Estimate the infrastructure or operational load needed to support a major Billing launch

Problem Statement Description

Product context: Stripe is financial infrastructure for internet businesses; its products include payments, Checkout, Billing, Connect, Radar, Issuing, Terminal, and tax tools.

Stripe is preparing for a major Billing launch that could materially increase subscription, invoicing, payment retry, tax, entitlement, webhook, support, and risk-review activity across merchants. You are asked to estimate the infrastructure and operational load required to support the launch, with enough rigor to inform capacity planning, staffing, launch readiness, and risk mitigation.

Frame the estimate from the perspective of Stripe Billing serving businesses that rely on recurring revenue and global payments reliability. The launch may affect both machine load, such as API requests, invoice generation, payment attempts, webhooks, fraud/risk checks, data writes, and reconciliation jobs, and human or operational load, such as support tickets, risk investigations, merchant onboarding reviews, incident response, and compliance escalations.

This is a guesstimate exercise, not a systems design deep dive. You should define the scope, identify the main demand drivers, choose reasonable assumptions, build a transparent estimation model, and explain which assumptions most affect the result.

The experience should consider:

- The launch scope: target merchant segment, expected adoption curve, geographies, pricing plans, and whether usage is from new merchants, existing Billing users, or migration from competitors.

- The primary unit of load: merchants, subscriptions, invoices, payment attempts, API calls, webhooks, risk reviews, support contacts, or infrastructure capacity.

- Population and frequency assumptions: number of merchants, customers per merchant, billing cycles, retry behavior, invoice events, and peak-versus-average usage.

- Operational multipliers: failed payments, fraud/risk flags, disputes, tax/compliance cases, onboarding checks, and support ticket rates.

- Infrastructure dimensions: compute, database writes, queues, background jobs, webhook delivery, observability, and regional or peak-time capacity buffers.

- Cohorts and sensitivity: SMB versus enterprise merchants, domestic versus international billing, high-risk versus low-risk industries, and launch-day versus steady-state load.

- Sanity checks: comparison to current Billing scale, expected merchant growth, competitor benchmarks where relevant, and whether the final estimate is directionally plausible.

- Launch risk factors: reliability requirements, financial correctness, customer trust, incident handling, and the cost of underestimating demand.

Your goal is to produce a structured, defensible estimate that Stripe leadership could use to decide whether the Billing launch is operationally ready, what capacity or staffing gaps may exist, and which assumptions should be validated before launch.