backend-development

name	backend-development
description	Master backend API development with Node.js, Python, PHP, Java, C#, GraphQL, REST APIs, databases, and microservices. Learn server-side architecture, authentication, scalability, and production deployment.

Backend Development & API Skills

Quick Start

Backend development creates the server-side logic and APIs that power applications. Start with your language choice and understand HTTP fundamentals.

Node.js/Express API

const express = require('express');
const app = express();

app.use(express.json());

// REST API endpoint
app.get('/api/users/:id', async (req, res) => {
    try {
        const user = await getUser(req.params.id);
        res.json(user);
    } catch (error) {
        res.status(500).json({ error: error.message });
    }
});

app.listen(3000, () => console.log('Server running on :3000'));

Python/FastAPI

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()

class User(BaseModel):
    id: int
    name: str
    email: str

@app.get("/api/users/{user_id}")
async def get_user(user_id: int):
    user = await fetch_user(user_id)
    return user

@app.post("/api/users")
async def create_user(user: User):
    return await save_user(user)

GraphQL Schema

type User {
    id: ID!
    name: String!
    email: String!
    posts: [Post!]!
}

type Query {
    user(id: ID!): User
    users: [User!]!
}

type Mutation {
    createUser(name: String!, email: String!): User
    deleteUser(id: ID!): Boolean
}

Core Topics

1. Language Fundamentals

• Node.js: JavaScript async/await, modules, package management
• Python: Async frameworks, type hints, virtual environments
• PHP: Object-oriented PHP, Laravel framework
• Java: Spring Boot, dependency injection, build tools
• C#: .NET Core, async patterns, LINQ

2. HTTP & REST Principles

• HTTP methods (GET, POST, PUT, DELETE, PATCH)
• Status codes (2xx, 3xx, 4xx, 5xx)
• RESTful API design patterns
• API versioning strategies
• Pagination, filtering, sorting

3. Database Integration

• SQL: Joins, aggregations, optimization
• ORMs: Prisma, SQLAlchemy, Hibernate, Entity Framework
• Database Selection: PostgreSQL vs. MongoDB
• Connection Pooling: Performance optimization
• Migrations: Schema version control

4. Authentication & Authorization

• JWT (JSON Web Tokens): Stateless authentication
• OAuth 2.0: Third-party authentication
• Session Management: Cookie-based authentication
• Role-Based Access Control (RBAC): Permission management
• API Keys: Simple authentication

5. Input Validation & Error Handling

• Request validation schemas
• Sanitization and data cleaning
• Meaningful error responses
• Exception handling patterns
• Security (CSRF, injection prevention)

6. Middleware & Request Pipeline

• Logging and monitoring
• CORS (Cross-Origin Resource Sharing)
• Rate limiting and throttling
• Compression and response optimization
• Request/response transformation

7. Web Frameworks

• Node.js: Express, Fastify, NestJS
• Python: Django, FastAPI, Flask
• PHP: Laravel, Symfony
• Java: Spring Boot, Quarkus
• C#: ASP.NET Core, Blazor

8. GraphQL

• Schema Definition: Types, queries, mutations
• Resolvers: Data fetching and computation
• Subscriptions: Real-time updates
• Federation: Microservices with GraphQL
• DataLoader: N+1 query prevention

9. Scalability & Performance

• Caching: Redis, Memcached strategies
• Database Optimization: Indexing, query analysis
• Load Balancing: Distributing traffic
• Async Processing: Background jobs, message queues
• Horizontal Scaling: Stateless design

10. Deployment & DevOps

• Docker: Containerization
• Kubernetes: Orchestration basics
• CI/CD: Automated testing and deployment
• Monitoring: Logging, metrics, APM
• Cloud Platforms: AWS, GCP, Azure

Learning Path

Month 1-2: Foundations

• Choose programming language
• HTTP and REST principles
• Basic CRUD API development
• SQL fundamentals

Month 3-4: Intermediate

• Framework mastery (Express, Django, FastAPI, Laravel)
• Database design and ORMs
• Authentication and authorization
• API design best practices

Month 5-6: Advanced

• GraphQL implementation
• Microservices architecture
• Caching and performance optimization
• Testing and CI/CD

Month 7+: Professional

• System design and scalability
• Cloud deployment and monitoring
• Event-driven architecture
• Team leadership

