Backend Patterns logo

Backend Patterns

CommunityPopular
affaan-m
backend-patterns

Patrones de arquitectura backend, diseño de API, optimización de base de datos y buenas prácticas del lado del servidor para Node.js, Express y rutas API de Next.js.

Overview

Publisheraffaan-m
RepositoryECC
Skill namebackend-patterns
Stars
261.1K
Forks
39.1K
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by affaan-m on GitHub. Read the source before you install it.

Installation

Install the Backend Patterns AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/affaan-m/ECC.git /tmp/ECC
mkdir -p .claude/skills
cp -r /tmp/ECC/docs/es/skills/backend-patterns .claude/skills/backend-patterns
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Backend Patterns in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Backend Patterns on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Backend Patterns is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Patrones de Desarrollo Backend

Patrones de arquitectura backend y buenas prácticas para aplicaciones del lado del servidor escalables.

Cuándo Activar

  • Diseñar endpoints de API REST o GraphQL
  • Implementar capas de repositorio, servicio o controlador
  • Optimizar consultas de base de datos (N+1, indexación, connection pooling)
  • Agregar caché (Redis, en memoria, headers de caché HTTP)
  • Configurar trabajos en segundo plano o procesamiento asíncrono
  • Estructurar manejo de errores y validación para APIs
  • Construir middleware (auth, logging, rate limiting)

Patrones de Diseño de API

Estructura de API RESTful

typescript
// PASS: URLs basadas en recursos
GET    /api/markets                 # Listar recursos
GET    /api/markets/:id             # Obtener recurso individual
POST   /api/markets                 # Crear recurso
PUT    /api/markets/:id             # Reemplazar recurso
PATCH  /api/markets/:id             # Actualizar recurso
DELETE /api/markets/:id             # Eliminar recurso

// PASS: Parámetros de consulta para filtrado, ordenamiento, paginación
GET /api/markets?status=active&sort=volume&limit=20&offset=0

Patrón Repository

typescript
// Abstraer la lógica de acceso a datos
interface MarketRepository {
  findAll(filters?: MarketFilters): Promise<Market[]>
  findById(id: string): Promise<Market | null>
  create(data: CreateMarketDto): Promise<Market>
  update(id: string, data: UpdateMarketDto): Promise<Market>
  delete(id: string): Promise<void>
}

class SupabaseMarketRepository implements MarketRepository {
  async findAll(filters?: MarketFilters): Promise<Market[]> {
    let query = supabase.from('markets').select('*')

    if (filters?.status) {
      query = query.eq('status', filters.status)
    }

    if (filters?.limit) {
      query = query.limit(filters.limit)
    }

    const { data, error } = await query

    if (error) throw new Error(error.message)
    return data
  }

  // Otros métodos...
}

Patrón de Capa de Servicio

typescript
// Lógica de negocio separada del acceso a datos
class MarketService {
  constructor(private marketRepo: MarketRepository) {}

  async searchMarkets(query: string, limit: number = 10): Promise<Market[]> {
    // Lógica de negocio
    const embedding = await generateEmbedding(query)
    const results = await this.vectorSearch(embedding, limit)

    // Obtener datos completos
    const markets = await this.marketRepo.findByIds(results.map(r => r.id))

    // Ordenar por similitud
    return markets.sort((a, b) => {
      const scoreA = results.find(r => r.id === a.id)?.score || 0
      const scoreB = results.find(r => r.id === b.id)?.score || 0
      return scoreA - scoreB
    })
  }

  private async vectorSearch(embedding: number[], limit: number) {
    // Implementación de búsqueda vectorial
  }
}

Patrón Middleware

typescript
// Pipeline de procesamiento de request/response
export function withAuth(handler: NextApiHandler): NextApiHandler {
  return async (req, res) => {
    const token = req.headers.authorization?.replace('Bearer ', '')

    if (!token) {
      return res.status(401).json({ error: 'Unauthorized' })
    }

    try {
      const user = await verifyToken(token)
      req.user = user
      return handler(req, res)
    } catch (error) {
      return res.status(401).json({ error: 'Invalid token' })
    }
  }
}

// Uso
export default withAuth(async (req, res) => {
  // El handler tiene acceso a req.user
})

Patrones de Base de Datos

Optimización de Consultas

typescript
// PASS: BIEN: Seleccionar solo las columnas necesarias
const { data } = await supabase
  .from('markets')
  .select('id, name, status, volume')
  .eq('status', 'active')
  .order('volume', { ascending: false })
  .limit(10)

// FAIL: MAL: Seleccionar todo
const { data } = await supabase
  .from('markets')
  .select('*')

Prevención de Problema N+1

typescript
// FAIL: MAL: Problema de consulta N+1
const markets = await getMarkets()
for (const market of markets) {
  market.creator = await getUser(market.creator_id)  // N consultas
}

