Quantified backend system contributions Questions
Prepare 3-4 specific examples of backend systems you've architected or significantly improved. For each, quantify the impact: scalability improvements (e.g., 'handled 10x traffic growth'), performance wins (e.g., 'reduced p99 latency from 500ms to 50ms'), reliability improvements (e.g., 'achieved 99.99% uptime'), or business impact (e.g., 'unblocked 3 product teams'). Be ready to briefly describe the technical challenge and your role.
EasyTechnical
0 practiced
How would you quantify the business impact of improving reliability from 1 day of downtime per month to 1 hour per month? Describe calculations and evidence you'd present (e.g., lost-revenue estimate, number of affected users, support ticket reduction, brand impact).
HardSystem Design
0 practiced
You must reduce p99 for a distributed cache-backed service serving 10k RPS. Propose architecture and configuration changes: cache size, eviction policy, replication factor, client-side sharding or local caches, and a testing plan to measure a 5x p99 reduction. Also discuss cache stampede protection.
MediumTechnical
0 practiced
You claim a caching change reduced average response time by 60% and increased throughput by 3x. What experiments, metrics, and controls would you show to convince engineers and PMs the effect is real and not an artifact of sampling, warm caches, or traffic differences?
MediumSystem Design
0 practiced
Design an observability plan for a backend service that must support claims like 'reduced p99 by 10x' and 'handled 5x traffic'. List necessary metrics, retention policies, dashboards, alert rules, distributed tracing spans, and how historical data will be stored to validate claims.
EasyTechnical
0 practiced
How do you calculate percent reduction from A to B? Show the calculation converting 500ms to 50ms and explain why you should present both absolute reduction (ms) and relative reduction (%).
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