Tools & Technologies

Languages & Frameworks

• Node.js: Express, Fastify, NestJS, Hapi
• Python: Django, FastAPI, Flask, Starlette
• PHP: Laravel, Symfony, Slim
• Java: Spring Boot, Quarkus, Micronaut
• Go: Gin, Echo, Standard Library
• C#: ASP.NET Core, minimal APIs

Databases

• SQL: PostgreSQL, MySQL, MariaDB
• NoSQL: MongoDB, Redis, DynamoDB
• Tools: DBeaver, pgAdmin, MongoDB Compass

API Development

• API Testing: Postman, Insomnia, REST Client
• Documentation: Swagger/OpenAPI, GraphQL IDL
• Monitoring: Sentry, DataDog, New Relic

Deployment

• Containerization: Docker, Docker Compose
• Orchestration: Kubernetes, Docker Swarm
• CI/CD: GitHub Actions, Jenkins, GitLab CI
• Cloud: AWS, GCP, Azure, Heroku

Development Tools

• Editors: VS Code, IntelliJ, JetBrains IDEs
• Version Control: Git, GitHub, GitLab
• Package Managers: npm, pip, Composer, Maven

Advanced Topics

Microservices Architecture

• Service Boundary: Identifying bounded contexts (Domain-Driven Design)
• Service Communication: Synchronous (REST, gRPC, HTTP/2) vs. Asynchronous (message queues)
• API Versioning: URL versioning, header versioning, content negotiation
• Service Discovery: Consul, Eureka, DNS-based discovery
• Inter-service Communication: Timeout handling, circuit breakers, retries
• Data Consistency: Saga pattern, event sourcing, eventual consistency
• Distributed Tracing: OpenTelemetry, Jaeger for debugging distributed systems
• Service Mesh: Istio, Linkerd for managing service communication

Message Queue & Asynchronous Processing

• Message Brokers: RabbitMQ, Apache Kafka, AWS SQS
• Publishing/Subscribing: Pub/Sub pattern for decoupled services
• Job Queues: Celery (Python), Bull (Node.js), Delayed Job (Ruby)
• Idempotency: Preventing duplicate processing
• Dead Letter Queues: Handling failed message retries
• Event Sourcing: Storing events instead of state
• CQRS (Command Query Responsibility Segregation): Separating reads and writes

Advanced Authentication & Authorization

• OAuth 2.0 Flows: Authorization Code, Client Credentials, PKCE
• OpenID Connect: Identity layer on top of OAuth 2.0
• Passwordless Auth: WebAuthn, Magic links, Biometrics
• Multi-Factor Authentication (MFA): TOTP, SMS, push notifications
• SAML: Enterprise SSO authentication
• Token Refresh: Handling token expiration and refresh strategies
• API Rate Limiting: Per-user, per-endpoint, sliding window algorithms

Caching Strategies

• HTTP Caching: ETag, Cache-Control, Last-Modified headers
• Application Caching: In-memory caches (Redis, Memcached)
• Database Query Caching: Query result caching, cache invalidation
• Cache Patterns: Cache-aside, write-through, write-behind
• Cache Stampede: When multiple requests request expired cache
• Distributed Caching: Cache coherence across multiple servers
• Cache Warming: Pre-loading frequently accessed data

Database Patterns & Optimization

• Connection Pooling: Preventing resource exhaustion
• Database Partitioning: Sharding, horizontal partitioning
• Read Replicas: Scaling read-heavy workloads
• Query Optimization: EXPLAIN plans, index strategies
• N+1 Query Prevention: Batch loading, DataLoader pattern
• Transaction Management: ACID guarantees, isolation levels
• CDC (Change Data Capture): Capturing database changes

API Design Patterns

• Pagination: Offset-based, cursor-based, keyset pagination
• Filtering: Multiple filter syntax (query params vs. GraphQL)
• Sorting: Multi-field sorting, default sort orders
• Sparse Fieldsets: Allowing clients to request specific fields
• Content Negotiation: Supporting multiple response formats (JSON, XML, etc.)
• HATEOAS: Hypermedia-driven APIs (advanced REST)
• API Throttling: Rate limiting per client
• Backwards Compatibility: API versioning strategies

Testing at Scale

• Unit Testing: Fast, isolated tests (Jest, pytest, unittest)
• Integration Testing: Testing with databases and external services
• Contract Testing: API contract testing between services
• Load Testing: Apache JMeter, Locust, k6
• Chaos Engineering: Simulating failures to test resilience
• Mutation Testing: Verifying test suite quality
• Property-Based Testing: QuickCheck, Hypothesis

