This repository documents a comprehensive learning path from monolithic applications to distributed system design. The goal is to understand the principles, patterns, and trade-offs involved in building scalable, resilient systems.
Background: Experienced with complex monolithic applications
Goal: Master distributed system design and modern architecture patterns
Approach: Theory + Practice with hands-on implementations
This project contains extensive educational reference documents in multiple locations. These files are comprehensive learning materials (~625 KB total) that should NOT be read automatically to conserve tokens.
docs/fundamentals/
- Phase 1 foundations (119 KB, 4 hours reading)docs/phase2-architecture-patterns/
- Phase 2 patterns (121 KB, 4.5 hours reading)docs/phase3-scalability-performance/
- Phase 3 scalability (50 KB, 2 hours reading)docs/phase4-data-management/
- Phase 4 data management (40 KB, 2 hours reading)docs/phase5-reliability-resilience/
- Phase 5 reliability (50 KB, 2 hours reading)docs/phase6-observability-monitoring/
- Phase 6 observability (50 KB, 2 hours reading)docs/phase7-security-identity/
- Phase 7 security (45 KB, 2 hours reading)docs/phase8-deployment-devops/
- Phase 8 deployment (40 KB, 1.5 hours reading)docs/phase9-real-world-systems/
- Phase 9 case studies (50 KB, 2 hours reading)docs/phase10-advanced-topics/
- Phase 10 advanced (40 KB, 1.5 hours reading)ecommerce-microservices/docs/
- Practical implementation guides
DO NOT:
- Automatically scan or read files in
docs/fundamentals/
- Automatically scan or read files in
docs/phase2-architecture-patterns/
- Automatically scan or read files in
docs/phase3-scalability-performance/
- Automatically scan or read files in
docs/phase4-data-management/
- Automatically scan or read files in
docs/phase5-reliability-resilience/
- Automatically scan or read files in
docs/phase6-observability-monitoring/
- Automatically scan or read files in
docs/phase7-security-identity/
- Automatically scan or read files in
docs/phase8-deployment-devops/
- Automatically scan or read files in
docs/phase9-real-world-systems/
- Automatically scan or read files in
docs/phase10-advanced-topics/
- Automatically scan or read files in
ecommerce-microservices/docs/
- Load these files into context unless explicitly needed
- Include them in exploratory file reads
ONLY read these files when:
- User explicitly asks about a topic covered in the docs
- User directly references a specific doc file
- The current task is directly related to the concepts explained
- User asks to explain a specific pattern or concept
How to decide if relevant:
- First, check the relevant INDEX file:
docs/fundamentals/INDEX.md
- For Phase 1 topicsdocs/phase2-architecture-patterns/INDEX.md
- For Phase 2 topicsdocs/phase3-scalability-performance/INDEX.md
- For Phase 3 topicsdocs/phase4-data-management/INDEX.md
- For Phase 4 topicsdocs/phase5-reliability-resilience/INDEX.md
- For Phase 5 topicsdocs/phase6-observability-monitoring/INDEX.md
- For Phase 6 topicsdocs/phase7-security-identity/INDEX.md
- For Phase 7 topicsdocs/phase8-deployment-devops/INDEX.md
- For Phase 8 topicsdocs/phase9-real-world-systems/INDEX.md
- For Phase 9 topicsdocs/phase10-advanced-topics/INDEX.md
- For Phase 10 topicsecommerce-microservices/docs/INDEX.md
- For practical guides
- Read the brief description in the INDEX
- Only open the full document if it directly answers the user's question
- Read only the specific section needed, not the entire document
Total: 119 KB across 3 documents + INDEX
-
Monolith Limitations (~26 KB)
- Scalability bottlenecks, deployment risks, technology lock-in, team coordination
-
Distributed Systems Fundamentals (~50 KB)
- CAP Theorem, ACID vs BASE, Network Fallacies, Consistency Models
-
System Design Principles (~43 KB)
- Separation of Concerns, Single Responsibility, Loose Coupling/High Cohesion, Design for Failure
Total: 121 KB across 3 documents + INDEX
-
Microservices Architecture (~40 KB)
- Service boundaries, communication patterns, service mesh, API Gateway
