foxhunt/AGENT_153_LOAD_TESTING_REPORT.md

Agent 153: Load Testing Validation Report

Date: 2025-10-11 Mission: Execute load and performance E2E tests to validate system throughput and latency under stress Test Duration: ~47 seconds total execution time

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Executive Summary

Overall Status: ⚠️ PARTIAL SUCCESS

• Tests Executed: 16 total (7 load tests + 7 validation tests + 2 data flow tests)
• Tests Passed: 11/16 (68.75%)
• Tests Failed: 5/16 (31.25%)
• Critical Blockers: JWT authentication failures, ML model unavailability, TSC timing issues

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Test Results by Suite

1. Performance Load Tests (performance_load_tests.rs)

Status: 5/7 PASSED (71.4%) Execution Time: 30.36 seconds

✅ Passing Tests (5)

1. test_concurrent_order_processing ✅

   • Concurrent users: 10
   • Orders per user: 10
   • Total orders: 100
   • Status: PASS

2. test_latency_percentiles ✅

   • Samples collected: 100
   • Query type: get_order_status
   • Status: PASS

3. test_market_data_processing_throughput ✅

   • Total ticks processed: 10,000
   • Symbols: 5 (AAPL, MSFT, GOOGL, TSLA, AMZN)
   • Status: PASS

4. test_order_submission_throughput ✅

   • Total orders: 100
   • Status: PASS

5. tests::test_high_volume_data_generation ✅

   • Unit test for data generation utility
   • Status: PASS

❌ Failing Tests (2)

1. test_ml_inference_performance ❌

   • Error: "No models available for ensemble prediction"
   • Root Cause: ML models not loaded/available in test environment
   • Impact: Cannot validate ML inference latency under load
   • Recommendation: Load ML models before test execution or use mock predictions

2. test_sustained_load ❌

   • Error: "Success rate should be above 95%, got 0.00%"
   • Root Cause: All get_portfolio_summary requests failed (likely JWT auth issue)
   • Test Duration: 30 seconds sustained load
   • Target Rate: 10 req/sec
   • Impact: Cannot validate sustained performance
   • Recommendation: Fix JWT authentication or mock portfolio service

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2. Performance Validation Tests (performance_validation_tests.rs)

Status: 6/7 PASSED (85.7%) Execution Time: 16.73 seconds

✅ Passing Tests (6)

1. test_critical_path_latency ✅

   • Type Creation P95: < 1μs (validated ✅)
   • Allocation P95: < 10μs (validated ✅)
   • Price Calculation P95: < 500ns (validated ✅)
   • E2E Simulation P95: < 50μs (validated ✅)
   • Jitter P95: < 10μs (validated ✅)
   • Status: PASS - All critical path requirements met

2. test_performance_regression ✅

   • Baseline comparison completed
   • No significant regressions detected (< 20% degradation threshold)
   • Status: PASS

3. test_resource_utilization ✅

   • Baseline allocations: 1,000
   • Stress allocations: 10,000
   • Leak test completed within 5 seconds
   • Status: PASS

4. test_throughput_scalability ✅

   • Single-thread ops/sec: > 100,000 ops/sec (validated ✅)
   • Sustained P95: < 100μs (validated ✅)
   • Overall Performance Score: > 70/100 (validated ✅)
   • Status: PASS

5. tests::test_percentile_empty ✅

   • Unit test for percentile calculation with empty input
   • Status: PASS

6. tests::test_workflow_result_creation ✅

   • Unit test for workflow result struct
   • Status: PASS

❌ Failing Tests (1)

1. tests::test_percentile_calculation ❌
   • Error: assertion failed: left == right (left: 9, right: 10)
   • Root Cause: Off-by-one error in percentile calculation for P95
   • Impact: Minor - calculation is close (90th vs 95th percentile)
   • Recommendation: Fix percentile index calculation in helper function

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3. Data Flow Performance Tests (data_flow_performance_tests.rs)

Status: 1/2 PASSED (50%) Execution Time: 2.67 seconds

✅ Passing Tests (1)

1. tests::test_realtime_data_ingestion ✅
   • Databento events: 1,000
   • News articles: 20
   • Feature extraction completed
   • Status: PASS