// PASS: BIEN: Obtención en lote
const markets = await getMarkets()
const creatorIds = markets.map(m => m.creator_id)
const creators = await getUsers(creatorIds)  // 1 consulta
const creatorMap = new Map(creators.map(c => [c.id, c]))

markets.forEach(market => {
  market.creator = creatorMap.get(market.creator_id)
})

Patrón de Transacción

typescript
async function createMarketWithPosition(
  marketData: CreateMarketDto,
  positionData: CreatePositionDto
) {
  // Usar transacción de Supabase
  const { data, error } = await supabase.rpc('create_market_with_position', {
    market_data: marketData,
    position_data: positionData
  })

  if (error) throw new Error('Transaction failed')
  return data
}

// Función SQL en Supabase
CREATE OR REPLACE FUNCTION create_market_with_position(
  market_data jsonb,
  position_data jsonb
)
RETURNS jsonb
LANGUAGE plpgsql
AS $$
BEGIN
  -- La transacción comienza automáticamente
  INSERT INTO markets VALUES (market_data);
  INSERT INTO positions VALUES (position_data);
  RETURN jsonb_build_object('success', true);
EXCEPTION
  WHEN OTHERS THEN
    -- El rollback ocurre automáticamente
    RETURN jsonb_build_object('success', false, 'error', SQLERRM);
END;
$$;

Estrategias de Caché

Capa de Caché con Redis

typescript
class CachedMarketRepository implements MarketRepository {
  constructor(
    private baseRepo: MarketRepository,
    private redis: RedisClient
  ) {}

  async findById(id: string): Promise<Market | null> {
    // Verificar caché primero
    const cached = await this.redis.get(`market:${id}`)

    if (cached) {
      return JSON.parse(cached)
    }

    // Cache miss - obtener de base de datos
    const market = await this.baseRepo.findById(id)

    if (market) {
      // Cachear por 5 minutos
      await this.redis.setex(`market:${id}`, 300, JSON.stringify(market))
    }

    return market
  }

  async invalidateCache(id: string): Promise<void> {
    await this.redis.del(`market:${id}`)
  }
}

Patrón Cache-Aside

typescript
async function getMarketWithCache(id: string): Promise<Market> {
  const cacheKey = `market:${id}`

  // Intentar caché
  const cached = await redis.get(cacheKey)
  if (cached) return JSON.parse(cached)

  // Cache miss - obtener de DB
  const market = await db.markets.findUnique({ where: { id } })

  if (!market) throw new Error('Market not found')

  // Actualizar caché
  await redis.setex(cacheKey, 300, JSON.stringify(market))

  return market
}

Patrones de Manejo de Errores

Manejador de Errores Centralizado

typescript
class ApiError extends Error {
  constructor(
    public statusCode: number,
    public message: string,
    public isOperational = true
  ) {
    super(message)
    Object.setPrototypeOf(this, ApiError.prototype)
  }
}

export function errorHandler(error: unknown, req: Request): Response {
  if (error instanceof ApiError) {
    return NextResponse.json({
      success: false,
      error: error.message
    }, { status: error.statusCode })
  }

  if (error instanceof z.ZodError) {
    return NextResponse.json({
      success: false,
      error: 'Validation failed',
      details: error.errors
    }, { status: 400 })
  }

  // Registrar errores inesperados
  console.error('Unexpected error:', error)

  return NextResponse.json({
    success: false,
    error: 'Internal server error'
  }, { status: 500 })
}

// Uso
export async function GET(request: Request) {
  try {
    const data = await fetchData()
    return NextResponse.json({ success: true, data })
  } catch (error) {
    return errorHandler(error, request)
  }
}

Reintentos con Backoff Exponencial

typescript
async function fetchWithRetry<T>(
  fn: () => Promise<T>,
  maxRetries = 3
): Promise<T> {
  let lastError: Error

  for (let i = 0; i < maxRetries; i++) {
    try {
      return await fn()
    } catch (error) {
      lastError = error as Error

      if (i < maxRetries - 1) {
        // Backoff exponencial: 1s, 2s, 4s
        const delay = Math.pow(2, i) * 1000
        await new Promise(resolve => setTimeout(resolve, delay))
      }
    }
  }

  throw lastError!
}

// Uso
const data = await fetchWithRetry(() => fetchFromAPI())

