wifi-densepose/benchmarks/docs/LOAD_TEST_SCENARIOS.md

# RuVector Load Testing Scenarios

## Overview

This document defines comprehensive load testing scenarios for the globally distributed RuVector system, targeting 500 million concurrent learning streams with burst capacity up to 25 billion.

## Test Environment

### Global Regions
- **Americas**: us-central1, us-east1, us-west1, southamerica-east1
- **Europe**: europe-west1, europe-west3, europe-north1
- **Asia-Pacific**: asia-east1, asia-southeast1, asia-northeast1, australia-southeast1
- **Total**: 11 regions

### Infrastructure
- **Cloud Run**: Auto-scaling instances (10-1000 per region)
- **Load Balancer**: Global HTTPS LB with Cloud CDN
- **Database**: Cloud SQL PostgreSQL (multi-region)
- **Cache**: Memorystore Redis (128GB per region)
- **Monitoring**: Cloud Monitoring + OpenTelemetry

---

## Scenario Categories

### 1. Baseline Scenarios

#### 1.1 Steady State (500M Concurrent)
**Objective**: Validate system handles target baseline load

**Configuration**:
- Total connections: 500M globally
- Distribution: Proportional to region capacity
  - Tier-1 regions (5): 80M each = 400M
  - Tier-2 regions (10): 10M each = 100M
- Query rate: 50K QPS globally
- Test duration: 4 hours
- Ramp-up: 30 minutes

**Success Criteria**:
- P99 latency < 50ms
- P50 latency < 10ms
- Error rate < 0.1%
- No memory leaks
- CPU utilization 60-80%
- All regions healthy

**Load Pattern**:
```javascript
{
  type: "ramped-arrival-rate",
  stages: [
    { duration: "30m", target: 50000 }, // Ramp up
    { duration: "4h",  target: 50000 }, // Steady
    { duration: "15m", target: 0 }      // Ramp down
  ]
}
```

#### 1.2 Daily Peak (750M Concurrent)
**Objective**: Handle 1.5x baseline during peak hours

**Configuration**:
- Total connections: 750M globally
- Peak hours: 18:00-22:00 local time per region
- Query rate: 75K QPS
- Test duration: 5 hours
- Multiple peaks (simulate time zones)

**Success Criteria**:
- P99 latency < 75ms
- P50 latency < 15ms
- Error rate < 0.5%
- Auto-scaling triggers within 60s
- Cost < $5K for test

---

### 2. Burst Scenarios

#### 2.1 World Cup Final (50x Burst)
**Objective**: Handle massive spike during major sporting event

**Event Profile**:
- **Pre-event**: 30 minutes before kickoff
- **Peak**: During match (90 minutes + 30 min halftime)
- **Post-event**: 60 minutes after final whistle
- **Geography**: Concentrated in specific regions (France, Argentina)

**Configuration**:
- Baseline: 500M concurrent
- Peak: 25B concurrent (50x)
- Primary regions: europe-west3 (France), southamerica-east1 (Argentina)
- Secondary spillover: All Europe/Americas regions
- Query rate: 2.5M QPS at peak
- Test duration: 3 hours

**Load Pattern**:
```javascript
{
  stages: [
    // Pre-event buzz (30 min before)
    { duration: "30m", target: 500000 },   // 10x baseline
    { duration: "15m", target: 2500000 },  // 50x PEAK
    // First half (45 min)
    { duration: "45m", target: 2500000 },  // Sustained peak
    // Halftime (15 min - slight drop)
    { duration: "15m", target: 1500000 },  // 30x
    // Second half (45 min)
    { duration: "45m", target: 2500000 },  // Back to peak
    // Extra time / penalties (30 min)
    { duration: "30m", target: 3000000 },  // 60x SUPER PEAK
    // Post-game analysis (30 min)
    { duration: "30m", target: 1000000 },  // 20x
    // Gradual decline (30 min)
    { duration: "30m", target: 100000 }    // 2x
  ]
}
```

**Regional Distribution**:
- **France**: 40% (10B peak)
- **Argentina**: 35% (8.75B peak)
- **Spain/Italy/Portugal**: 10% (2.5B peak)
- **Rest of Europe**: 8% (2B peak)
- **Americas**: 5% (1.25B peak)
- **Asia/Pacific**: 2% (500M peak)

