performance-monitor

Performance Monitor

System yang tetap KILAT meski loaded! ⚡

🎯 Core Function

Monitor dan optimize semua aspek performance:

1. Response Time Tracking - Measure how fast I respond
2. Resource Usage - Monitor CPU, memory, disk, network
3. Skill Efficiency - Track which skills are fast/slow
4. Bottleneck Detection - Find what's slowing things down
5. Auto Optimization - Improve performance automatically

📊 Metrics Tracked

Response Metrics:

✅ Average response time: [X ms]
✅ Fastest response: [Y ms]
✅ Slowest response: [Z ms]
✅ P95 response time: [XX ms]
✅ P99 response time: [XXX ms]
✅ Requests per minute: [X]

Resource Metrics:

✅ CPU usage: [XX%]
✅ Memory usage: [XX MB]
✅ Disk I/O: [X MB/s]
✅ Network: [X KB/s]
✅ Active connections: [X]
✅ Concurrent tasks: [X]

Skill Metrics:

✅ Most used skills: [list]
✅ Slowest skills: [list]
✅ Fastest skills: [list]
✅ Error rates: [skill, %]
✅ Efficiency scores: [skill, %]

🔧 Monitoring Modes

Mode 1: Real-Time

Live monitoring with immediate alerts
- Response time spikes
- Resource usage thresholds
- Error rate increases
- System health changes

Mode 2: Periodic Reports

Regular performance reports:
- Every hour: Quick snapshot
- Daily: Detailed analysis
- Weekly: Trends & improvements
- Monthly: Comprehensive review

Mode 3: On-Demand

Manual performance check:
- `/performance` - Quick status
- `/performance-detailed` - Full report
- `/performance-benchmark` - Stress test

📈 Performance Dashboard

Quick Status (/performance):

PERFORMANCE STATUS: ✅ OPTIMAL

Response Time:
✓ Avg: 850ms
✓ Fast: 120ms
✓ Slow: 2.5s

Resources:
✓ CPU: 45%
✓ Memory: 1.2GB
✓ Disk: 60%

Health: 98%
Status: All systems normal

Detailed Report (/performance-detailed):

DETAILED PERFORMANCE REPORT
============================

## Response Times (Last 24h)
- Average: 850ms
- P50: 650ms
- P95: 1.8s
- P99: 3.2s

Top 5 Fastest Tasks:
1. Simple greeting: 120ms
2. Yes/No answers: 180ms
3. Status checks: 220ms
4. Short queries: 350ms
5. Quick facts: 420ms

Top 5 Slowest Tasks:
1. Complex code generation: 8.5s
2. Full research reports: 12s
3. Multi-step workflows: 15s
4. Video generation: 45s
5. Large file processing: 60s

## Resource Usage
- CPU: 45% (avg 52%)
- Memory: 1.2GB / 4GB (30%)
- Disk I/O: Read 15MB/s, Write 5MB/s
- Network: Stable

## Skill Performance
- Fastest: context-mastery (50ms)
- Slowest: ai-video-generator (45s)
- Most used: autonomous-coding (120/day)

## Optimization Suggestions
1. Clear cache (saves 200MB)
2. Optimize database query (saves 1.2s)
3. Enable compression (saves 30% bandwidth)

🔍 Bottleneck Detection

Common Bottlenecks:

Slow Response:

DIAGNOSIS:
- Network latency: High
- Processing time: Normal
- Query speed: Slow

ACTION: Optimize database queries

High Memory:

DIAGNOSIS:
- Cache size: Growing
- Session data: Accumulating
- Memory leaks: Possible

ACTION:
1. Clear old caches
2. Compact sessions
3. Fix memory leak in [module]

CPU Spikes:

DIAGNOSIS:
- Processing: Heavy task
- Multiple tasks: Concurrent
- Inefficient: Algorithm issue

ACTION:
1. Queue heavy tasks
2. Optimize algorithms
3. Add caching

⚡ Auto-Optimization

Automatic Actions:

When Response Slow:

1. Enable caching
2. Compress outputs
3. Reduce verbosity
4. Pre-fetch data
5. Optimize queries

When Memory High:

1. Clear stale caches
2. Compress session data
3. Remove unused imports
4. Optimize data structures
5. Run garbage collection

When CPU High:

1. Queue non-urgent tasks
2. Parallelize where possible
3. Use more efficient algorithms
4. Implement batching
5. Scale horizontally

🛠️ Commands

/performance

Quick status check:

PERFORMANCE: ✅ OPTIMAL

Response: 850ms avg
Resources: Normal
Health: 98%

/performance-detailed

Full performance report:

Detailed metrics for all areas...

/benchmark

Run performance benchmark:

BENCHMARK STARTED

Testing...
✓ Simple queries: [X]
✓ Complex tasks: [Y]
✓ Skill efficiency: [Z]

Result: Performance Grade [A/B/C/D]
Recommendations: [optimization tips]

/optimize

Run auto-optimization:

AUTO-OPTIMIZATION

Actions taken:
1. Cleared cache: +200MB
2. Compressed logs: -150MB
3. Optimized queries: +1.2s faster
4. Enabled compression: -30% bandwidth

Performance improved by: 25%

/monitor <metric>

Monitor specific metric:

MONITORING: Response Time

Current: 850ms
Threshold: <1000ms ✅
Trend: Stable
Alerts: None

/alert

Set performance alerts:

ALERTS CONFIGURED:

⚠️ Response time > 3s → Alert
⚠️ Memory > 3GB → Alert
⚠️ CPU > 80% → Alert
⚠️ Error rate > 5% → Alert

📊 Performance History

Track Over Time:

PERFORMANCE TREND (Last 7 days):

Response Time:
Day 1: 920ms
Day 2: 880ms
Day 3: 850ms
Day 4: 830ms
Day 5: 810ms
Day 6: 790ms
Day 7: 770ms
Trend: ↘️ Improving

Resource Usage:
CPU: 52% → 45% (↓7%)
Memory: 1.5GB → 1.2GB (↓20%)
Disk: Stable

🚀 Optimization Tips

For AI Response:

1. Cache common responses
2. Pre-compute frequent queries
3. Use streaming for large outputs
4. Compress text responses
5. Lazy-load heavy features

For System:

1. Clear caches regularly
2. Optimize database queries
3. Enable async processing
4. Use connection pooling
5. Monitor and alert proactively

For Skills:

1. Profile skill execution
2. Optimize slow skills
3. Cache skill outputs
4. Batch similar requests
5. Parallelize independent tasks

📈 Continuous Improvement

WEEKLY OPTIMIZATION:

This week:
- Reduced response time: 10%
- Saved memory: 500MB
- Fixed 3 performance bugs
- Optimized 5 slow skills
- Improved throughput: 25%

Next week focus:
- Optimize video generation
- Reduce database queries
- Improve caching strategy

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Goal: Keep OpenClaw running KILAT! ⚡

Status: Performance Monitoring ACTIVE
Health: 98%+
Optimization: Continuous