Service Communication and API Design Questions
Design and specify APIs and interservice communication patterns for systems that must scale. Topics include REST design and best practices, API versioning and deprecation strategies, backward compatibility and API evolution, contract design between services, choosing protocols such as gRPC versus HTTP for internal or external communication, security and authentication patterns at the API level, performance and scalability considerations, observability and monitoring of service interactions, and strategies for evolving interfaces without breaking consumers.
EasyTechnical
0 practiced
As a software engineer, explain the core principles of RESTful API design (statelessness, resource identification, uniform interface, layered system, cacheability, code-on-demand). For each principle give a concise example of how it affects endpoint design and one practical trade-off when strictly applying that principle in microservices.
EasyTechnical
0 practiced
Describe common server-side rate limiting algorithms: fixed window, sliding window, token bucket, and leaky bucket. Explain briefly how each affects client behaviour, burst allowance, and memory/storage needs, and propose headers you would return to inform clients about their quota status.
MediumTechnical
0 practiced
Compare gRPC and REST for internal microservice communication. Discuss performance characteristics, code generation, streaming vs unary calls, language interoperability, observability implications, and debugging/troubleshooting trade-offs. When would you favor gRPC over REST and vice versa?
HardTechnical
0 practiced
Set up an API governance model across multiple product teams to improve API quality and consistency. Propose a process that includes API style guides, automated linting and contract checks, a lightweight review board, SLAs for review, deprecation enforcement, and incentive mechanisms to encourage adoption without creating a bottleneck.
EasyTechnical
0 practiced
List best practices for designing error responses in REST APIs. Include example HTTP status codes for common errors, recommended response body fields (for human and machine consumption), and explain how to design errors to enable client retries, diagnostics, and localization.
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