-
Event-Driven Architecture (~43 KB)
- Event sourcing, CQRS, event streaming vs messaging, Saga pattern
-
Architectural Patterns (~38 KB)
- Layered, Hexagonal, Clean Architecture, Strangler Fig pattern
Total: 50 KB (1 comprehensive document + INDEX)
- Scalability & Performance (~50 KB)
- Caching strategies (cache-aside, write-through, CDN, Redis patterns)
- Load balancing (L4 vs L7, algorithms, health checks, circuit breakers)
- Database scaling (read replicas, sharding, connection pooling)
- Performance optimization (async processing, denormalization)
Total: 40 KB (1 comprehensive document + INDEX)
- Data Management (~40 KB)
- Database types (Relational, Document, Key-Value, Column-Family, Graph, Time-Series)
- Polyglot persistence strategy
- Data consistency patterns (Two-Phase Commit, Saga, Idempotency)
- Data replication (Master-slave, Multi-master, Quorum-based)
Total: 50 KB (1 comprehensive document + INDEX)
- Reliability & Resilience (~50 KB)
- Fault tolerance patterns (Circuit breaker, Bulkhead, Retry, Timeout, Fallback)
- High availability (Redundancy, health checks, SLAs/SLOs/SLIs, error budgets)
- Chaos engineering (Principles, experiments, Chaos Monkey, Gremlin, Chaos Mesh)
Total: 50 KB (1 comprehensive document + INDEX)
- Observability & Monitoring (~50 KB)
- Three pillars (Metrics, Logs, Traces)
- Monitoring methods (RED, USE, Golden Signals)
- Tools (Prometheus, Grafana, ELK, OpenTelemetry, Jaeger)
- Alerting (Design principles, on-call practices, runbooks)
Total: 45 KB (1 comprehensive document + INDEX)
- Security & Identity (~45 KB)
- Authentication (JWT, sessions, OAuth 2.0, mTLS)
- Authorization (RBAC)
- Secrets management (HashiCorp Vault, key rotation)
- API security (Rate limiting, input validation, CORS, SQL injection prevention)
- Zero Trust Architecture
Total: 40 KB (1 comprehensive document + INDEX)
- Deployment & DevOps (~40 KB)
- Containerization (Docker, multi-stage builds, Docker Compose)
- Kubernetes (Deployments, Services, Ingress, HPA, ConfigMaps, Secrets)
- CI/CD (GitHub Actions, GitLab CI)
- Deployment strategies (Rolling update, blue-green, canary)
- Infrastructure as Code (Terraform, Helm)
Total: 50 KB (1 comprehensive document + INDEX)
- Real-World Systems (~50 KB)
- URL Shortener (Base62 encoding, caching, analytics)
- Social Media Feed (Hybrid fan-out strategy)
- Video Streaming (Adaptive bitrate, CDN)
- E-commerce (Inventory management, Saga, Elasticsearch)
- Ride-Sharing (Geospatial indexing, matching)
- Messaging (Delivery guarantees, Cassandra, presence)
Total: 40 KB (1 comprehensive document + INDEX)
- Advanced Topics (~40 KB)
- Serverless (AWS Lambda, cold start mitigation)
- Edge Computing (Cloudflare Workers, Lambda@Edge)
- Modern APIs (GraphQL DataLoader, gRPC streaming)
- Service Mesh (Istio traffic management, mTLS)
- Performance (Query optimization, connection pooling, caching)
- Emerging (WebAssembly, CRDTs, Event Sourcing)
Total: ~50 KB across multiple guides
- Docker volumes and data persistence
- Daemons vs processes
- Microservices communication patterns
- Message broker fundamentals (RabbitMQ)
- Queue system comparisons (RabbitMQ vs Celery vs Solace)
- Payment gateway integration patterns
ā
GOOD - Read when needed:
User: "Explain the CAP theorem"
ā Read docs/fundamentals/distributed-systems-fundamentals.md (section 1 only)
User: "How do I implement event sourcing?"
ā Read docs/phase2-architecture-patterns/event-driven-architecture.md (section 1)
User: "What's the Saga pattern?"
ā Read docs/phase2-architecture-patterns/event-driven-architecture.md (section 4)
User: "How do I implement caching?"
ā Read docs/phase3-scalability-performance/scalability-performance.md (section 1)
User: "When should I use MongoDB vs PostgreSQL?"
ā Read docs/phase4-data-management/data-management.md (section 1)
User: "Explain the Saga pattern for distributed transactions"
ā Read docs/phase4-data-management/data-management.md (section 2)
ā BAD - Don't read automatically:
User: "How do I run the tests?"
