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.
HardTechnical
0 practiced
Design SLIs, SLOs and an error budget for a backend service where business requires very high availability but budget is constrained. Explain how you would quantify the effect of a reliability engineering change on error-budget consumption and forecast long-term costs versus value.
MediumTechnical
0 practiced
You inherited a legacy service that performs poorly at high concurrency due to serialization bottlenecks. List concrete changes you would consider (algorithmic, data-structure, locking, architecture), explain how each improves concurrency, and describe how you would measure a 5x throughput improvement.
EasyTechnical
0 practiced
List four categories of tooling you would use to measure backend performance (profiler, APM, load-testing, metrics/monitoring). For each category give a concrete tool example and one scenario when that tool is the right choice.
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