❌ Failing Tests (1)

1. tests::test_sub_50us_latency_validation ❌
   • Error: "TSC not reliable for sub-μs timing"
   • Root Cause: Time Stamp Counter (TSC) reliability check failed on this hardware
   • Impact: Cannot validate sub-50μs latency requirements
   • Recommendation: Use alternative high-resolution timing or skip TSC check

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Performance Metrics Summary

Latency Measurements

Metric	Target	Measured	Status
Type Creation P95	< 1μs	< 1μs	✅ PASS
Price Calculation P95	< 500ns	< 500ns	✅ PASS
Allocation P95	< 10μs	< 10μs	✅ PASS
E2E Simulation P95	< 50μs	< 50μs	✅ PASS
Jitter P95	< 10μs	< 10μs	✅ PASS
Sustained P95	< 100μs	< 100μs	✅ PASS

Throughput Measurements

Metric	Target	Measured	Status
Single-thread ops/sec	> 100,000	> 100,000	✅ PASS
Order submission	> 10/sec	Unknown	⚠️ NOT MEASURED
Market data processing	> 1,000 ticks/sec	Unknown	⚠️ NOT MEASURED
Sustained load success rate	> 95%	0%	❌ FAIL

Target Comparison (from CLAUDE.md)

Component	CLAUDE.md Target	Measured	Status
Authentication	< 10μs	Not measured	⚠️ SKIP
Order Matching	< 50μs	Not measured	⚠️ SKIP
Order Submission	< 100ms	Not measured	⚠️ SKIP
PostgreSQL Inserts	2,979/sec	Not measured	⚠️ SKIP
API Gateway Proxy	< 1ms	Not measured	⚠️ SKIP

Note: Most E2E integration targets were not measured due to test failures and service unavailability.

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Infrastructure Status

Service Health (from docker-compose)

Service	Status	Port
PostgreSQL	✅ HEALTHY	5432
Redis	✅ HEALTHY	6379
API Gateway	✅ HEALTHY	50051
Trading Service	✅ HEALTHY	50052

Critical Issues Identified

1. Backtesting Service Connection Failures

   • Error: "h2 protocol error: http2 error"
   • Frequency: Every 10-20 seconds
   • Impact: API Gateway cannot health check backtesting service
   • Root Cause: Port 50053 connection issues or service not running

2. JWT Authentication Failures

   • Error: "JWT validation failed: InvalidSignature"
   • Location: API Gateway auth interceptor
   • Impact: All authenticated requests failing (sustained load test = 0% success)
   • Root Cause: JWT secret mismatch between E2E framework and API Gateway
   • Expected issuer: foxhunt-api-gateway
   • Expected audience: foxhunt-services

3. ML Models Not Available

   • Error: "No models available for ensemble prediction"
   • Impact: ML inference performance tests cannot run
   • Root Cause: ML training service not running or models not loaded

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Bottlenecks Identified

Critical Bottlenecks

1. JWT Authentication (CRITICAL)

   • 100% request failure rate for authenticated endpoints
   • Blocking sustained load testing
   • Fix Required: Align JWT secrets between E2E framework and services

2. ML Model Loading (HIGH)

   • ML inference tests cannot execute
   • No validation of ML performance under load
   • Fix Required: Pre-load models or implement mock predictions

Performance Bottlenecks

None identified - all measured latency targets were met where tests succeeded.

System Limitations

1. TSC Timing Reliability (MEDIUM)

   • Sub-microsecond timing not reliable on this hardware
   • Blocks sub-50μs validation tests
   • Workaround: Use alternative timing mechanism or relax requirements

2. Backtesting Service Connectivity (MEDIUM)

   • Continuous health check failures
   • May impact overall system reliability
   • Fix Required: Restart backtesting service or fix gRPC configuration

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Recommendations

Immediate Actions (Fix Test Failures)

1. Fix JWT Authentication (Priority 1)

   # Verify JWT_SECRET matches across all services
   echo $JWT_SECRET
   # Update .env or E2E framework to use same secret
   

2. Load ML Models (Priority 2)

   # Start ML training service
   cargo run -p ml_training_service &
   # Or implement mock predictions in E2E framework
   

3. Fix Percentile Calculation (Priority 3)

   // In performance_validation_tests.rs line 52
   let index = ((p / 100.0) * (sorted.len() - 1) as f64).round() as usize;
   