ā Don't read any docs, this is a practical question
User: "Debug this error in the code"
ā Don't read theory docs, focus on debugging
User: "List all the files"
ā Don't include docs in file listing, they're reference materials
Why? These files are very large (~625 KB total) and contain educational content. They should only be loaded when genuinely needed for the current task to conserve tokens and improve response time.
Goal: Understand why we move beyond monoliths and core distributed system concepts
-
Monolith Limitations
- Scalability bottlenecks
- Deployment risks
- Technology lock-in
- Team coordination challenges
-
Distributed Systems Fundamentals
- CAP Theorem (Consistency, Availability, Partition Tolerance)
- ACID vs BASE
- Network fallacies
- Consistency models (eventual, strong, causal)
-
System Design Principles
- Separation of concerns
- Single Responsibility Principle at system level
- Loose coupling, high cohesion
- Design for failure
- Document your current monolith's pain points
- Identify bounded contexts using Domain-Driven Design
- Create a service decomposition proposal
Goal: Learn common architectural patterns and when to use them
-
Microservices Architecture
- Service boundaries and sizing
- Communication patterns (sync vs async)
- Service mesh concepts
- API Gateway pattern
-
Event-Driven Architecture
- Event sourcing
- CQRS (Command Query Responsibility Segregation)
- Event streaming vs messaging
- Saga pattern for distributed transactions
-
Other Patterns
- Layered architecture
- Hexagonal architecture (Ports & Adapters)
- Clean architecture
- Strangler Fig pattern (for migration)
- Design a microservices architecture for your monolith
- Implement a simple event-driven system (2-3 services)
- Build an API Gateway proof-of-concept
Goal: Learn how to scale systems horizontally and vertically
-
Caching Strategies
- Cache-aside, write-through, write-behind
- CDN (Content Delivery Networks)
- Redis, Memcached patterns
- Cache invalidation strategies
-
Load Balancing
- Layer 4 vs Layer 7 load balancing
- Round-robin, least connections, consistent hashing
- Health checks and circuit breakers
- Global and regional load balancing
-
Database Scaling
- Read replicas
- Sharding strategies (horizontal partitioning)
- Database per service pattern
- Denormalization for read performance
- Connection pooling
-
Asynchronous Processing
- Message queues (RabbitMQ, Kafka, SQS)
- Job queues and workers
- Backpressure handling
- Dead letter queues
- Implement caching layer (Redis) for high-traffic endpoints
- Set up load balancer with multiple instances
- Create a job queue system with workers
Goal: Master data storage, consistency, and replication in distributed systems
-
Database Types & Use Cases
- Relational (PostgreSQL, MySQL)
- Document stores (MongoDB, CouchDB)
- Key-value stores (Redis, DynamoDB)
- Column-family (Cassandra, HBase)
- Graph databases (Neo4j)
- Time-series databases (InfluxDB, TimescaleDB)
-
Data Consistency Patterns
- Two-phase commit (2PC)
- Three-phase commit
- Saga pattern
- Compensating transactions
- Idempotency
-
Data Replication
- Master-slave replication
- Multi-master replication
- Quorum-based replication
- Conflict resolution
- Design a polyglot persistence solution
- Implement a distributed transaction with Saga pattern
- Set up database replication (master-slave)
Goal: Build systems that gracefully handle failures
-
Fault Tolerance Patterns
- Circuit breaker (Hystrix, Resilience4j)
- Bulkhead pattern
- Retry with exponential backoff
- Timeout management
- Fallback strategies
-
High Availability
- Redundancy and failover
- Active-active vs active-passive
- Health checks and monitoring
- Disaster recovery planning
- SLAs, SLOs, SLIs
-
Chaos Engineering
- Failure injection
- Chaos Monkey concepts
- Testing resilience
- Implement circuit breaker pattern
- Set up health checks and auto-recovery
- Conduct a chaos engineering experiment
Goal: Learn to understand and debug distributed systems in production
-
The Three Pillars
- Logging (structured logging, log aggregation)
- Metrics (RED/USE methods, golden signals)
- Tracing (distributed tracing, OpenTelemetry)
-
Tools & Platforms
- ELK Stack (Elasticsearch, Logstash, Kibana)
- Prometheus + Grafana
- Jaeger, Zipkin for tracing
- DataDog, New Relic (commercial options)
-
Alerting & On-Call
- Alert design (actionable, not noisy)
- On-call best practices
- Incident response
