Backend System Design

Backend system design covers the fundamental principles of building scalable, reliable, and high-performance server-side applications.

1. Basic Concepts ✅

In this section, you'll learn the building blocks of backend system design:

• Monolith vs. Microservice Architecture - Comparison of monolithic and microservice architectures
• Request-Response Model - HTTP request-response lifecycle and inter-service communication
• HTTP, REST, gRPC Protocols - API protocol selection and best practices
• Basic Database Concepts - SQL/NoSQL, indexing, normalization
• Basic Data Structures and Algorithms - Algorithm selection in system design context

Content Plan

2. Performance and Scalability ✅

• Load Balancing - Application & Infrastructure level load balancing
• Caching - Distributed caching, cache patterns, and invalidation
• Database Sharding and Partitioning - Horizontal/vertical partitioning, consistent hashing
• Database Replication - Master-slave, multi-master replication, read/write splitting
• Asynchronous Processing & Message Queues - Async patterns with Kafka, RabbitMQ, Redis

3. Reliability & High Availability ✅

• Failover Mechanisms - Automated failover, consensus algorithms
• Circuit Breaker and Bulkhead Pattern - Fault tolerance with Resilience4j
• Health Checks & Heartbeats - Spring Boot Actuator and monitoring
• Backpressure Control - Rate limiting and queue management

4. Consistency Models ✅

• Strong vs Eventual Consistency - Comparison of consistency models
• CAP Theorem - Consistency, Availability, Partition tolerance
• Paxos and Raft Consensus Algorithms - Distributed consensus patterns
• Other Consistency Models - Causal, Sequential, Monotonic consistency

5. API Design and Gateways ✅

• API Versioning - URL, header, query parameter, and annotation-based versioning strategies
• Rate Limiting & Throttling - Redis-based Token Bucket and Sliding Window algorithms
• API Gateway Usage - Spring Cloud Gateway with authentication, circuit breakers, and monitoring
• GraphQL vs REST vs gRPC - Complete comparison with practical Spring Boot implementations

6. Microservice Communication ✅

• Communication Patterns - Synchronous vs Asynchronous communication with Spring Boot
• Service Discovery - Eureka, Consul, Kubernetes native discovery
• Service Mesh - Istio integration with Spring Boot applications

7. Data Processing and Streaming ✅

• Event Sourcing - Event sourcing model and immutable event store
• CQRS (Command Query Responsibility Segregation) - Separating command and query responsibilities
• Stream Processing - Real-time data stream processing

8. Observability ✅

• Logging (ELK Stack) - Structured logging and ELK Stack integration
• Metrics (Prometheus, Grafana) - Application and system metrics collection
• Tracing (Jaeger, Zipkin) - Distributed tracing and performance analysis
• Distributed Tracing - Cross-service correlation and user journey tracking

9. Security ✅

• Authentication vs Authorization - OAuth2, JWT, method-level security
• TLS/SSL & mTLS - Certificate management, HTTPS configuration
• API Security - HMAC, rate limiting, WAF integration
• Secret Management - HashiCorp Vault, encrypted properties

10. Cloud and Container Orchestration ✅

• Containers (Docker) - Containerization, Docker best practices, multi-stage builds
• Kubernetes Basics - Pod, Service, Deployment, ConfigMap, Secret, HPA, RBAC
• Helm Charts - Kubernetes package management, templating, multi-environment deployment
• Serverless and FaaS - AWS Lambda, Azure Functions, Google Cloud Functions, Serverless Framework

11. Site Reliability Engineering ✅

• SLI/SLO/SLA Definitions - Service Level Indicators, Objectives, and Agreements
• Incident Management - Incident response and management processes
• Chaos Engineering - Chaos engineering and resilience testing
• Capacity Planning - Capacity planning and proactive scaling

12. Operations and Cost Management ✅

• Infrastructure as Code - CloudFormation, Terraform infrastructure management and automation
• Cost Monitoring & Optimization - FinOps principles and cost analysis strategies
• CI/CD Workflows - DevOps culture and continuous integration/deployment

13. Edge and Geographically Distributed Systems ✅

• Multi-Region Deployment - Active-Active and Active-Passive deployment strategies
• Data Localization and GDPR - GDPR compliance and data sovereignty requirements
• Edge Computing - Cloudflare Workers, AWS Edge Services, and real-time processing

14. Continuous Improvement ✅

• Feedback Loops - User and system feedback, A/B testing, and telemetry analysis
• Blue/Green and Canary Deployments - Risk-controlled deployment strategies and automated rollback
• Retrospective & Post-Mortem - Organizational learning and continuous improvement methodologies