Menú
Plan infrastructure capacity for expected load. Use when sizing systems, planning for growth, or analyzing resource requirements. Covers load estimation and resource sizing.
Basado en la clasificación ocupacional SOC
Biome 2.x linting and formatting patterns. Use when configuring code quality tools, setting up linting rules, formatting code, or integrating with CI/CD. Covers migration from ESLint/Prettier.
Hono 4.x web framework patterns. Use when building APIs, middleware, routing, or server-side applications. Covers multi-runtime support (Node, Bun, Cloudflare Workers), validation, CORS, and error handling.
Radix UI primitive patterns. Use when building accessible, unstyled UI components like dialogs, dropdowns, tooltips, tabs, and selects. Covers Tailwind styling, keyboard navigation, animations, and portal management.
React development patterns. Use when building React components, managing state, creating custom hooks, or optimizing React applications. Covers React 19 features, TypeScript integration, and composition patterns.
Tailwind CSS 4.x utility-first styling patterns. Use when building UI components, creating responsive layouts, implementing design systems, or customizing themes. Covers CSS-first configuration, @theme directive, and component patterns.
Vite 7.x build tool patterns. Use when configuring build setup, development server, environment variables, asset handling, or optimizing production builds for React applications.
| name | capacity-planning |
| description | Plan infrastructure capacity for expected load. Use when sizing systems, planning for growth, or analyzing resource requirements. Covers load estimation and resource sizing. |
L = λ × W
L = Average number of items in system
λ = Average arrival rate
W = Average time in system
Given:
- 1000 requests/second
- 100ms average response time
Required concurrent connections:
L = 1000 × 0.1 = 100 concurrent connections
connections = (requests_per_second × avg_query_time) × 1.5
memory = (concurrent_users × memory_per_user) + base_overhead
cores = (peak_rps × cpu_time_per_request) / target_utilization