**Success Criteria**:
- System survives without crash
- P99 latency < 200ms (degraded acceptable)
- P50 latency < 50ms
- Error rate < 5% (acceptable during super peak)
- Auto-scaling completes within 10 minutes
- No cascading failures
- Graceful degradation activated when needed
- Cost < $100K for full test

**Pre-warming**:
- Enable predictive scaling 15 minutes before test
- Pre-allocate 25x capacity in primary regions
- Warm up CDN caches
- Increase database connection pools

#### 2.2 Product Launch (10x Burst)
**Objective**: Handle viral traffic spike (e.g., AI model release)

**Configuration**:
- Baseline: 500M concurrent
- Peak: 5B concurrent (10x)
- Distribution: Global, concentrated in US
- Query rate: 500K QPS
- Test duration: 2 hours
- Pattern: Sudden spike, gradual decline

**Load Pattern**:
```javascript
{
  stages: [
    { duration: "5m",  target: 500000 },  // 10x instant spike
    { duration: "30m", target: 500000 },  // Sustained
    { duration: "45m", target: 300000 },  // Gradual decline
    { duration: "40m", target: 100000 }   // Return to normal
  ]
}
```

**Success Criteria**:
- Reactive scaling responds within 60s
- P99 latency < 100ms
- Error rate < 2%
- No downtime

#### 2.3 Flash Crowd (25x Burst)
**Objective**: Unpredictable viral event

**Configuration**:
- Baseline: 500M concurrent
- Peak: 12.5B concurrent (25x)
- Geography: Unpredictable (use US for test)
- Query rate: 1.25M QPS
- Test duration: 90 minutes
- Pattern: Very rapid spike (< 2 minutes)

**Load Pattern**:
```javascript
{
  stages: [
    { duration: "2m",  target: 1250000 }, // 25x in 2 minutes!
    { duration: "30m", target: 1250000 }, // Hold peak
    { duration: "30m", target: 750000 },  // Decline
    { duration: "28m", target: 100000 }   // Return
  ]
}
```

**Success Criteria**:
- System survives without manual intervention
- Reactive scaling activates immediately
- P99 latency < 150ms
- Error rate < 3%
- Cost cap respected

---

### 3. Failover Scenarios

#### 3.1 Single Region Failure
**Objective**: Validate regional failover

**Configuration**:
- Baseline: 500M concurrent
- Failed region: europe-west1 (80M connections)
- Failover targets: europe-west3, europe-north1
- Query rate: 50K QPS
- Test duration: 1 hour
- Failure trigger: 30 minutes into test

**Procedure**:
1. Run baseline load for 30 minutes
2. Simulate region failure (kill all instances in europe-west1)
3. Observe failover behavior
4. Measure recovery time
5. Validate data consistency

**Success Criteria**:
- Failover completes within 60 seconds
- Connection loss < 5%
- No data loss
- P99 latency spike < 200ms during failover
- Automatic recovery when region restored

#### 3.2 Multi-Region Cascade Failure
**Objective**: Test disaster recovery

**Configuration**:
- Baseline: 500M concurrent
- Failed regions: europe-west1, europe-west3 (160M connections)
- Failover: Global redistribution
- Test duration: 2 hours
- Progressive failures (15 min apart)

**Procedure**:
1. Run baseline load
2. Kill europe-west1 at T+30m
3. Kill europe-west3 at T+45m
4. Observe cascade prevention
5. Validate global recovery

**Success Criteria**:
- No cascading failures
- Circuit breakers activate
- Graceful degradation if needed
- Connection loss < 10%
- System remains stable

#### 3.3 Database Failover
**Objective**: Test database resilience

**Configuration**:
- Baseline: 500M concurrent
- Database: Trigger Cloud SQL failover to replica
- Query rate: 50K QPS (read-heavy)
- Test duration: 1 hour
- Failure trigger: 20 minutes into test

**Success Criteria**:
- Failover completes within 30 seconds
- Connection pool recovers automatically
- Read queries continue with < 5% errors
- Write queries resume after failover
- No permanent data loss

