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>
55 lines
1.6 KiB
Markdown
55 lines
1.6 KiB
Markdown
# Tune Concurrency Patterns
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Tune concurrency patterns for the following component: $ARGUMENTS
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## Concurrency Tuning Strategy:
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### 1. **Current Pattern Analysis**
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- Identify existing concurrency patterns (worker pools, pipelines, etc.)
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- Measure current performance and resource utilization
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- Analyze bottlenecks in concurrent processing
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### 2. **Optimization Areas**
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#### **Worker Pool Tuning**
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- Optimal worker count based on CPU cores and workload
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- Channel buffer sizing for backpressure management
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- Task distribution strategies
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- Worker lifecycle management
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#### **Pipeline Optimization**
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- Stage balancing to prevent bottlenecks
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- Buffer sizing between pipeline stages
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- Error propagation and recovery
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- Context cancellation handling
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#### **Fan-in/Fan-out Patterns**
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- Optimal fan-out ratios
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- Result merging strategies
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- Resource allocation across branches
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- Synchronization mechanisms
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### 3. **MEV Bot Specific Tuning**
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#### **Transaction Processing**
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- Optimal concurrent transaction processing
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- Event parsing parallelization
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- Memory usage per goroutine
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#### **Market Analysis**
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- Concurrent pool data fetching
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- Parallel arbitrage calculations
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- Resource sharing between analysis tasks
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## Implementation Guidelines:
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- Test with realistic workload patterns
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- Monitor resource utilization (CPU, memory, goroutines)
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- Ensure graceful degradation under load
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- Maintain error handling and recovery mechanisms
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## Deliverables:
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- Concurrency tuning recommendations
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- Performance benchmarks with different configurations
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- Resource utilization analysis
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- Configuration guidelines for different environments
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- Monitoring and alerting for concurrency issues |