c54c569f30
Completed clean root directory structure: - Root now contains only: .git, .env, docs/, orig/ - Moved all remaining files and directories to orig/: - Config files (.claude, .dockerignore, .drone.yml, etc.) - All .env variants (except active .env) - Git config (.gitconfig, .github, .gitignore, etc.) - Tool configs (.golangci.yml, .revive.toml, etc.) - Documentation (*.md files, @prompts) - Build files (Dockerfiles, Makefile, go.mod, go.sum) - Docker compose files - All source directories (scripts, tests, tools, etc.) - Runtime directories (logs, monitoring, reports) - Dependency files (node_modules, lib, cache) - Special files (--delete) - Removed empty runtime directories (bin/, data/) V2 structure is now clean: - docs/planning/ - V2 planning documents - orig/ - Complete V1 codebase preserved - .env - Active environment config (not in git) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
51 lines
1.4 KiB
Markdown
51 lines
1.4 KiB
Markdown
# Improve Latency Performance
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Improve latency performance for the following critical path: $ARGUMENTS
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## Latency Optimization Strategy:
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### 1. **Latency Analysis**
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- Measure current end-to-end latency
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- Identify latency components (network, computation, I/O)
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- Analyze latency distribution and outliers
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### 2. **Optimization Areas**
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#### **Network Latency**
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- Connection pooling for RPC calls
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- Request batching and pipelining
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- Caching frequently accessed data
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- Asynchronous processing patterns
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#### **Computational Latency**
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- Algorithmic complexity reduction
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- Lookup table implementation
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- Parallel processing opportunities
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- Precision vs. performance trade-offs
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#### **I/O Latency**
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- Buffering and streaming optimizations
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- Disk I/O patterns
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- Database query optimization
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- File system caching
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### 3. **MEV Bot Specific Optimizations**
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#### **Critical Path Components**
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- Transaction detection and parsing (< 10 microseconds target)
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- Market analysis and arbitrage calculation
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- Opportunity evaluation and ranking
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- Execution decision making
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## Implementation Guidelines:
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- Measure latency at each component
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- Focus on 95th and 99th percentile improvements
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- Ensure deterministic performance characteristics
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- Maintain accuracy while improving speed
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## Deliverables:
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- Latency benchmark results (before/after)
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- Latency distribution analysis
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- Optimization documentation
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- Monitoring and alerting for latency regressions
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- Performance vs. accuracy trade-off analysis |