Technical Foundation and Self Assessment Questions

Covers baseline technical knowledge and the candidate's ability to honestly assess and communicate their technical strengths and weaknesses. Topics include fundamental infrastructure and networking concepts, operating system and protocol basics, core development and platform concepts relevant to the role, and the candidate's candid self evaluation of their depth in specific technologies. Interviewers use this to calibrate how technical the candidate is expected to be, identify areas for growth, and ensure alignment of expectations between product and engineering for collaboration.

MediumSystem Design

57 practiced

Design a logging and distributed tracing strategy for a microservices application that must support root-cause analysis across dozens of services. Address log formats, correlation IDs, trace sampling rates, storage retention tiers, and cost-control measures that preserve critical observability signals while containing ingest costs.

HardSystem Design

42 practiced

Design a storage and query architecture for an event-sourced system expected to reach petabyte-scale of raw events, where queries commonly request events by time range and event type. Address partitioning, compaction, indexing, hot versus cold storage, retention, and how you would enable efficient replay and projection rebuilds.

MediumTechnical

71 practiced

Enterprise customers require API stability. Propose an API versioning and deprecation strategy that minimizes client disruption. Describe versioning mechanisms (URL/versioned header/content negotiation), deprecation timelines, and how you'd coordinate with large customers who cannot upgrade quickly.

HardTechnical

37 practiced

Explain TLS internals relevant to 0-RTT session resumption (TLS 1.3), including how 0-RTT reduces latency, where replay attacks can occur, and concrete mitigations you would implement if enabling 0-RTT for latency-sensitive IoT devices.

EasyTechnical

35 practiced

Explain how database indexes work at a high level (B-tree versus hash indexes) and how indexing choices affect query performance and write throughput. Provide recommendations for OLTP workloads versus analytical (OLAP) queries when advising a customer about schema and index strategy.

Unlock Full Question Bank

Get access to hundreds of Technical Foundation and Self Assessment interview questions and detailed answers.

Join thousands of developers preparing for their dream job.