backend-patterns
affaan-m/ecc
Backend architecture patterns, API design, database optimization, and best practices for Node.js, Express, and Next.js.
What is backend-patterns?
Reference guide for building scalable server-side applications with proven patterns for REST APIs, repository layers, middleware, database optimization, caching, and error handling. Use when designing API endpoints, structuring backend code, optimizing queries, or implementing cross-cutting concerns like authentication and logging.
- RESTful API design with resource-based URLs and query parameters
- Repository and service layer patterns for clean data access abstraction
- Middleware patterns for authentication, logging, and request processing
- Database query optimization including N+1 prevention and indexing strategies
- Caching strategies with Redis and cache-aside patterns
- Centralized error handling and retry logic with exponential backoff
How to install backend-patterns
npx skills add null --skill backend-patternsHow to use backend-patterns
- 1.Review the API Design Patterns section to structure your endpoints with resource-based URLs
- 2.Implement the Repository Pattern to abstract data access logic from business logic
- 3.Create a Service Layer to encapsulate business rules and orchestrate repository calls
- 4.Add Middleware Pattern wrappers for cross-cutting concerns like authentication
- 5.Apply Query Optimization techniques to select only needed columns and avoid N+1 queries
- 6.Implement caching using the Cache-Aside Pattern for frequently accessed data
- 7.Set up centralized error handling with custom ApiError classes and error handler middleware
Use cases
- Designing REST or GraphQL API endpoints for a Node.js/Express application
- Implementing layered architecture with repository, service, and controller separation
- Optimizing slow database queries and preventing N+1 problems in production
- Adding Redis caching to reduce database load on frequently accessed data
- Building authentication middleware for Next.js API routes
- Backend engineers building Node.js or Express APIs
- Full-stack developers working with Next.js API routes
- Architects designing scalable server-side systems
- Teams migrating to layered architecture patterns
backend-patterns FAQ
Use it whenever you want to abstract data access logic from business logic, making it easier to swap databases or add caching layers without changing service code.
Batch fetch related data in a single query and use a Map to join results in memory, rather than looping through records and fetching related data one at a time.
Repository handles data access (CRUD operations), while Service contains business logic and orchestrates multiple repositories or external calls.
No. Cache frequently accessed, slow-to-compute data with stable values. Avoid caching rapidly changing data or sensitive information without proper invalidation strategies.
Use database-native transactions (e.g., Supabase RPC functions) to ensure multiple operations succeed or fail together, with automatic rollback on error.
Full instructions (SKILL.md)
Source of truth, from affaan-m/ecc.
name: backend-patterns description: Backend architecture patterns, API design, database optimization, and server-side best practices for Node.js, Express, and Next.js API routes. metadata: origin: ECC
Backend Development Patterns
Backend architecture patterns and best practices for scalable server-side applications.
When to Activate
- Designing REST or GraphQL API endpoints
- Implementing repository, service, or controller layers
- Optimizing database queries (N+1, indexing, connection pooling)
- Adding caching (Redis, in-memory, HTTP cache headers)
- Setting up background jobs or async processing
- Structuring error handling and validation for APIs
- Building middleware (auth, logging, rate limiting)
API Design Patterns
RESTful API Structure
// PASS: Resource-based URLs
GET /api/markets # List resources
GET /api/markets/:id # Get single resource
POST /api/markets # Create resource
PUT /api/markets/:id # Replace resource
PATCH /api/markets/:id # Update resource
DELETE /api/markets/:id # Delete resource
// PASS: Query parameters for filtering, sorting, pagination
GET /api/markets?status=active&sort=volume&limit=20&offset=0
Repository Pattern
// Abstract data access logic
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
}
// Other methods...
