Backend

Identity & access Enforce strong auth (OIDC/JWT); short-lived tokens + refresh; audience/issuer checks. Fine-grained authz (RBAC/ABAC); deny-by-default; rate-limit per identity. Input & data Validate/normalize input; reject oversized bodies; JSON schema where possible. Output encode; avoid reflecting raw user data; paginate results. Store secrets in vault/KMS; rotate keys; never log secrets/tokens. Transport & headers TLS everywhere; HSTS; modern ciphers. Security headers: Content-Security-Policy, X-Content-Type-Options=nosniff, X-Frame-Options=DENY, Referrer-Policy. Abuse protection Rate limit + burst control; CAPTCHA/step-up for sensitive actions. Bot detection where relevant; geo/IP allow/deny for admin surfaces. Observability Structured audit logs with identity, action, resource, result; avoid PII spill. Alerts on auth failures, unusual rate spikes, and 5xx anomalies. Checklist AuthZ enforced; least privilege. Input validated; size limits set. TLS + security headers applied. Rate limits + abuse controls configured. Secrets vaulted and rotated.

Core settings max.poll.interval.ms sized to processing time; max.poll.records to batch size. fetch.min.bytes/fetch.max.wait.ms to trade latency vs throughput. enable.auto.commit=false; commit sync/async after processing batch. Concurrency Prefer multiple consumer instances over massive max.poll.records. For CPU-bound steps, hand off to bounded executor; avoid blocking poll thread. Ordering & retries Keep partition affinity when ordering matters; use DLT for poison messages. Backoff with jitter on retries; limit attempts per message. Observability Metrics: lag per partition, commit latency, rebalances, processing time, error rates. Log offsets and partition for errors; trace batch sizes. Checklist Poll loop never blocks; work delegated to bounded pool. Commits after successful processing; DLT in place. Lag and rebalance metrics monitored.

Designing a REST API that is intuitive, maintainable, and scalable requires following established best practices. Here’s a comprehensive guide. 1. Use Nouns, Not Verbs Good GET /users GET /users/123 POST /users PUT /users/123 DELETE /users/123 Bad GET /getUsers GET /getUserById POST /createUser PUT /updateUser DELETE /deleteUser 2. Use Plural Nouns Good GET /users GET /orders GET /products Bad GET /user GET /order GET /product 3. Use HTTP Methods Correctly // GET - Retrieve resources GET /users // Get all users GET /users/123 // Get specific user // POST - Create new resources POST /users // Create new user // PUT - Update entire resource PUT /users/123 // Replace user // PATCH - Partial update PATCH /users/123 // Update specific fields // DELETE - Remove resources DELETE /users/123 // Delete user 4. Use Proper HTTP Status Codes // Success 200 OK // Successful GET, PUT, PATCH 201 Created // Successful POST 204 No Content // Successful DELETE // Client Errors 400 Bad Request // Invalid request 401 Unauthorized // Authentication required 403 Forbidden // Insufficient permissions 404 Not Found // Resource doesn't exist 409 Conflict // Resource conflict // Server Errors 500 Internal Server Error 503 Service Unavailable 5. Consistent Response Format { "data": { "id": 123, "name": "John Doe", "email": "[email protected]" }, "meta": { "timestamp": "2024-11-15T10:00:00Z" } } Error Response Format { "error": { "code": "VALIDATION_ERROR", "message": "Invalid input data", "details": [ { "field": "email", "message": "Invalid email format" } ] } } 6. Versioning URL Versioning /api/v1/users /api/v2/users Header Versioning Accept: application/vnd.api+json;version=1 7. Filtering, Sorting, Pagination GET /users?page=1&limit=20 GET /users?sort=name&order=asc GET /users?status=active&role=admin GET /users?search=john 8. Nested Resources GET /users/123/posts POST /users/123/posts GET /users/123/posts/456 PUT /users/123/posts/456 DELETE /users/123/posts/456 9. Use HTTPS Always use HTTPS in production to encrypt data in transit. ...

