Backend Language Proficiency Questions

Demonstrate strong practical knowledge of a backend programming language such as JavaScript with Node dot js, Python, Java, Go, or similar. Cover language fundamentals, idiomatic usage, standard library features, package and dependency management, common frameworks and ecosystem tools, testing strategies and tooling, error handling and observability, and patterns for maintainable server side code. Be ready to explain concurrency and asynchronous models in the language, performance considerations, security best practices, deployment and packaging approaches, and examples of backend services or APIs you built including trade offs and chosen libraries.

HardTechnical

45 practiced

Write an example in your language that demonstrates zero-copy or reduced-copy techniques for binary data handling (for example, using memoryviews in Python, slices in Go, or Buffer APIs in Node.js) to avoid excessive GC pressure and copying when proxying large responses. Explain when these techniques are appropriate and what pitfalls to watch for.

EasyBehavioral

38 practiced

Code review scenario: A team member wrote code in your language that catches all exceptions and returns a 500 without logging or differentiating error types. As SRE reviewing the change, what feedback would you give? Provide specific code-level suggestions and explain why they improve SLO observability and debugging.

HardSystem Design

43 practiced

Design a language-agnostic approach (and show one example in your language) for safely loading and applying runtime configuration updates to a backend service without restarting. Include atomicity guarantees, validation, and rollback strategy if the new config causes errors.

EasyTechnical

37 practiced

Explain trade-offs between using an embedded language runtime (e.g., Python interpreted code) vs compiling to a native binary (Go) for SRE tooling and critical services. Discuss startup latency, memory footprint, ease of distribution, observability, and safety in crash scenarios.

MediumTechnical

31 practiced

Design a simple rate limiter component in your preferred backend language that can be used in-process for per-user limits (e.g., 100 requests/minute). Implement token-bucket or leaky-bucket algorithm in code and explain how your design would change to support distributed, multi-instance rate limiting with low coordination overhead.

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