Define response time, throughput, and concurrency targets based on real user needs and peak scenarios. Specify load profiles, cache strategies, and autoscaling expectations. Tie performance to cost by setting per‑transaction and per‑month budget ceilings with monitoring thresholds. Include test data volumes and warm‑up behaviors so benchmarks reflect reality. Require dashboards that surface latency percentiles and saturation signals. Document graceful degradation strategies for overload conditions. These guardrails prevent surprises, guide architecture choices, and keep finance comfortable as adoption grows and traffic patterns evolve unpredictably.
Describe what personal data is collected, where it flows, how long it is retained, and who can access it. Mandate encryption standards, key management practices, and breach notification timelines. Specify consent flows, data subject rights, and audit requirements relevant to your jurisdictions. Include threat modeling and dependency reviews for vendors and open‑source components. Provide logging requirements that respect privacy while enabling investigations. Align legal, security, and engineering early to avoid costly rework. Clear, measurable controls protect users, accelerate approvals, and strengthen trust with customers and regulators.