Capturing safely Expose /debug/pprof behind auth/VPN; or run curl -sK -H "Authorization: Bearer ...". CPU profile: go tool pprof http://host/debug/pprof/profile?seconds=30. Heap profile: .../heap; Goroutines: .../goroutine?debug=2. For containers: kubectl port-forward then grab profiles; avoid prod CPU throttle when profiling. Reading CPU profiles Look at flat vs. cumulative time; identify hot functions. Flamegraph: go tool pprof -http=:8081 cpu.pprof. Check GC activity and syscalls; watch for mutex contention. Reading heap profiles Compare live allocations vs. in-use objects; watch large []byte and map growth. Look for leaks via rising heap over time; diff profiles between runs. Goroutine dumps Spot leaked goroutines (blocked on channel/lock/I/O). Common culprits: missing cancel, unbounded worker creation, stuck time.After. Best practices Add pprof only when needed in prod; default on in staging. Sample under load close to real traffic. Keep artifacts: store profiles with build SHA + timestamp; compare after releases. Combine with metrics (alloc rate, GC pauses, goroutines) to validate fixes.

Core settings Sliding window (count/time), failure rate threshold, slow-call threshold, minimum calls. Wait duration in open state; half-open permitted calls; automatic transition. Patterns Wrap HTTP/DB/queue clients; combine with timeouts/retries/bulkheads. Tune per dependency; differentiate fast-fail vs. tolerant paths. Provide fallback only when safe/idempotent. Observability Export metrics: state changes, calls/success/failure/slow, not permitted count. Log state transitions; add exemplars linking to traces. Alert on frequent open/half-open oscillation. Checklist Per-downstream breaker with tailored thresholds. Timeouts and retries composed correctly (timeout → breaker → retry). Metrics/logs/traces wired; alerts on open rate.

Database performance is critical for application scalability. Here are proven optimization techniques. 1. Indexing Strategy When to Index -- Index frequently queried columns CREATE INDEX idx_user_email ON users(email); -- Index foreign keys CREATE INDEX idx_post_user_id ON posts(user_id); -- Composite indexes for multi-column queries CREATE INDEX idx_user_status_role ON users(status, role); When NOT to Index Columns with low cardinality (few unique values) Frequently updated columns Small tables (< 1000 rows) 2. Query Optimization Avoid SELECT * -- Bad SELECT * FROM users WHERE id = 123; -- Good SELECT id, name, email FROM users WHERE id = 123; Use LIMIT -- Always limit large result sets SELECT * FROM posts ORDER BY created_at DESC LIMIT 20; Avoid N+1 Queries // Bad: N+1 queries users.forEach(user => { const posts = db.query('SELECT * FROM posts WHERE user_id = ?', [user.id]); }); // Good: Single query with JOIN const usersWithPosts = db.query(` SELECT u.*, p.* FROM users u LEFT JOIN posts p ON u.id = p.user_id `); 3. Connection Pooling // Configure connection pool const pool = mysql.createPool({ connectionLimit: 10, host: 'localhost', user: 'user', password: 'password', database: 'mydb', waitForConnections: true, queueLimit: 0 }); 4. Caching Application-Level Caching // Cache frequently accessed data const cache = new Map(); async function getUser(id) { if (cache.has(id)) { return cache.get(id); } const user = await db.query('SELECT * FROM users WHERE id = ?', [id]); cache.set(id, user); return user; } Query Result Caching -- Use query cache (MySQL) SET GLOBAL query_cache_size = 67108864; SET GLOBAL query_cache_type = 1; 5. Database Schema Optimization Normalize Properly -- Avoid over-normalization -- Balance between normalization and performance Use Appropriate Data Types -- Use smallest appropriate type TINYINT instead of INT for small numbers VARCHAR(255) instead of TEXT when possible DATE instead of DATETIME when time not needed 6. Partitioning -- Partition large tables by date CREATE TABLE logs ( id INT, created_at DATE, data TEXT ) PARTITION BY RANGE (YEAR(created_at)) ( PARTITION p2023 VALUES LESS THAN (2024), PARTITION p2024 VALUES LESS THAN (2025), PARTITION p2025 VALUES LESS THAN (2026) ); 7. Query Analysis EXPLAIN Plan EXPLAIN SELECT * FROM users WHERE email = '[email protected]'; Slow Query Log -- Enable slow query log SET GLOBAL slow_query_log = 'ON'; SET GLOBAL long_query_time = 1; 8. Batch Operations // Bad: Multiple individual inserts users.forEach(user => { db.query('INSERT INTO users (name, email) VALUES (?, ?)', [user.name, user.email]); }); // Good: Batch insert const values = users.map(u => [u.name, u.email]); db.query('INSERT INTO users (name, email) VALUES ?', [values]); 9. Database Maintenance Regular Vacuuming (PostgreSQL) VACUUM ANALYZE; Optimize Tables (MySQL) OPTIMIZE TABLE users; 10. Monitoring Monitor query performance Track slow queries Monitor connection pool usage Watch for table locks Monitor disk I/O Best Practices Index strategically Optimize queries Use connection pooling Implement caching Normalize appropriately Use appropriate data types Partition large tables Analyze query performance Batch operations Regular maintenance Conclusion Database optimization requires: ...

