claude-flow
Version:
Ruflo - Enterprise AI agent orchestration for Claude Code. Deploy 60+ specialized agents in coordinated swarms with self-learning, fault-tolerant consensus, vector memory, and MCP integration
251 lines (243 loc) • 8.61 kB
JSON
{
"v3PerformanceTargets": {
"version": "3.0.0",
"strategy": "phased_rollout",
"totalPhases": 4,
"riskMitigation": "progressive_targets",
"phases": {
"phase1": {
"name": "Security Foundation",
"duration": "weeks 1-3",
"description": "Conservative targets while establishing security baseline",
"targets": {
"flashAttention": {
"target": "2.49x minimum",
"description": "Conservative start, focus on stability",
"measurement": "baseline vs flash attention speedup",
"priority": "medium"
},
"searchImprovement": {
"target": "150x minimum",
"description": "Basic HNSW implementation",
"measurement": "vector search latency improvement",
"priority": "high"
},
"memoryReduction": {
"target": "40%",
"description": "Initial optimization, achievable target",
"measurement": "heap usage reduction",
"priority": "medium"
},
"startupTime": {
"target": "<750ms",
"description": "Less aggressive than final target",
"measurement": "CLI cold start time",
"priority": "high"
},
"securityScore": {
"target": "75/100",
"description": "Significant security improvement",
"measurement": "npm audit + custom security scans",
"priority": "critical"
}
},
"gates": {
"required": ["securityScore", "startupTime"],
"optional": ["flashAttention", "memoryReduction"]
}
},
"phase2": {
"name": "Core Systems Optimization",
"duration": "weeks 4-8",
"description": "Mid-range targets with core system optimizations",
"targets": {
"flashAttention": {
"target": "3.5x - 5.0x",
"description": "Mid-range optimization",
"measurement": "sequence processing speedup",
"priority": "high"
},
"searchImprovement": {
"target": "500x - 2000x",
"description": "Optimized HNSW with tuning",
"measurement": "vector search performance",
"priority": "high"
},
"memoryReduction": {
"target": "50%",
"description": "Enhanced optimization techniques",
"measurement": "memory usage efficiency",
"priority": "medium"
},
"startupTime": {
"target": "<500ms",
"description": "Target achieved with optimization",
"measurement": "CLI startup latency",
"priority": "high"
},
"swarmCoordination": {
"target": "<100ms",
"description": "15-agent coordination latency",
"measurement": "swarm consensus time",
"priority": "high"
},
"agentSpawnTime": {
"target": "<200ms",
"description": "Individual agent spawn latency",
"measurement": "agent initialization time",
"priority": "medium"
}
},
"gates": {
"required": ["flashAttention", "searchImprovement", "startupTime"],
"optional": ["swarmCoordination", "agentSpawnTime"]
}
},
"phase3": {
"name": "Integration Excellence",
"duration": "weeks 9-12",
"description": "High-performance targets with full integration",
"targets": {
"flashAttention": {
"target": "5.0x - 7.47x",
"description": "Near-maximum optimization",
"measurement": "attention mechanism performance",
"priority": "high"
},
"searchImprovement": {
"target": "2000x - 12,500x",
"description": "Maximum performance achieved",
"measurement": "vector database performance",
"priority": "high"
},
"memoryReduction": {
"target": "65%",
"description": "Advanced compression techniques",
"measurement": "overall memory efficiency",
"priority": "medium"
},
"startupTime": {
"target": "<350ms",
"description": "Excellence target achieved",
"measurement": "optimized CLI performance",
"priority": "medium"
},
"mcpResponseTime": {
"target": "<100ms p95",
"description": "MCP server optimization",
"measurement": "MCP tool execution latency",
"priority": "high"
},
"learningAdaptation": {
"target": "<0.05ms",
"description": "SONA micro-LoRA adaptation",
"measurement": "learning cycle latency",
"priority": "medium"
}
},
"gates": {
"required": ["flashAttention", "searchImprovement", "mcpResponseTime"],
"optional": ["memoryReduction", "learningAdaptation"]
}
},
"phase4": {
"name": "Excellence & Polish",
"duration": "weeks 13-16",
"description": "Stretch targets and final optimization",
"targets": {
"flashAttention": {
"target": "7.47x",
"description": "Maximum theoretical speedup",
"measurement": "peak attention performance",
"priority": "stretch"
},
"searchImprovement": {
"target": "12,500x",
"description": "Peak HNSW performance",
"measurement": "optimal vector search",
"priority": "stretch"
},
"memoryReduction": {
"target": "75%",
"description": "Maximum memory efficiency",
"measurement": "peak memory optimization",
"priority": "stretch"
},
"startupTime": {
"target": "<300ms",
"description": "Sub-300ms cold start",
"measurement": "peak startup performance",
"priority": "stretch"
},
"overallThroughput": {
"target": "10x",
"description": "Overall system throughput",
"measurement": "end-to-end performance",
"priority": "high"
},
"reliabilityScore": {
"target": "99.9%",
"description": "Three nines reliability",
"measurement": "system uptime and stability",
"priority": "high"
}
},
"gates": {
"required": ["overallThroughput", "reliabilityScore"],
"optional": ["flashAttention", "searchImprovement", "memoryReduction"]
}
}
},
"monitoring": {
"frequency": "continuous",
"alerting": {
"regressionThreshold": "10%",
"criticalThreshold": "25%",
"notificationChannels": ["console", "metrics"]
},
"benchmarks": {
"automated": true,
"schedule": "daily",
"regressionDetection": true
}
},
"rollbackTriggers": [
"Security score drops below 70/100",
"Startup time exceeds 1000ms",
"Memory usage increases by >50%",
"Critical functionality broken",
"Performance regression >25%"
],
"success_metrics": {
"phase1_success": {
"security_baseline": "Achieved 75/100 security score",
"stability": "No critical regressions",
"performance": "Baseline improvements established"
},
"phase2_success": {
"performance": "Mid-range targets achieved",
"coordination": "15-agent swarm operational",
"optimization": "Core systems optimized"
},
"phase3_success": {
"integration": "agentic-flow integration complete",
"performance": "High-performance targets met",
"features": "All v3 features operational"
},
"phase4_success": {
"excellence": "Stretch targets achieved where possible",
"reliability": "Production-ready stability",
"optimization": "Peak performance validated"
}
},
"adaptive_strategy": {
"enabled": true,
"description": "Targets adjust based on actual achievement rates",
"rules": {
"if_ahead_of_schedule": "Attempt next phase targets early",
"if_behind_schedule": "Focus on required gates, defer optional",
"if_critical_issues": "Halt advancement, focus on resolution"
}
}
}
}