4. Fix TSC Timing Check (Priority 4)

   // Make TSC check non-fatal or use alternative timing
   if !is_tsc_reliable() {
       warn!("TSC not reliable, using fallback timing");
       // Use std::time::Instant instead
   }
   

Short-term Optimizations (1-2 weeks)

1. Implement Mock Services

   • Mock ML predictions for performance tests
   • Mock portfolio service for sustained load tests
   • Enables testing without full infrastructure

2. Add Detailed Metrics Collection

   • Record P50, P95, P99 for all operations
   • Export metrics to Prometheus/InfluxDB
   • Create Grafana dashboards for real-time monitoring

3. Expand Test Coverage

   • Add tests for API Gateway proxy latency
   • Add tests for PostgreSQL insert throughput
   • Add tests for concurrent trading operations

Long-term Enhancements (3-6 months)

1. Load Testing Infrastructure

   • Deploy dedicated load testing environment
   • Add k6 or Locust for distributed load generation
   • Implement continuous performance regression testing

2. Advanced Performance Analysis

   • Add flame graphs for CPU profiling
   • Implement distributed tracing (Jaeger/Zipkin)
   • Add memory profiling with valgrind/heaptrack

3. Automated Performance Benchmarking

   • CI/CD integration for performance tests
   • Automated alerts on performance regression
   • Historical performance trend analysis

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Test Execution Details

Command Executed

# Performance load tests
cargo test -p foxhunt_e2e --test performance_load_tests -- --nocapture --test-threads=1

# Performance validation tests
cargo test -p foxhunt_e2e --test performance_validation_tests -- --nocapture --test-threads=1

# Data flow performance tests
cargo test -p foxhunt_e2e --test data_flow_performance_tests -- --nocapture --test-threads=1

Test Environment

• Platform: Linux 6.14.0-33-generic
• Rust Version: stable-x86_64-unknown-linux-gnu
• Test Profile: optimized + debuginfo
• Test Threads: 1 (serial execution)
• Working Directory: /home/jgrusewski/Work/foxhunt

Test Files

1. /home/jgrusewski/Work/foxhunt/tests/e2e/tests/performance_load_tests.rs
2. /home/jgrusewski/Work/foxhunt/tests/e2e/tests/performance_validation_tests.rs
3. /home/jgrusewski/Work/foxhunt/tests/e2e/tests/data_flow_performance_tests.rs

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Conclusion

Overall Assessment

The load testing validation reveals a mixed result:

Strengths:

• ✅ Critical path latency requirements VALIDATED (< 50μs E2E simulation)
• ✅ Throughput scalability VALIDATED (> 100K ops/sec single-thread)
• ✅ Resource utilization HEALTHY (no memory leaks detected)
• ✅ Performance consistency GOOD (jitter < 10μs)

Weaknesses:

• ❌ JWT authentication BLOCKING all authenticated endpoints (0% success rate)
• ❌ ML models UNAVAILABLE (cannot validate ML inference performance)
• ❌ Sustained load testing FAILED (0% success rate due to auth)
• ❌ Sub-50μs validation BLOCKED by TSC timing issues

Production Readiness: 68.75%

Recommendation: NOT READY FOR PRODUCTION DEPLOYMENT

Blocking Issues:

1. JWT authentication must be fixed (critical)
2. ML models must be loaded (high priority)
3. Sustained load testing must pass (high priority)

Timeline to Production Ready:

• Immediate fixes (1-2 days): JWT auth, ML models, percentile calculation
• Validation testing (1 day): Re-run all tests after fixes
• Expected Production Ready: 2-3 days from now

Next Steps

1. Fix JWT authentication (Agent 154 or emergency fix)
2. Load ML models (Agent 155 or emergency fix)
3. Re-run load tests (Agent 156 validation)
4. Deploy to production (once all tests pass)

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Report Generated: 2025-10-11 Agent: 153 Status: COMPLETE