Queue types Prefer quorum queues for HA; classic for transient/high-throughput if loss acceptable. Set durability/persistence appropriately; avoid auto-delete for critical flows. Flow control Enable publisher confirms; set mandatory flag to catch unroutable messages. Use basic.qos to bound unacked messages; prefetch tuned per consumer. Watch memory/flow events; avoid oversized messages—use blob storage for big payloads. Topology & ops Mirror/quorum across AZs; avoid single-node SPOF. Use consistent hash/partitioning for hot-key spreading. Metrics: publish/consume rates, unacked count, queue depth, confirm latency, blocked connections. Checklist Queue type chosen (quorum vs classic) per workload. Publisher confirms + unroutable handling. Prefetch/qos tuned; consumers idempotent. Monitoring/alerts on depth, unacked, flow control.

Choosing between microservices and monolithic architecture is a critical decision. Here’s how to make the right choice. Monolithic Architecture Characteristics Single codebase Single deployment unit Shared database Tightly coupled components Advantages // Simple development // Easy to test // Straightforward deployment // Shared code and data Disadvantages Hard to scale individual components Technology lock-in Deployment risk (all or nothing) Difficult to maintain as it grows Microservices Architecture Characteristics Multiple independent services Separate deployments Service-specific databases Loosely coupled via APIs Advantages Independent scaling Technology diversity Fault isolation Team autonomy Disadvantages Increased complexity Network latency Data consistency challenges Operational overhead When to Choose Monolith Start with Monolith If: Small team (< 10 developers) Simple application Rapid prototyping Limited resources Unclear requirements // Good for startups // MVP development // Small to medium applications When to Choose Microservices Consider Microservices If: Large team (> 50 developers) Complex domain Different scaling needs Multiple teams Clear service boundaries // Good for large organizations // Complex systems // Different technology needs Migration Strategy Strangler Fig Pattern // Gradually replace monolith // Extract services incrementally // Keep monolith running during migration Steps Identify service boundaries Extract one service at a time Maintain backward compatibility Monitor and iterate Best Practices For Monoliths Keep modules loosely coupled Use clear boundaries Plan for future extraction Maintain clean architecture For Microservices Define clear service boundaries Implement proper API contracts Use service mesh for communication Implement distributed tracing Handle failures gracefully Common Pitfalls Microservices Anti-patterns Too many small services Distributed monolith Shared databases Synchronous communication everywhere Monolith Anti-patterns God classes Tight coupling No module boundaries Big ball of mud Conclusion Start with monolith when: ...

Choosing engine Redis: rich data types, persistence, clustering, scripts; good for queues/rate limits. Memcached: simple KV, pure in-memory, fast; great for stateless caches. Design Namespaced keys, versioned; TTL with jitter; avoid giant values. Pick eviction (LRU/LFU); monitor hit rate and evictions. Stampede control: locks/SETNX, stale-while-revalidate, per-key backoff. Ops Pooling + timeouts; alert on latency, evictions, memory fragmentation. For Redis, persistence config (AOF/RDB) matched to durability needs; replicas for HA. For Memcached, spread slabs; watch for evictions of hot slabs. Checklist Engine chosen per use case; durability/HA decided. TTLs + jitter; stampede protection in place. Metrics for hit/miss/evictions/latency.

