How engineering work and technical decisions translate into measurable business outcomes and how to demonstrate that linkage. Topics include mapping architecture choices, reliability, performance improvements and developer productivity initiatives to business metrics such as revenue, customer engagement, time to market, cost reduction and customer satisfaction. Candidates should be able to identify engineering metrics to track including latency, availability, error and incident rates, cycle time and deployment frequency, explain instrumentation strategies to capture signals, design measurement plans and experiments to establish causal impact, and attribute observed changes to specific engineering efforts. This topic also covers communicating technical tradeoffs and impact to nontechnical stakeholders, choosing appropriate granularity for measurement, and describing concrete initiatives with their measurement approach and quantified business impact.
MediumTechnical
0 practiced
You have three tables: metrics(date date, metric_name text, value float), deployments(service text, deployed_at timestamp, commit_hash text), logs(request_id text, service text, level text, timestamp timestamp). Describe a SQL-based approach to detect the date with the largest drop in a KPI and list services that had deployments that day to prioritize root cause investigation. Mention statistical checks you would run to avoid false positives.
MediumSystem Design
0 practiced
Design SLOs and an error budget policy for a multi-tenant platform where tenants have different paid tiers. Describe how you would implement per-tenant SLIs, compute aggregate weighted SLOs for the company, and policies for billing credits or mitigations when a tenant's SLO is violated.
MediumTechnical
0 practiced
A leadership team claims a new IDE plugin will increase developer productivity by 20%. As Solutions Architect, design an instrumentation and measurement approach to validate this ROI across teams, including metrics to collect, rollout strategy, controlling for team differences, and how to attribute impact to the tool versus other factors.
HardSystem Design
0 practiced
Design an end-to-end attribution plan for a multi-month storage-engine migration that touches many services. The goal is to quantify the migration's causal impact on revenue and latency. Describe instrumentation, cohort or holdout design, synthetic control or counterfactual generation, power calculations, rollout strategy, and rollback contingencies.
MediumTechnical
0 practiced
Given two tables events(user_id, event_type, amount, occurred_at) and requests(request_id, user_id, duration_ms, occurred_at), write an SQL query to compute revenue per active user grouped by latency band (0-100ms, 100-500ms, 500ms+). Explain how you handle users with multiple requests and multiple purchase events to avoid double counting.
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