Full Stack Developer • Backend & Infrastructure Engineer • Systems Architect • DevOps Practitioner

I'm a systems-first developer who builds resilient, scalable infrastructure—not just features. My approach combines deep system design knowledge with hands-on implementation across the full stack, from distributed backend services to cloud-native deployments.

What drives me:

• 🏗️ Architecture over Implementation — Understanding why before how
• 🔧 Production Systems — Building for failure, monitoring, observability
• 🚀 Performance at Scale — Distributed systems, concurrent processing, real-time data
• 🎯 Infrastructure as Code — Kubernetes, Docker, CI/CD pipelines
• 🌐 Web3 & Decentralized Systems — Blockchain infrastructure, Solana, Rust

const approach = {
      learning: "Systems deeply, not superficially",
      building: "Mental models before frameworks",
      mindset: "Break things to understand them",
      scale: "Design for failure from day one",
      optimization: "Measure, don't assume"
  };

• 💥 I'm obsessed with how systems behave under failure
• 🔨 I enjoy breaking things just to understand how to fix them properly
• 🧠 I prefer mental models over frameworks
• 🎯 I believe learning infra before Web3 makes everything clearer

Building a production-grade exchange system to deeply understand financial infrastructure before transitioning to Web3/DeFi protocols.

System Architecture:

┌─────────────────────────────────────────────────────────────┐
│                    WebSocket Server (Real-time)              │
│                   ↓ Market Data & Order Updates             │
├─────────────────────────────────────────────────────────────┤
│                      API Gateway (REST)                      │
│                  ↓ Order Placement & Queries                 │
├─────────────────────────────────────────────────────────────┤
│                   Redis Pub/Sub + Queue                      │
│              ↓ Event Streaming & Sequencing                  │
├─────────────────────────────────────────────────────────────┤
│                    Matching Engine Core                      │
│         ↓ Order Book, Price-Time Priority, Fills            │
├─────────────────────────────────────────────────────────────┤
│              Balance Manager (ACID Compliance)               │
│         Available Balance ↔ Locked Balance                   │
├─────────────────────────────────────────────────────────────┤
│                PostgreSQL + Redis (State)                    │
└─────────────────────────────────────────────────────────────┘

Why This Matters for Web3:

• 🎯 Understanding centralized exchange mechanics before building DEX protocols
• 🧠 Mental models for AMMs, order books on Solana, MEV protection
• 🏗️ Production-grade infrastructure thinking for blockchain systems
• 🦀 Transitioning to Rust with domain knowledge intact

Key Learnings from Building the Exchange:

• How to handle concurrent order processing with Redis queues
• ACID compliance in distributed systems (PostgreSQL transactions)
• Real-time data streaming architecture (WebSocket + Pub/Sub)
• Performance optimization: O(log n) order book, sub-ms latency
• State management: Available vs Locked balance semantics
• Event sourcing patterns for audit trails

• Rebuild exchange in Rust with tokio async runtime
• Deploy to Kubernetes cluster with horizontal auto-scaling
• Implement Solana smart contracts for decentralized order book
• Build MEV-resistant order flow system with encryption
• Add Grafana dashboards for real-time monitoring
• Write comprehensive system design docs and architecture decision records

Databases & Caching

Message Queues & Streaming

Cloud Providers

Monitoring & Observability

const engineeringPrinciples = {
  systems: "Learn deeply, not superficially — understand the 'why'",
  building: "Mental models compound faster than frameworks",
  debugging: "Break things intentionally to learn how to fix them",
  scale: "Design for failure; systems fail, always",
  optimization: "Measure first, optimize second — premature optimization kills",
  infrastructure: "Master the fundamentals before abstractions",
  web3: "Understand centralized systems before decentralized ones"
};

// Production mindset
const approach = (problem) => {
  return {
    step1: "Understand the system constraints",
    step2: "Model failure scenarios",
    step3: "Build, measure, iterate",
    step4: "Document mental models, not just code"
  };
};

// How I approach learning
const learningPath = {
  theory: "Read papers, understand algorithms",
  practice: "Build from scratch, no libraries",
  production: "Deploy, monitor, debug in real scenarios",
  sharing: "Write docs, teach others, solidify understanding"
};

• 🎯 Mental models > Frameworks — Frameworks change, principles don't
• 🔧 Build from scratch first — Understanding emerges from implementation
• 📊 Observability is not optional — You can't fix what you can't measure
• ⚡ Systems thinking — Everything is a distributed system at scale
• 🚀 Infrastructure before abstraction — Learn Kubernetes before serverless
• 💡 Failure is a feature — Design for it, test for it, monitor for it
• 🧠 Read code, lots of it — Best way to learn is from production systems

System Design & Architecture

• Designing scalable distributed systems from ground up
• Event-driven architectures with message queues
• Real-time data processing pipelines
• High-availability & fault-tolerant systems

Backend Engineering

• RESTful & GraphQL API design
• WebSocket servers for real-time communication
• Database optimization (SQL & NoSQL)
• Caching strategies with Redis

DevOps & Infrastructure

• Kubernetes cluster management & orchestration
• CI/CD pipeline automation
• Infrastructure as Code (Terraform, Helm)
• Monitoring, logging, and alerting (Prometheus, Grafana)

I'm always open to discussing:

• 🏗️ System design & architecture patterns
• ⚡ High-performance backend optimization
• ☸️ Kubernetes & cloud-native infrastructure
• 🔗 Web3 protocols & decentralized systems
• 📈 Exchange mechanics & financial infrastructure
• 🎓 Mentorship in backend engineering or DevOps