Autenticación y Autorización

Validación de Token JWT

typescript
import jwt from 'jsonwebtoken'

interface JWTPayload {
  userId: string
  email: string
  role: 'admin' | 'user'
}

export function verifyToken(token: string): JWTPayload {
  try {
    const payload = jwt.verify(token, process.env.JWT_SECRET!) as JWTPayload
    return payload
  } catch (error) {
    throw new ApiError(401, 'Invalid token')
  }
}

export async function requireAuth(request: Request) {
  const token = request.headers.get('authorization')?.replace('Bearer ', '')

  if (!token) {
    throw new ApiError(401, 'Missing authorization token')
  }

  return verifyToken(token)
}

// Uso en ruta API
export async function GET(request: Request) {
  const user = await requireAuth(request)

  const data = await getDataForUser(user.userId)

  return NextResponse.json({ success: true, data })
}

Control de Acceso Basado en Roles

typescript
type Permission = 'read' | 'write' | 'delete' | 'admin'

interface User {
  id: string
  role: 'admin' | 'moderator' | 'user'
}

const rolePermissions: Record<User['role'], Permission[]> = {
  admin: ['read', 'write', 'delete', 'admin'],
  moderator: ['read', 'write', 'delete'],
  user: ['read', 'write']
}

export function hasPermission(user: User, permission: Permission): boolean {
  return rolePermissions[user.role].includes(permission)
}

export function requirePermission(permission: Permission) {
  return (handler: (request: Request, user: User) => Promise<Response>) => {
    return async (request: Request) => {
      const user = await requireAuth(request)

      if (!hasPermission(user, permission)) {
        throw new ApiError(403, 'Insufficient permissions')
      }

      return handler(request, user)
    }
  }
}

// Uso - HOF envuelve el handler
export const DELETE = requirePermission('delete')(
  async (request: Request, user: User) => {
    // El handler recibe el usuario autenticado con permiso verificado
    return new Response('Deleted', { status: 200 })
  }
)

Rate Limiting

El rate limiting debe usar un almacén compartido como Redis, un gateway, o el limitador nativo de la plataforma. No usar contadores en memoria por proceso para APIs de producción: se reinician al desplegarse, se dividen entre réplicas y fallan abiertamente en entornos serverless o multi-instancia.

Mantener la capa backend responsable de elegir el punto de integración y la forma del error; usar api-design para el contrato HTTP y security-review para la revisión de casos de abuso.

Trabajos en Segundo Plano y Colas

Patrón de Cola Simple

typescript
class JobQueue<T> {
  private queue: T[] = []
  private processing = false

  async add(job: T): Promise<void> {
    this.queue.push(job)

    if (!this.processing) {
      this.process()
    }
  }

  private async process(): Promise<void> {
    this.processing = true

    while (this.queue.length > 0) {
      const job = this.queue.shift()!

      try {
        await this.execute(job)
      } catch (error) {
        console.error('Job failed:', error)
      }
    }

    this.processing = false
  }

  private async execute(job: T): Promise<void> {
    // Lógica de ejecución del trabajo
  }
}

// Uso para indexar markets
interface IndexJob {
  marketId: string
}

const indexQueue = new JobQueue<IndexJob>()

export async function POST(request: Request) {
  const { marketId } = await request.json()

  // Agregar a la cola en lugar de bloquear
  await indexQueue.add({ marketId })

  return NextResponse.json({ success: true, message: 'Job queued' })
}

Logging y Monitoreo

Logging Estructurado

typescript
interface LogContext {
  userId?: string
  requestId?: string
  method?: string
  path?: string
  [key: string]: unknown
}

class Logger {
  log(level: 'info' | 'warn' | 'error', message: string, context?: LogContext) {
    const entry = {
      timestamp: new Date().toISOString(),
      level,
      message,
      ...context
    }

    console.log(JSON.stringify(entry))
  }

  info(message: string, context?: LogContext) {
    this.log('info', message, context)
  }

  warn(message: string, context?: LogContext) {
    this.log('warn', message, context)
  }

  error(message: string, error: Error, context?: LogContext) {
    this.log('error', message, {
      ...context,
      error: error.message,
      stack: error.stack
    })
  }
}

const logger = new Logger()

// Uso
export async function GET(request: Request) {
  const requestId = crypto.randomUUID()

  logger.info('Fetching markets', {
    requestId,
    method: 'GET',
    path: '/api/markets'
  })

  try {
    const markets = await fetchMarkets()
    return NextResponse.json({ success: true, data: markets })
  } catch (error) {
    logger.error('Failed to fetch markets', error as Error, { requestId })
    return NextResponse.json({ error: 'Internal error' }, { status: 500 })
  }
}

Recuerda: Los patrones backend permiten aplicaciones del lado del servidor escalables y mantenibles. Elige los patrones que se ajusten a tu nivel de complejidad.

Frequently asked questions

What does the Backend Patterns AI skill do?

Patrones de arquitectura backend, diseño de API, optimización de base de datos y buenas prácticas del lado del servidor para Node.js, Express y rutas API de Next.js.

Why use Backend Patterns on TypingMind?

Because you install it once and use it with any model. Backend Patterns is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Backend Patterns in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/affaan-m/ECC/tree/main/docs/es/skills/backend-patterns. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Backend Patterns?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Backend Patterns?

As many as you like. As long as a model supports skills, you can use Backend Patterns with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Backend Patterns AI skill free?

Yes. It is published on GitHub by affaan-m under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