}
Service Layer Pattern
// Business logic separated from data access
class MarketService {
constructor(private marketRepo: MarketRepository) {}
async searchMarkets(query: string, limit: number = 10): Promise<Market[]> {
// Business logic
const embedding = await generateEmbedding(query)
const results = await this.vectorSearch(embedding, limit)
// Fetch full data
const markets = await this.marketRepo.findByIds(results.map(r => r.id))
// Sort by similarity
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) {
// Vector search implementation
}
}
Middleware Pattern
// Request/response processing pipeline
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' })
}
}
}
// Usage
export default withAuth(async (req, res) => {
// Handler has access to req.user
})
Database Patterns
Query Optimization
// PASS: GOOD: Select only needed columns
const { data } = await supabase
.from('markets')
.select('id, name, status, volume')
.eq('status', 'active')
.order('volume', { ascending: false })
.limit(10)
// FAIL: BAD: Select everything
const { data } = await supabase
.from('markets')
.select('*')
N+1 Query Prevention
// FAIL: BAD: N+1 query problem
const markets = await getMarkets()
for (const market of markets) {
market.creator = await getUser(market.creator_id) // N queries
}
// PASS: GOOD: Batch fetch
const markets = await getMarkets()
const creatorIds = markets.map(m => m.creator_id)
const creators = await getUsers(creatorIds) // 1 query
const creatorMap = new Map(creators.map(c => [c.id, c]))
markets.forEach(market => {
market.creator = creatorMap.get(market.creator_id)
})
Transaction Pattern
async function createMarketWithPosition(
marketData: CreateMarketDto,
positionData: CreatePositionDto
) {
// Use Supabase transaction
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
}
// SQL function in Supabase
CREATE OR REPLACE FUNCTION create_market_with_position(
market_data jsonb,
position_data jsonb
)
RETURNS jsonb
LANGUAGE plpgsql
AS $$
BEGIN
-- Start transaction automatically
INSERT INTO markets VALUES (market_data);
INSERT INTO positions VALUES (position_data);
RETURN jsonb_build_object('success', true);
EXCEPTION
WHEN OTHERS THEN
-- Rollback happens automatically
RETURN jsonb_build_object('success', false, 'error', SQLERRM);
END;
$$;
Caching Strategies
Redis Caching Layer
class CachedMarketRepository implements MarketRepository {
constructor(
private baseRepo: MarketRepository,
private redis: RedisClient
) {}
async findById(id: string): Promise<Market | null> {
// Check cache first
const cached = await this.redis.get(`market:${id}`)
if (cached) {
return JSON.parse(cached)
}
// Cache miss - fetch from database
const market = await this.baseRepo.findById(id)
if (market) {
// Cache for 5 minutes
await this.redis.setex(`market:${id}`, 300, JSON.stringify(market))
}
return market
}
async invalidateCache(id: string): Promise<void> {
await this.redis.del(`market:${id}`)
}
}
Cache-Aside Pattern
async function getMarketWithCache(id: string): Promise<Market> {
const cacheKey = `market:${id}`
// Try cache
const cached = await redis.get(cacheKey)
if (cached) return JSON.parse(cached)
// Cache miss - fetch from DB
const market = await db.markets.findUnique({ where: { id } })
if (!market) throw new Error('Market not found')
// Update cache
await redis.setex(cacheKey, 300, JSON.stringify(market))
return market
}
Error Handling Patterns
Centralized Error Handler
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 })
}
// Log unexpected errors
console.error('Unexpected error:', error)
return NextResponse.json({
success: false,
error: 'Internal server error'
}, { status: 500 })
}
// Usage
export async function GET(request: Request) {
try {
const data = await fetchData()
return NextResponse.json({ success: true, data })
} catch (error) {
return errorHandler(error, request)
}
}
Retry with Exponential Backoff
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) {
// Exponential backoff: 1s, 2s, 4s
const delay = Math.pow(2, i) * 1000
await new Promise(resolve => setTimeout(resolve, delay))
}
}
}
throw lastError!
}
// Usage
const data = await fetchWithRetry(() => fetchFromAPI())
Authentication & Authorization
JWT Token Validation
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)
}
// Usage in API route
export async function GET(request: Request) {
const user = await requireAuth(request)
const data = await getDataForUser(user.userId)
return NextResponse.json({ success: true, data })
}
Role-Based Access Control
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)
}
}
}
// Usage - HOF wraps the handler
export const DELETE = requirePermission('delete')(
async (request: Request, user: User) => {
// Handler receives authenticated user with verified permission
return new Response('Deleted', { status: 200 })
}
)
Rate Limiting
Rate limiting must use a shared store such as Redis, a gateway, or the platform's native limiter. Do not use per-process in-memory counters for production APIs: they reset on deploy, split across replicas, and fail open in serverless or multi-instance environments.
Keep the backend layer responsible for choosing the integration point and error
shape; use api-design for the HTTP contract and security-review for abuse
case review.
Background Jobs & Queues
Simple Queue Pattern
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> {
// Job execution logic
}
}
// Usage for indexing markets
interface IndexJob {
marketId: string
}
const indexQueue = new JobQueue<IndexJob>()
export async function POST(request: Request) {
const { marketId } = await request.json()
// Add to queue instead of blocking
await indexQueue.add({ marketId })
return NextResponse.json({ success: true, message: 'Job queued' })
}
Logging & Monitoring
Structured Logging
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()
// Usage
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 })
}
}
Remember: Backend patterns enable scalable, maintainable server-side applications. Choose patterns that fit your complexity level.
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