data exposure) and ensure the API is intuitive and consistent with Apple's design philosophy.
Ask clarifying questions about the resource, its fields, relationships, and expected usage patterns. Define the resource model and identify required vs. optional attributes.
Choose a clear, plural noun for the resource path (e.g., /users) and use POST for creation. Discuss whether to return the created resource or a reference.
Specify the JSON structure for the request body and the response, including field types, formats, and examples. Consider using a standard like JSON:API or HAL for hypermedia.
Outline validation for required fields, data types, formats, and business rules. Describe how to return meaningful error messages with appropriate status codes (e.g., 400, 422).
Choose status codes for success (201 Created with Location header) and errors (400, 401, 403, 409, 500). Discuss idempotency, rate limiting, and versioning strategies.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by explaining the purpose of the Idempotency-Key header: to allow clients to safely retry requests without unintended side effects. Then outline a server-side implementation that stores the key and associated response, and describe how to handle duplicates by returning the stored response or rejecting concurrent requests.
Pro tip: Emphasize the importance of choosing an appropriate scope and expiration for idempotency keys, and discuss how to handle race conditions with atomic operations or locks to prevent duplicate processing.
Clarify that idempotency ensures multiple identical requests have the same effect as a single request, which is crucial for operations like payments or order creation.
Decide where to store idempotency keys and responses, such as a database or cache, with a unique constraint on the key and a TTL for cleanup.
On receiving a request, check if the key exists. If not, process the request, store the key with the response, and return the response. If it exists, return the stored response or an appropriate error.
Use atomic operations (e.g., INSERT ... ON CONFLICT) or distributed locks to prevent race conditions where two requests with the same key are processed simultaneously.
Address scenarios like key expiration, partial failures, and how to handle different response codes (e.g., 409 Conflict for in-progress requests).
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Covered structured logging with request IDs for traceability, sanitizing inputs before they touch any persistence layer, and returning consistent error envelopes rather than leaking stack traces.
Start by outlining a layered defense strategy: validate and sanitize all inputs at the API boundary, handle errors gracefully with consistent error responses, and log comprehensively for observability. Emphasize that these concerns are interconnected and should be designed together, not as afterthoughts. Conclude by discussing how you'd implement and monitor these practices in production, aligning with Apple's high standards for security and reliability.
Pro tip: Show that you think about error handling, logging, and sanitization as part of the API contract and developer experience—not just internal implementation. Mention how you'd document error codes and sanitization rules for consumers, and how you'd use structured logging with correlation IDs to trace requests across services.
Ask about the API's exposure (public vs. internal), data sensitivity, compliance needs (e.g., GDPR, HIPAA), and expected traffic patterns. This shows you tailor solutions to the problem.
Describe a multi-layered approach: schema validation (e.g., JSON Schema, OpenAPI), type checking, whitelisting, and escaping. Mention using established libraries and avoiding custom sanitization where possible.
Explain how you'd catch and categorize errors (client vs. server), return consistent HTTP status codes and error payloads, and avoid leaking sensitive information. Discuss idempotency and retry strategies for transient failures.
Outline structured logging with levels (DEBUG, INFO, WARN, ERROR), correlation IDs, and redaction of sensitive data. Mention integration with monitoring tools (e.g., Prometheus, Grafana) and alerting on error rates.
Describe how you'd test error paths, fuzz inputs, and review logs in staging. Emphasize continuous improvement based on production feedback and security audits.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Went with token-based auth and said authorization should be enforced at the service layer, not just the gateway.
Start by clarifying the context—what type of system (e.g., public API, internal microservices, mobile app backend) and scale—then propose a layered approach: authentication (e.g., OAuth 2.0/OIDC with JWT) and authorization (e.g., RBAC/ABAC) with secure token handling. For rate limiting, discuss algorithms (token bucket, sliding window) and where to enforce (API gateway, service mesh), emphasizing trade-offs like fairness, latency, and distributed coordination.
Pro tip: At Apple, privacy and security are paramount—mention how you'd minimize data collection and use on-device authentication (e.g., Secure Enclave, biometrics) where possible, and ensure rate limiting doesn't leak user information.
Ask about the system's scale, clients (mobile, web, third-party), security/compliance needs (e.g., GDPR, HIPAA), and expected traffic patterns to tailor your answer.
Choose a standard like OAuth 2.0/OIDC for delegated auth, use short-lived JWTs with refresh tokens, and store secrets securely (e.g., Keychain, HSM). Consider multi-factor and biometric options.
Implement RBAC or ABAC based on roles/attributes, enforce least privilege, and centralize policy decisions (e.g., using OPA). Ensure tokens carry necessary claims but avoid sensitive data.
Compare algorithms (token bucket for bursts, sliding window for precision), decide enforcement point (API gateway vs. service), and handle distributed state (e.g., Redis). Define limits per user/IP/API key.
Highlight trade-offs: strict limits vs. user experience, centralized vs. decentralized enforcement, and complexity of distributed rate limiting. Mention logging, alerting, and adaptive limits.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Unit tests on the validation and business logic in isolation, integration tests spinning up the actual service against a test database and hitting the endpoints.
Start by clarifying the API's contract, critical paths, and dependencies, then outline a layered testing strategy: unit tests for isolated logic with mocks, integration tests for real interactions with databases and external services. Emphasize test pyramid principles, tooling choices, and how you'd ensure tests are fast, reliable, and maintainable in CI.
Pro tip: At Apple, reliability and performance are paramount, so highlight how you'd test edge cases, error handling, and concurrency, and mention using contract tests to prevent breaking changes in a microservices environment.
Ask questions to understand the API's endpoints, data models, authentication, and external dependencies. Identify critical user journeys and non-functional requirements like latency and throughput.
Propose a test pyramid: many fast unit tests for business logic, fewer integration tests for component interactions, and a small number of end-to-end tests. Explain what to mock vs. what to test with real dependencies.
Describe how you'd isolate units (functions, classes) using mocks/stubs for dependencies. Cover happy paths, edge cases, error conditions, and boundary values. Mention code coverage goals but focus on meaningful assertions.
Explain how you'd test the API with real databases, message queues, and external services (using test containers or sandbox environments). Include testing of HTTP layer, serialization, authentication, and failure modes.
Discuss integrating tests into CI/CD, ensuring they run quickly and reliably, and handling flaky tests. Mention test data management, parallelization, and monitoring test health.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
This was the part I felt least prepared for.
Start by clarifying the resource and its access patterns, then describe the data model with entities, relationships, and storage choices. Explain concurrency control mechanisms like optimistic locking, transactions, or distributed locks, and justify trade-offs based on consistency, latency, and scale.
Pro tip: Anchor your answer in Apple's values: emphasize user privacy, data integrity, and seamless experience. Mention how you'd handle edge cases like partial failures and ensure idempotency, showing you think beyond the happy path.
Ask about the resource's purpose, expected read/write ratio, consistency needs, and scale. This shows you avoid assumptions and tailor the design.
Describe entities, attributes, relationships, and storage (SQL/NoSQL). Explain indexing and partitioning strategies for performance.
Pinpoint race conditions like lost updates, dirty reads, or write skew. Explain how they could occur in your model.
Select mechanisms: optimistic/pessimistic locking, transactions, versioning, or distributed locks. Justify based on trade-offs.
Cover consistency vs. availability, latency, and failure handling. Mention idempotency, retries, and monitoring.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.