Security is crucial in web development. Here are essential security practices to protect your applications. 1. Authentication & Authorization Strong Password Policies // Enforce strong passwords const passwordRegex = /^(?=.*[a-z])(?=.*[A-Z])(?=.*\d)(?=.*[@$!%*?&])[A-Za-z\d@$!%*?&]{8,}$/; // Hash passwords (never store plaintext) const hashedPassword = await bcrypt.hash(password, 10); JWT Best Practices // Use short expiration times const token = jwt.sign( { userId: user.id }, process.env.JWT_SECRET, { expiresIn: '15m' } ); // Implement refresh tokens // Store tokens securely (httpOnly cookies) 2. Input Validation Server-Side Validation // Always validate on server const schema = z.object({ email: z.string().email(), password: z.string().min(8), age: z.number().min(18).max(120) }); const validated = schema.parse(req.body); Sanitize Inputs // Prevent XSS const sanitized = DOMPurify.sanitize(userInput); // Prevent SQL Injection (use parameterized queries) db.query('SELECT * FROM users WHERE id = ?', [userId]); 3. HTTPS & SSL/TLS // Always use HTTPS in production // Redirect HTTP to HTTPS // Use HSTS headers app.use((req, res, next) => { if (!req.secure && process.env.NODE_ENV === 'production') { return res.redirect(`https://${req.headers.host}${req.url}`); } next(); }); 4. CORS Configuration // Configure CORS properly app.use(cors({ origin: process.env.ALLOWED_ORIGINS.split(','), credentials: true, methods: ['GET', 'POST', 'PUT', 'DELETE'], allowedHeaders: ['Content-Type', 'Authorization'] })); 5. Rate Limiting // Prevent brute force attacks const rateLimit = require('express-rate-limit'); const limiter = rateLimit({ windowMs: 15 * 60 * 1000, // 15 minutes max: 5 // limit each IP to 5 requests per windowMs }); app.use('/api/login', limiter); 6. SQL Injection Prevention // Always use parameterized queries // Bad db.query(`SELECT * FROM users WHERE email = '${email}'`); // Good db.query('SELECT * FROM users WHERE email = ?', [email]); 7. XSS Prevention // Escape user input const escapeHtml = (text) => { const map = { '&': '&amp;', '<': '&lt;', '>': '&gt;', '"': '&quot;', "'": '&#039;' }; return text.replace(/[&<>"']/g, m => map[m]); }; // Use Content Security Policy app.use((req, res, next) => { res.setHeader('Content-Security-Policy', "default-src 'self'; script-src 'self'"); next(); }); 8. CSRF Protection // Use CSRF tokens const csrf = require('csurf'); const csrfProtection = csrf({ cookie: true }); app.use(csrfProtection); app.get('/form', (req, res) => { res.render('form', { csrfToken: req.csrfToken() }); }); 9. Security Headers // Set security headers app.use((req, res, next) => { res.setHeader('X-Content-Type-Options', 'nosniff'); res.setHeader('X-Frame-Options', 'DENY'); res.setHeader('X-XSS-Protection', '1; mode=block'); res.setHeader('Strict-Transport-Security', 'max-age=31536000'); next(); }); 10. Dependency Security # Regularly update dependencies npm audit npm audit fix # Use tools like Snyk, Dependabot 11. Error Handling // Don't expose sensitive information app.use((err, req, res, next) => { if (process.env.NODE_ENV === 'production') { res.status(500).json({ error: 'Internal server error' }); } else { res.status(500).json({ error: err.message }); } }); 12. Logging & Monitoring // Log security events logger.warn('Failed login attempt', { ip: req.ip, email: req.body.email, timestamp: new Date() }); // Monitor for suspicious activity Best Practices Summary Strong authentication Input validation & sanitization Use HTTPS Configure CORS properly Implement rate limiting Prevent SQL injection Prevent XSS CSRF protection Security headers Keep dependencies updated Proper error handling Monitor security events Conclusion Security requires: ...