Original practice scenario: A hypothetical streaming player requests sequential video segments from a nearby edge that becomes slow. Design fallback while preserving smooth playback and bounded origin load.
Read model answer +
Use the player buffer and observed segment delivery as decision signals. A fallback strategy should protect playback while avoiding synchronized retries that overwhelm another edge or the origin.
Work through it
Track buffer duration, segment identity and delivery deadlines, distinguishing a missing segment from a transiently slow request and a failed authorization.
Retry idempotent segment requests with bounded concurrency, selecting a compatible alternative location or lower bitrate under an explicit adaptation policy.
Add jitter, circuit-breaking and origin protection, then test edge failure during seeks, network switches and live content with short availability windows.
Tradeoffs to discuss
Aggressive fallback reduces stall risk but can waste bandwidth through duplicate downloads; longer waits preserve bandwidth while consuming buffer.
Common pitfalls
Do not switch to a representation whose segment timeline is incompatible with the current playback position.
A successful HTTP response must still be validated as the expected authorized media segment.
Original practice scenario: A hypothetical entertainment service evaluates a new recommendation row. Several profiles share a household and devices. How would you choose the randomization unit and metrics?
Read model answer +
Choose an assignment unit that matches likely interference. Profile-level randomization can become misleading when shared devices or household members influence each other's viewing.
Work through it
State the target outcome and candidate population, then examine whether household, account or profile assignment offers a credible separation of treatment experiences.
Measure meaningful viewing outcomes and satisfaction proxies with latency and diversity guardrails, retaining unsuccessful recommendations and non-engagement in the denominator.
Estimate uncertainty at the assignment unit and inspect novelty effects and important content or household slices before deciding whether to expand.
Tradeoffs to discuss
Household assignment reduces contamination but lowers the effective sample count; profile assignment offers more units while requiring stronger independence assumptions.
Common pitfalls
Do not treat repeated sessions from one assigned household as independent experimental observations.
A click increase may reflect a distracting presentation rather than better content discovery.