Security at Scale

• Input Validation: Schema validation, sanitization
• SQL Injection Prevention: Prepared statements, parameterized queries
• OWASP Top 10: Understanding and preventing common vulnerabilities
• Secrets Management: Vault, AWS Secrets Manager
• API Security: API keys, OAuth, mutual TLS
• HTTPS/TLS: Certificate management, TLS versions
• CORS Security: Origin validation, credential handling
• Dependency Management: Scanning for vulnerable dependencies (Snyk, npm audit)

Observability & Monitoring

• Structured Logging: JSON logs with context, log levels
• Metrics: Application metrics (response time, error rate, throughput)
• Tracing: Distributed tracing with correlation IDs
• Health Checks: Liveness and readiness probes
• Alerting: Setting up meaningful alerts, alerting fatigue
• APM Tools: DataDog, New Relic, Dynatrace
• Log Aggregation: ELK Stack, Splunk, CloudWatch

Deployment & DevOps

• Blue-Green Deployment: Zero-downtime deployments
• Canary Releases: Gradual rollout to users
• Feature Flags: Enabling/disabling features at runtime
• Database Migrations: Handling schema changes safely
• Rollback Strategies: Quick rollback to previous version
• Environment Management: Dev, staging, production consistency
• Infrastructure as Code: Terraform, CloudFormation, Pulumi

Common Pitfalls & Gotchas

1. N+1 Query Problem: Fetching related data in a loop

   -- ❌ Bad: N+1 queries (1 user + N posts)
   SELECT * FROM users WHERE id = 1;
   SELECT * FROM posts WHERE user_id = 1;  -- Called again and again
   
   -- ✅ Good: Single query with join
   SELECT u.*, p.* FROM users u
   LEFT JOIN posts p ON u.id = p.user_id WHERE u.id = 1;
   

2. Unbounded Query Results: Returning millions of records

   • Fix: Implement pagination with reasonable limits
   • Example: LIMIT 100 OFFSET offset

3. Missing Error Handling: Silent failures or generic error messages

   • Fix: Meaningful error messages, proper HTTP status codes
   • Example: 400 for validation error, 409 for conflict, 500 for server error

4. Blocking Operations: Synchronous operations that take time

   • Fix: Use async/await, background jobs, message queues
   • Example: Process file upload asynchronously

5. Stateful Service Design: Assuming server state across requests

   • Fix: Design stateless services for horizontal scaling
   • Example: Store session in Redis, not in-memory

6. Missing Connection Pooling: Creating new DB connections per request

   • Fix: Use connection pools (HikariCP, pgBouncer)
   • Impact: 10-100x performance improvement

7. Inadequate Validation: Trusting client input

   • Fix: Validate on server-side, use schema validation
   • Example: zod, joi, Pydantic for data validation

8. Hardcoded Configuration: API keys, passwords in code

   • Fix: Use environment variables, secrets manager
   • Example: process.env.DATABASE_URL, AWS Secrets Manager

9. Missing Audit Logging: No record of what happened

   • Fix: Log all sensitive operations (login, payment, deletion)
   • Example: User ID, timestamp, action, IP address, result

10. Slow Database Queries: Unoptimized queries impacting user experience

    • Fix: Use EXPLAIN ANALYZE, add indexes, denormalize if needed
    • Benchmark: Every query should complete in < 100ms

Production Deployment Checklist

• API documented (Swagger/OpenAPI)
• Input validation implemented for all endpoints
• Authentication and authorization enforced
• Rate limiting configured
• Error handling with proper status codes
• Logging configured (structured logs)
• Monitoring and alerting set up
• Database optimized and indexed
• Connection pooling configured
• Caching strategy implemented
• API tested (unit, integration, load tests)
• Security audit completed (OWASP Top 10)
• CORS properly configured
• HTTPS/TLS enabled
• CI/CD pipeline in place
• Rollback strategy documented
• Database migration strategy tested
• Backup and disaster recovery plan

Best Practices

1. RESTful Design - Clear resources, proper HTTP methods, status codes
2. Security First - Input validation, authentication, encryption, OWASP compliance
3. Error Handling - Meaningful messages, proper status codes, error tracking
4. Performance - Caching, indexing, query optimization, async processing
5. Documentation - API docs, README, code comments, examples
6. Testing - Unit tests, integration tests, load tests, API tests
7. Monitoring - Structured logging, metrics, tracing, alerting
8. Scalability - Stateless design, horizontal scaling, database optimization
9. Observability - Logs, metrics, traces, health checks
10. DevOps - CI/CD, infrastructure as code, automated deployments