---

### 4. Workload Scenarios

#### 4.1 Read-Heavy (90% Reads)
**Objective**: Validate cache effectiveness

**Configuration**:
- Total connections: 500M
- Query mix: 90% similarity search, 10% updates
- Cache hit rate target: > 75%
- Query rate: 50K QPS
- Test duration: 2 hours

**Success Criteria**:
- P99 latency < 30ms (due to caching)
- Cache hit rate > 75%
- Database CPU < 50%

#### 4.2 Write-Heavy (40% Writes)
**Objective**: Test write throughput

**Configuration**:
- Total connections: 500M
- Query mix: 60% reads, 40% vector updates
- Query rate: 50K QPS
- Test duration: 2 hours
- Vector dimensions: 768

**Success Criteria**:
- P99 latency < 100ms
- Database CPU < 80%
- Replication lag < 5 seconds
- No write conflicts

#### 4.3 Mixed Workload (Realistic)
**Objective**: Simulate production traffic

**Configuration**:
- Total connections: 500M
- Query mix:
  - 70% similarity search
  - 15% filtered search
  - 10% vector inserts
  - 5% deletes
- Query rate: 50K QPS
- Test duration: 4 hours
- Varying vector dimensions (384, 768, 1536)

**Success Criteria**:
- P99 latency < 50ms
- All operations succeed
- Resource utilization balanced

---

### 5. Stress Scenarios

#### 5.1 Gradual Load Increase
**Objective**: Find breaking point

**Configuration**:
- Start: 100M concurrent
- End: Until system breaks
- Increment: +100M every 30 minutes
- Query rate: Proportional to connections
- Test duration: Until failure

**Success Criteria**:
- Identify maximum capacity
- Measure degradation curve
- Observe failure modes

#### 5.2 Long-Duration Soak Test
**Objective**: Detect memory leaks and resource exhaustion

**Configuration**:
- Total connections: 500M
- Query rate: 50K QPS
- Test duration: 24 hours
- Pattern: Steady state

**Success Criteria**:
- No memory leaks
- No connection leaks
- Stable performance over time
- Resource cleanup works

---

## Test Execution Strategy

### Sequential Execution (Standard Suite)
Total time: ~18 hours

1. Baseline Steady State (4h)
2. Daily Peak (5h)
3. Product Launch 10x (2h)
4. Single Region Failover (1h)
5. Read-Heavy Workload (2h)
6. Write-Heavy Workload (2h)
7. Mixed Workload (4h)

### Burst Suite (Special Events)
Total time: ~8 hours

1. World Cup 50x (3h)
2. Flash Crowd 25x (1.5h)
3. Multi-Region Cascade (2h)
4. Database Failover (1h)

### Quick Validation (Smoke Test)
Total time: ~2 hours

1. Baseline Steady State - 30 minutes
2. Product Launch 10x - 30 minutes
3. Single Region Failover - 30 minutes
4. Mixed Workload - 30 minutes

---

## Monitoring During Tests

### Real-Time Metrics
- Connection count per region
- Query latency percentiles (p50, p95, p99)
- Error rates by type
- CPU/Memory utilization
- Network throughput
- Database connections
- Cache hit rates

### Alerts
- P99 latency > 50ms (warning)
- P99 latency > 100ms (critical)
- Error rate > 1% (warning)
- Error rate > 5% (critical)
- Region unhealthy
- Database connections > 90%
- Cost > $10K/hour

### Dashboards
1. Executive: High-level metrics, SLA status
2. Operations: Regional health, resource utilization
3. Cost: Hourly spend, projections
4. Performance: Latency distributions, throughput

---

## Cost Estimates

### Per-Test Costs

| Scenario | Duration | Peak Load | Estimated Cost |
|----------|----------|-----------|----------------|
| Baseline Steady | 4h | 500M | $180 |
| Daily Peak | 5h | 750M | $350 |
| World Cup 50x | 3h | 25B | $80,000 |
| Product Launch 10x | 2h | 5B | $3,600 |
| Flash Crowd 25x | 1.5h | 12.5B | $28,000 |
| Single Region Failover | 1h | 500M | $45 |
| Workload Tests | 2h | 500M | $90 |

