API and Full Stack Coding Patterns Questions
Beyond pure algorithms, be prepared for problems that combine algorithmic thinking with API design, rate limiting, caching strategies, or distributed system concepts. Understanding how a coding solution fits into a larger fullstack architecture.
MediumTechnical
0 practiced
Many clients retry using exponential backoff without jitter and are causing synchronized retries that spike load. As an SRE, design a mitigation that reduces retry amplification. Provide client and server-side changes (algorithms), including server guidance headers and a token-bucket approach to handle retries gracefully.
MediumTechnical
0 practiced
How do you propagate W3C trace context through asynchronous queues and third-party webhooks? Specify which headers to carry, how to handle sampling decisions, and what to do when trace headers are missing in incoming messages.
HardTechnical
0 practiced
Design and implement a server-side batching & caching layer for GraphQL resolvers that prevents N+1 DB queries, supports per-request caching, and enforces per-resolver timeouts. Provide Node.js pseudocode using the DataLoader pattern and describe how you would expose caching/invalidation across requests.
HardSystem Design
0 practiced
Design an API gateway for a global service that supports zero-downtime deployments, schema validation, TLS termination, per-route SLOs, and robust observability. Describe deployment patterns (canary, blue/green), multi-AZ/multi-region failover, and safe schema migration steps for validating request/response shapes.
EasyTechnical
0 practiced
Implement a fixed-window rate limiter in Python that enforces at most N requests per window (window in seconds) per user_id. Provide a class RateLimiter with method allow_request(user_id: str, timestamp: int) -> bool. Use in-memory data structures and assume a single-process server. Include comments about time and space complexity and how you would test it.
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