- Set up complete observability stack
- Implement distributed tracing across services
- Create meaningful dashboards and alerts
Goal: Secure distributed systems and manage authentication/authorization
-
Authentication & Authorization
- OAuth 2.0 / OpenID Connect
- JWT tokens
- API keys and secrets management
- Service-to-service authentication (mTLS)
-
Security Patterns
- Zero trust architecture
- Defense in depth
- Rate limiting and throttling
- DDoS protection
- API security best practices
-
Secrets Management
- Vault, AWS Secrets Manager
- Key rotation
- Encryption at rest and in transit
- Implement OAuth 2.0 authentication
- Set up secrets management solution
- Add rate limiting to API gateway
Goal: Master deployment strategies and infrastructure as code
-
Containerization & Orchestration
- Docker deep dive
- Kubernetes fundamentals
- Service discovery
- Container networking
-
CI/CD Pipelines
- Automated testing strategies
- Blue-green deployments
- Canary releases
- Rolling deployments
- Feature flags
-
Infrastructure as Code
- Terraform
- CloudFormation
- Pulumi
- GitOps principles
- Containerize your services
- Deploy to Kubernetes cluster
- Build complete CI/CD pipeline
Goal: Study and understand large-scale production systems
-
URL Shortener (like bit.ly)
- Requirements: low latency, high availability
- Key concepts: hashing, base62 encoding, caching
-
Social Media Feed (like Twitter)
- Requirements: real-time updates, high read/write ratio
- Key concepts: fan-out on write vs read, timelines
-
Video Streaming (like YouTube)
- Requirements: bandwidth optimization, global distribution
- Key concepts: CDN, adaptive bitrate, chunking
-
E-commerce Platform (like Amazon)
- Requirements: transactions, inventory, search
- Key concepts: eventual consistency, order processing
-
Messaging System (like WhatsApp)
- Requirements: real-time, delivery guarantees
- Key concepts: WebSockets, message queues, presence
-
Ride-Sharing (like Uber)
- Requirements: geolocation, matching, real-time tracking
- Key concepts: geohashing, websockets, event streaming
- Design 2-3 of these systems in detail
- Implement a simplified version of one system
Goal: Explore cutting-edge concepts and optimization techniques
-
Advanced Patterns
- Serverless architecture (Lambda, Cloud Functions)
- Edge computing
- GraphQL federation
- gRPC and protocol buffers
- Service mesh (Istio, Linkerd)
-
Performance Optimization
- Database query optimization
- N+1 query problem solutions
- Connection pooling strategies
- Batch processing optimization
- Memory and CPU profiling
-
Global Distribution
- Multi-region deployments
- Data locality and GDPR compliance
- Global load balancing
- Conflict-free replicated data types (CRDTs)
- Implement serverless functions
- Set up multi-region deployment
- Optimize a bottleneck in your system
- URL Shortener - Week 3-4
- Task Queue System - Week 5-6
- Chat Application - Week 7-8
- Rate Limiter - Week 9-10
- Notification Service - Week 11-12
Design and implement a complete distributed system of your choice:
- Option A: E-commerce platform with microservices
- Option B: Real-time analytics dashboard
- Option C: Content delivery and streaming service
- Option D: Distributed task scheduler
Requirements:
- 5+ microservices
- Multiple databases (polyglot persistence)
- Message queue integration
- Complete observability
- CI/CD pipeline
- Load testing and optimization
- Documentation and diagrams
- "Designing Data-Intensive Applications" by Martin Kleppmann
- "System Design Interview" by Alex Xu (Vol 1 & 2)
- "Building Microservices" by Sam Newman
- "Release It!" by Michael Nygard
- "Database Internals" by Alex Petrov
- System Design Primer (GitHub)
- High Scalability blog
- AWS Architecture Center
- Google Cloud Architecture Framework
- Microsoft Azure Architecture Center
- LeetCode System Design
- System Design Interview prep sites
- AWS Free Tier for hands-on practice
(Document key insights, challenges, and solutions as you progress)
- Start with Phase 1: Review monolith limitations and identify decomposition boundaries
- Set up your learning environment (Docker, local Kubernetes, cloud account)
- Begin documenting your current system's architecture
Remember: System design is about trade-offs. There's no perfect solution, only solutions that fit specific requirements and constraints. Focus on understanding the "why" behind each pattern and practice making reasoned decisions.