API Design and Integration Questions

Design and evaluate application programming interfaces for external and internal consumption. Topics include resource and schema modeling for RESTful APIs, GraphQL schema and resolver design for diverse clients, and when to choose gRPC style remote procedure calls for high performance internal services. Candidates should address consistent error responses including problem details, pagination and filtering strategies, versioning and deprecation plans, idempotency keys and safe retry semantics, rate limiting headers and status codes, authentication and authorization patterns, contract testing, monitoring and observability, and how to balance backward compatibility with iteration velocity.

MediumTechnical

23 practiced

Design a pagination API for a resource where clients need filtering, multi-column sorting, and consistent results even under concurrent writes. Provide example request query parameters and describe server-side considerations (indexes, stable sort keys, whether to return total counts). Discuss trade-offs between UX and performance.

MediumTechnical

24 practiced

Design an idempotency strategy for a payment API used by partners where network retries and duplicate submissions are common. Include: idempotency key semantics, storage TTL, expected response behavior for duplicate keys, handling of partial failures, and concurrency controls to avoid double-charges.

MediumTechnical

20 practiced

Design a monitoring and observability plan for a suite of REST APIs: list the key metrics, logs, traces, and dashboards you would build; propose SLOs and alerting thresholds; and explain how you would instrument APIs to support debugging of client issues and performance regressions.

EasyTechnical

21 practiced

Compare REST, GraphQL, and gRPC for API design. For each technology describe typical use cases, top architectural trade-offs (performance, client flexibility, caching, versioning, streaming), and recommend which one you would choose for: a public partner API, an internal high-throughput service mesh, and mobile clients with diverse network conditions.

HardTechnical

26 practiced

Design an observability strategy specifically for GraphQL APIs that lets you trace and measure per-operation and per-field latency, detect expensive queries, and implement cost-based or complexity-based rate limiting. Include what instrumentation you would add to resolvers, how to store/query field-level metrics, and how to use this data for developer guidance and throttling.

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