foxhunt/testing/service-load

Load Tests - Trading Service Throughput Validation

Overview

Comprehensive load testing suite for validating trading service throughput and performance under various load scenarios.

Test Scenarios

1. Sustained Load (10,000 orders/sec for 60s)

• Target: 10,000 orders/second sustained throughput
• Duration: 60 seconds
• Concurrent Clients: 100
• Validates: System stability under sustained load

2. Peak Burst (50,000 orders/sec for 10s)

• Target: 50,000 orders/second peak burst
• Duration: 10 seconds
• Concurrent Clients: 500
• Validates: System behavior under peak load spikes

3. Market Data Streaming (1M updates)

• Target: 1,000,000 concurrent market data updates
• Streams: 1,000 concurrent streams
• Duration: 30 seconds
• Validates: Streaming infrastructure capacity

4. Connection Pool Saturation (1,000 clients)

• Target: 1,000 concurrent clients
• Requests per Client: 100
• Validates: Connection pool management and resource limits

Usage

Run All Tests

cargo run -p load_tests --release -- --scenario all

Run Individual Scenarios

# Sustained load
cargo run -p load_tests --release -- --scenario sustained

# Peak burst
cargo run -p load_tests --release -- --scenario burst

# Streaming
cargo run -p load_tests --release -- --scenario streaming

# Connection pool
cargo run -p load_tests --release -- --scenario pool

Custom Configuration

cargo run -p load_tests --release -- \
  --scenario sustained \
  --url http://trading-service:50052 \
  --output /path/to/report.md \
  --verbose

Metrics Collected

Throughput Metrics

• Requests per second (sustained and peak)
• Total requests processed
• Success/failure rates

Latency Distribution

• P50 (median) latency
• P95 latency
• P99 latency
• Maximum latency

Resource Usage

• Memory consumption (average)
• Connection pool utilization
• Stream management overhead

Output Report

Test results are saved as Markdown reports containing:

• Executive summary
• Detailed metrics breakdown
• Latency distribution charts
• Resource usage analysis
• Performance recommendations

Default output: /tmp/WAVE_120_AGENT_5_LOAD_TESTING.md

Prerequisites

1. Trading Service Running:

   docker-compose up -d trading_service
   # OR
   cargo run -p trading_service
   

2. Database Available:

   docker-compose up -d postgres redis
   

3. Sufficient System Resources:

   • 8GB+ RAM recommended
   • Multi-core CPU for parallel clients
   • Network bandwidth for 50k+ req/sec

Architecture

Components

• Scenarios: Test scenario implementations

  • sustained_load.rs: 10k orders/sec for 60s
  • burst_load.rs: 50k orders/sec for 10s
  • streaming_load.rs: 1M market data updates
  • pool_saturation.rs: 1000 concurrent clients
  • comprehensive.rs: All scenarios sequentially

• Clients: gRPC client implementations

  • trading_client.rs: Trading service client wrapper

• Metrics: Performance measurement

  • metrics.rs: HDR histogram-based metrics collection
  • monitor.rs: System resource monitoring

Load Generation Pattern

// Concurrent client pattern
for client_id in 0..NUM_CLIENTS {
    tokio::spawn(async move {
        let client = TradingClient::connect(url).await?;

        // Submit orders with rate limiting
        while duration_remaining {
            client.submit_order(...).await?;
            tokio::time::sleep(rate_limit).await;
        }
    });
}

Performance Targets

Sustained Load

• ✅ Throughput: ≥9,000 req/sec
• ✅ Error Rate: <1%
• ✅ P95 Latency: <10ms

Peak Burst

• ✅ Throughput: ≥40,000 req/sec
• ✅ Error Rate: <5%
• ✅ P99 Latency: <50ms

Streaming

• ✅ Updates: ≥900k received
• ✅ Concurrent Streams: 1000
• ✅ Stream Stability: <1% failures

Connection Pool

• ✅ Concurrent Connections: 1000
• ✅ Error Rate: <5%
• ✅ P99 Latency: <100ms

Troubleshooting

Connection Refused

# Verify trading service is running
grpc_health_probe -addr=localhost:50052

High Error Rates

• Check system resource limits (ulimit, file descriptors)
• Verify database connection pool size
• Review trading service logs for errors

Memory Issues

• Reduce concurrent clients
• Enable connection pooling
• Check for memory leaks in trading service

Integration with CI/CD

# .github/workflows/load-test.yml
- name: Run Load Tests
  run: |
    docker-compose up -d
    cargo run -p load_tests --release -- --scenario all

- name: Upload Report
  uses: actions/upload-artifact@v3
  with:
    name: load-test-report
    path: /tmp/WAVE_120_AGENT_5_LOAD_TESTING.md

Wave 120 Objectives

Agent 5 Tasks:

• ✅ Create load_tests package
• ✅ Implement 4 throughput scenarios
• ✅ Measure latency, throughput, error rates
• ✅ Monitor memory usage
• ⏳ Run tests against live service
• ⏳ Generate performance report

Expected Outcomes:

• Validate 10k orders/sec sustained capacity
• Confirm 50k orders/sec peak burst handling
• Verify 1M concurrent stream updates
• Validate 1000+ concurrent client support