Implement Backend Development Patterns
Backend Development Patterns provides TypeScript code examples for RESTful APIs, repository pattern, service layers, middleware, database queries, caching
Why it matters
Enhance backend application architecture and scalability by implementing proven design patterns for APIs, data access, service layers, and error handling.
Outcomes
What it gets done
Implement RESTful API structures with resource-based URLs and query parameters.
Apply Repository and Service Layer patterns for clean data access and business logic separation.
Utilize Middleware for request processing, such as authentication.
Optimize database interactions with query optimization, N+1 prevention, and transactions.
Integrate caching strategies like Redis and Cache-Aside.
Implement robust error handling with centralized handlers and retry mechanisms.
Install
Add it to your toolbox
Run in your project directory:
curl -fsSL https://spark.entire.vc/get/ag-cc-skill-backend-patterns | bash Overview
Backend Development Patterns
Code examples demonstrating backend architecture patterns in TypeScript Reference these patterns when implementing API endpoints, data access layers, caching, or error handling in TypeScript backend applications
What it does
Backend Development Patterns provides TypeScript code examples demonstrating API design patterns, data access abstraction through repositories, service layer separation, middleware implementation, database query optimization, caching strategies, transaction handling, and error management. The examples show RESTful endpoint structures, repository interfaces, service classes, middleware functions, query optimization techniques, Redis caching implementations, Supabase transactions, and centralized error handlers.
When to use - and when NOT to
Use these patterns when implementing RESTful API endpoints, abstracting database access with repository interfaces, separating business logic into service layers, adding authentication middleware, optimizing database queries, implementing caching, handling transactions, or standardizing error responses. The examples demonstrate preventing N+1 query problems, implementing cache-aside patterns, and creating reusable middleware.
Do NOT use these patterns for frontend state management or client-side data fetching.
Inputs and outputs
The source material provides TypeScript code examples showing RESTful URL structures, repository interfaces with methods like findAll and findById, service layer implementations with business logic, middleware functions for authentication, query optimization techniques including column selection and batch fetching, Redis caching with TTL, Supabase transaction patterns using RPC functions, and centralized error handlers supporting ApiError and Zod validation errors.
Integrations
The examples demonstrate Supabase database operations including query building with select, eq, limit, and order methods, plus RPC functions for transactions. Redis caching examples show get, setex, and del operations. Next.js API route examples demonstrate middleware wrapping handlers. JWT token verification examples use jwt.verify. Zod error handling examples show z.ZodError integration in error handlers.
Who it's for
Developers implementing backend patterns in TypeScript who need reference examples for API structure, data access layers, caching, and error handling.
// RESTful API Structure
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
// 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
}
}
// N+1 Query Prevention
// 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)
})
Source README
Backend Development Patterns
Backend architecture patterns and best practices for scalable server-side applications.
API Design Patterns
RESTful API Structure
// ✅ 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
// ✅ 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
// ✅ 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)
// ❌ BAD: Select everything
const { data } = await supabase
.from('markets')
.select('*')
N+1 Query Prevention
// ❌ BAD: N+1 query problem
const markets = await getMarkets()
for (const market of markets) {
market.creator = await getUser(market.creator_id) // N queries
}
// ✅ 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 async (request: Request) => {
const user = await requireAuth(request)
if (!hasPermission(user, permission)) {
throw new ApiError(403, 'Insufficient permissions')
}
return user
}
}
// Usage
export const DELETE = requirePermission('delete')(async (request: Request) => {
// Handler with permission check
})
Rate Limiting
Simple In-Memory Rate Limiter
class RateLimiter {
private requests = new Map<string, number[]>()
async checkLimit(
identifier: string,
maxRequests: number,
windowMs: number
): Promise<boolean> {
const now = Date.now()
const requests = this.requests.get(identifier) || []
// Remove old requests outside window
const recentRequests = requests.filter(time => now - time < windowMs)
if (recentRequests.length >= maxRequests) {
return false // Rate limit exceeded
}
// Add current request
recentRequests.push(now)
this.requests.set(identifier, recentRequests)
return true
}
}
const limiter = new RateLimiter()
export async function GET(request: Request) {
const ip = request.headers.get('x-forwarded-for') || 'unknown'
const allowed = await limiter.checkLimit(ip, 100, 60000) // 100 req/min
if (!allowed) {
return NextResponse.json({
error: 'Rate limit exceeded'
}, { status: 429 })
}
// Continue with request
}
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.
When to Use
This skill is applicable to execute the workflow or actions described in the overview.
Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
FAQ
Common questions
Discussion
Questions & comments · 0
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