### Full Suite Costs
- **Standard Suite**: ~$900
- **Burst Suite**: ~$112K
- **Quick Validation**: ~$150

**Cost Optimization**:
- Use committed use discounts (30% off)
- Run tests in low-cost regions when possible
- Use preemptible instances for load generators
- Leverage CDN caching
- Clean up resources immediately after tests

---

## Pre-Test Checklist

### Infrastructure
- [ ] All regions deployed and healthy
- [ ] Load balancer configured
- [ ] CDN enabled
- [ ] Database replicas ready
- [ ] Redis caches warmed
- [ ] Monitoring dashboards set up
- [ ] Alerting policies active
- [ ] Budget alerts configured

### Load Generation
- [ ] K6 scripts validated
- [ ] Load generators deployed in all regions
- [ ] Test data prepared
- [ ] Baseline traffic running
- [ ] Credentials configured
- [ ] Results storage ready

### Team
- [ ] On-call engineer available
- [ ] Communication channels open (Slack)
- [ ] Runbook reviewed
- [ ] Rollback plan ready
- [ ] Stakeholders notified

---

## Post-Test Analysis

### Deliverables
1. Test execution log
2. Metrics summary (latency, throughput, errors)
3. SLA compliance report
4. Cost breakdown
5. Bottleneck analysis
6. Recommendations document
7. Performance comparison (vs. previous tests)

### Key Questions
- Did we meet SLA targets?
- Where did bottlenecks occur?
- How well did auto-scaling perform?
- Were there any unexpected failures?
- What was the actual cost vs. estimate?
- What improvements should we make?

---

## Example: Running World Cup Test

```bash
# 1. Pre-warm infrastructure
cd /home/user/ruvector/src/burst-scaling
npm run build
node dist/burst-predictor.js --event "World Cup Final" --time "2026-07-15T18:00:00Z"

# 2. Deploy load generators
cd /home/user/ruvector/benchmarks
npm run deploy:generators

# 3. Run scenario
npm run scenario:worldcup -- \
  --regions "europe-west3,southamerica-east1" \
  --peak-multiplier 50 \
  --duration "3h" \
  --enable-notifications

# 4. Monitor (separate terminal)
npm run dashboard

# 5. Collect results
npm run analyze -- --test-id "worldcup-2026-final-test"

# 6. Generate report
npm run report -- --test-id "worldcup-2026-final-test" --format pdf
```

---

## Troubleshooting

### High Error Rates
- Check: Database connection pool exhaustion
- Check: Network bandwidth limits
- Check: Rate limiting too aggressive
- Action: Scale up resources or enable degradation

### High Latency
- Check: Cold cache (low hit rate)
- Check: Database query performance
- Check: Network latency between regions
- Action: Warm caches, optimize queries, adjust routing

### Failed Auto-Scaling
- Check: GCP quotas and limits
- Check: Budget caps
- Check: IAM permissions
- Action: Request quota increase, adjust caps

### Cost Overruns
- Check: Instances not scaling down
- Check: Database overprovisioned
- Check: Excessive logging
- Action: Force scale-in, reduce logging verbosity

---

## Next Steps

1. **Run Quick Validation**: Ensure system is ready
2. **Run Standard Suite**: Comprehensive testing
3. **Schedule Burst Tests**: Coordinate with team (expensive!)
4. **Iterate Based on Results**: Tune thresholds and configurations
5. **Document Learnings**: Update runbooks and architecture docs

---

## References

- [Architecture Overview](/home/user/ruvector/docs/cloud-architecture/architecture-overview.md)
- [Scaling Strategy](/home/user/ruvector/docs/cloud-architecture/scaling-strategy.md)
- [Burst Scaling](/home/user/ruvector/src/burst-scaling/README.md)
- [Benchmarking Guide](/home/user/ruvector/benchmarks/README.md)
- [Operations Runbook](/home/user/ruvector/src/burst-scaling/RUNBOOK.md)

---

**Document Version**: 1.0
**Last Updated**: 2025-11-20
**Author**: RuVector Performance Team