Added complete documentation and runnable examples for the arbitrage detection engine.
Documentation:
- Complete README.md with architecture overview
- Component descriptions with code examples
- Configuration reference with all parameters
- Performance benchmarks and optimization tips
- Best practices for production deployment
- Usage examples for all major features
Examples (examples_test.go):
- Basic setup and initialization
- Opportunity detection workflows
- Real-time swap monitoring
- Opportunity stream consumption
- Path finding examples
- Profitability calculation
- Gas estimation
- Opportunity ranking
- Statistics tracking
All examples are runnable as Go examples and thoroughly document:
- Setup procedures
- Error handling patterns
- Configuration options
- Integration patterns
- Monitoring strategies
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Implemented Phase 3 of the V2 architecture: a comprehensive arbitrage detection engine with path finding, profitability calculation, and opportunity detection.
Core Components:
- Opportunity struct: Represents arbitrage opportunities with full execution context
- PathFinder: Finds two-pool, triangular, and multi-hop arbitrage paths using BFS
- Calculator: Calculates profitability using protocol-specific math (V2, V3, Curve)
- GasEstimator: Estimates gas costs and optimal gas prices
- Detector: Main orchestration component for opportunity detection
Features:
- Multi-protocol support: UniswapV2, UniswapV3, Curve StableSwap
- Concurrent path evaluation with configurable limits
- Input amount optimization for maximum profit
- Real-time swap monitoring and opportunity stream
- Comprehensive statistics tracking
- Token whitelisting and filtering
Path Finding:
- Two-pool arbitrage: A→B→A across different pools
- Triangular arbitrage: A→B→C→A with three pools
- Multi-hop arbitrage: Up to 4 hops with BFS search
- Liquidity and protocol filtering
- Duplicate path detection
Profitability Calculation:
- Protocol-specific swap calculations
- Price impact estimation
- Gas cost estimation with multipliers
- Net profit after fees and gas
- ROI and priority scoring
- Executable opportunity filtering
Testing:
- 100% test coverage for all components
- 1,400+ lines of comprehensive tests
- Unit tests for all public methods
- Integration tests for full workflows
- Edge case and error handling tests
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Updated project guidance to reflect V2 foundation completion:
Branch Structure:
- v2-master (production, protected)
- v2-master-dev (development, protected)
- feature/v2-prep (archived, foundation complete)
- feature/v2/* (feature branches from v2-master-dev)
Branch Hierarchy:
v2-master ← v2-master-dev ← feature/v2/*
Updated Sections:
- Project Status: V2 Foundation Complete ✅
- Git Workflow: New branch structure and workflow
- Example Workflow: Updated to use v2-master-dev
- What TO Do: Reflects foundation completion
- Key Files: Added V2 foundation files (100% coverage)
- Current Branches: New section documenting branch structure
- Contact and Resources: Updated with completion status
Workflow:
1. Create feature branch from v2-master-dev
2. Implement with 100% test coverage
3. Run make validate locally
4. PR to v2-master-dev (CI/CD enforces coverage)
5. Merge v2-master-dev → v2-master for production
Foundation Status:
- 3,300+ lines (1,500 implementation, 1,800 tests)
- 100% test coverage (enforced)
- CI/CD fully configured
- Ready for protocol parser implementations
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Complete Phase 1 foundation implementation with 100% test coverage:
Components Implemented:
- Parser factory with multi-protocol support
- Logging infrastructure with slog
- Metrics infrastructure with Prometheus
- Multi-index pool cache (address, token pair, protocol, liquidity)
- Validation pipeline with configurable rules
All tests passing with 100% coverage (enforced).
Ready for Phase 2: Protocol-specific parser implementations.
- Created MODULARITY_REQUIREMENTS.md with component independence rules
- Created PROTOCOL_SUPPORT_REQUIREMENTS.md covering 13+ protocols
- Created TESTING_REQUIREMENTS.md enforcing 100% coverage
- Updated CLAUDE.md with strict feature/v2/* branch strategy
Requirements documented:
- Component modularity (standalone + integrated)
- 100% test coverage enforcement (non-negotiable)
- All DEX protocols (Uniswap V2/V3/V4, Curve, Balancer V2/V3, Kyber Classic/Elastic, Camelot V2/V3 with all Algebra variants)
- Proper decimal handling (critical for calculations)
- Pool caching with multi-index and O(1) mappings
- Market building with essential arbitrage detection values
- Price movement detection with decimal precision
- Transaction building (single and batch execution)
- Pool discovery and caching
- Comprehensive validation at all layers
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Final production deployment fixes to enable full MEV bot functionality.
Changes:
- Add data volume mount to docker-compose.yml for database persistence
- Enable arbitrage service in config.dev.yaml
- Add arbitrage configuration section with default values
Testing:
- Container running and healthy
- Processing Arbitrum blocks successfully
- Running arbitrage scans every 5 seconds
- Database created and operational
- Metrics server accessible on port 9090
Status:
- Container: mev-bot-production
- Health: Up and healthy
- Blocks processed: 17+
- Arbitrage scans: 10+ completed
- Auto-restart: enabled (restart: always)
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Add comprehensive production deployment infrastructure with Docker auto-restart
and systemd on-boot startup capabilities.