Architecture Patterns

Layered Architecture

api/
├── controllers/    # HTTP request handling
├── services/       # Business logic
├── repositories/   # Data access
├── models/        # Domain models
├── middleware/     # Authentication, logging, error handling
└── utils/         # Helper functions

Clean Code Architecture

src/
├── domain/         # Business entities, use cases
├── application/    # Application logic, DTOs
├── infrastructure/ # Database, external APIs
├── presentation/   # API controllers
└── config/         # Configuration

Performance Optimization Checklist

• Database queries optimized (indexes, joins)
• N+1 queries fixed (use eager loading)
• Caching implemented (Redis for hot data)
• Connection pooling configured
• Async processing for heavy tasks
• Pagination implemented
• Response compression enabled (gzip)
• CDN configured for static assets
• Load testing performed
• Response times monitored

Testing Best Practices

// Good test - tests behavior, not implementation
describe('UserService', () => {
  test('creates user with hashed password', async () => {
    const user = await UserService.create({
      email: '[e-mail]',
      password: 'password123'
    });

    expect(user.email).toBe('[e-mail]');
    expect(user.password).not.toBe('password123'); // Hashed
    expect(user.password).toMatch(/^\$2b\$/); // bcrypt hash
  });
});

// Bad test - tests implementation detail
describe('UserService', () => {
  test('calls bcrypt.hash', async () => {
    const mockHash = jest.spyOn(bcrypt, 'hash');
    await UserService.create(...);
    expect(mockHash).toHaveBeenCalled(); // Implementation detail!
  });
});

API Design Example

// Well-designed API
GET    /api/v1/users                    // List users with pagination
GET    /api/v1/users/:id               // Get single user
POST   /api/v1/users                   // Create user
PATCH  /api/v1/users/:id               // Update user
DELETE /api/v1/users/:id               // Delete user

// Query string examples
GET /api/v1/users?page=1&limit=20&sort=-created_at&role=admin

// Error response example
HTTP 400 Bad Request
{
  "error": {
    "code": "INVALID_EMAIL",
    "message": "Invalid email format",
    "details": { "field": "email" }
  }
}

// Success response example
HTTP 200 OK
{
  "data": { "id": "123", "email": "[e-mail]" },
  "meta": { "timestamp": "2024-01-01T00:00:00Z" }
}

Resources & Learning

Documentation

• REST API Best Practices
• API Design Best Practices
• GraphQL Official Docs
• OWASP API Security

Frameworks & Tools

• Node.js Best Practices
• Python FastAPI
• Django REST Framework
• Spring Boot Docs
• ASP.NET Core

Learning Platforms

• Backend Masters
• System Design Interview
• API Design & Strategy

Keeping Up to Date

• Backend Weekly
• Node Weekly
• Python Weekly
• API Changelog

Interview Preparation

Common Backend Interview Topics

1. Database Design: Normalization, indexing, query optimization
2. REST API Design: Proper HTTP methods, status codes, error handling
3. Authentication: JWT, OAuth 2.0, session management
4. Caching: Redis, cache invalidation, caching strategies
5. Scalability: Horizontal scaling, load balancing, database replication
6. Monitoring: Logging, metrics, alerting
7. Testing: Unit tests, integration tests, mocking
8. System Design: Designing Twitter, Instagram, or similar systems

System Design Interview

• Scalability: How would you handle 1M requests/second?
• Database Selection: When to use SQL vs. NoSQL?
• Caching Strategy: What should be cached? How long?
• Load Balancing: How would you distribute traffic?
• Data Consistency: SQL consistency vs. NoSQL eventual consistency?

Next Steps

1. Master your framework - Node.js/Express, Django, FastAPI, Spring Boot, ASP.NET Core
2. Learn database design - Schema design, indexing, query optimization
3. Study system design - Handling millions of users, distributed systems
4. Implement real-world features - Authentication, caching, rate limiting, payments
5. Focus on testing - Unit tests, integration tests, test coverage
6. Deploy to production - Set up CI/CD, monitoring, alerting
7. Learn microservices - Service communication, data consistency, distributed tracing