Changes:
- Add deploy-production-docker.sh: Automated deployment script with Docker validation
- Add install-systemd-service.sh: Systemd service installer for auto-start on boot
- Add scripts/mev-bot.service: Systemd service definition for MEV bot
- Update docker-compose.yml: Enable logs volume mount and metrics port
- Update PRODUCTION_QUICKSTART.md: Simplified deployment documentation
Features:
- Docker auto-restart on failure (restart: always policy)
- Systemd auto-start on system boot
- Persistent logs via volume mount
- Health checks and resource limits
- Comprehensive deployment validation
- Easy-to-use installation scripts
Usage:
./scripts/deploy-production-docker.sh # Deploy with Docker
sudo ./scripts/install-systemd-service.sh # Enable auto-start on boot
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Add docker-compose.yml with production-ready configuration including auto-restart, health checks, resource limits, and security hardening
- Completely rewrite DEPLOYMENT_GUIDE.md from smart contract deployment to comprehensive Docker/L2 MEV bot deployment guide
- New guide includes Docker deployment, systemd integration, monitoring setup with Prometheus/Grafana, performance optimization, security configuration, and troubleshooting
- Configuration supports environment-based setup with .env file integration
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Migrate from Docker to Podman for enhanced security (rootless containers)
- Add production-ready Dockerfile with multi-stage builds
- Configure production environment with Arbitrum mainnet RPC endpoints
- Add comprehensive test coverage for core modules (exchanges, execution, profitability)
- Implement production audit and deployment documentation
- Update deployment scripts for production environment
- Add container runtime and health monitoring scripts
- Document RPC limitations and remediation strategies
- Implement token metadata caching and pool validation
This commit prepares the MEV bot for production deployment on Arbitrum
with full containerization, security hardening, and operational tooling.
🤖 Generated with Claude Code
Co-Authored-By: Claude <noreply@anthropic.com>
Created detailed report explaining zero arbitrage executions:
**Key Findings:**
- Bot IS working correctly (detecting 30+ opportunities)
- 100% rejection rate due to negative profit after gas
- Average profit: $0.00 before gas, -$0.014 after gas
- All opportunities correctly rejected (protecting from losses)
**Root Cause:**
Market is too efficient - no profitable arbitrage exists at current settings:
- Arbitrum highly competitive (100s of MEV bots)
- Typical spreads <0.1% (need >0.5% to profit after fees)
- Gas + fees + slippage >0.5% on all detected opportunities
- Faster bots capture any real opportunities in milliseconds
**Recommendations:**
Short-term (1-2 weeks):
- Deploy to co-located VPS (reduce latency 10-50x)
- Implement flash loan execution (architecture ready)
- Lower profit threshold to 0.00005 ETH (test on testnet first)
- Add mempool monitoring (detect before block inclusion)
Medium-term (2-4 weeks):
- Enable multi-hop arbitrage (3-4 hops, less competition)
- Optimize gas pricing (dynamic bidding based on profit)
- Add cross-chain opportunities
- Integrate with Flashbots private mempool
**Realistic Targets:**
- Week 1-2: First profitable execution
- Week 3-4: 1-2 profitable trades/day
- Month 2: 5-10 profitable trades/day
- Month 3: $50-$200 daily profit (with all optimizations)
Industry benchmarks show amateur bots execute <0.01% of detected opportunities.
This is NORMAL for efficient markets like Arbitrum.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
Added detailed log analysis showing bot is fully operational:
- Processing 3,770 blocks in 15 minutes (100% success rate)
- Detecting 193 DEX transactions across multiple protocols
- System health score: 90/100 (Production Ready)
Identified issue: Chainstack RPS limit lower than configured
- 614 RPS errors in 10k log lines (94.9% of errors)
- Errors occur in bursts during pool data fetching
- Does not block core functionality (graceful error handling)
Applied immediate fix in config/arbitrum_production.yaml:
- Reduced RPS from 100 to 20 (match Chainstack Growth plan)
- Reduced concurrent requests from 20 to 5
- Reduced burst from 100 to 30
- Added 50ms delay between requests
Impact: Should eliminate 95%+ of RPS errors while maintaining performance
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
Critical fixes applied to resolve 94.4% error rate from RPC rate limiting:
**Configuration Fixes:**
- .env.production: Set Chainstack WSS as primary endpoint
- config/providers_runtime.yaml: Prioritized Chainstack with 100 RPS limits
- config/arbitrum_production.yaml: Increased rate limits from 20 to 100 RPS
**Code Fixes:**
- pkg/scanner/market/scanner.go: Use shared RPC client from contractExecutor
instead of creating new clients for every pool fetch (critical fix)
**Results:**
- Blocks processing continuously without interruption
- DEX transactions being detected and analyzed
- 429 errors reduced from 21,590 (94.4%) to minimal occurrences
- System health restored to production readiness
**Root Cause:**
Scanner was creating new RPC clients for every concurrent pool fetch,
bypassing rate limiting and causing excessive requests to RPC endpoint.
Each goroutine's client made independent requests without coordination.
**Technical Details:**
- Shared client respects global rate limits
- Prevents connection pool exhaustion
- Reduces overhead from repeated connection setup
- Ensures all RPC calls go through rate-limited provider manager
Resolves: LOG_ANALYSIS_20251029.md findings
Impact: Critical - enables continuous block processing
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
