foxhunt/docs/WAVE77_AGENT8_LOAD_TEST_RESULTS.md

WAVE 77 AGENT 8: Load Testing Results & Architecture Gap Analysis

Agent: Agent 8 - Load Testing Execution Date: 2025-10-03 Status: ARCHITECTURE GAP IDENTIFIED - Tooling Required

---

Executive Summary

FINDING: Load testing could not be executed due to architecture mismatch between available tooling and actual service implementation.

ISSUE:

• Services expose pure gRPC APIs (ports 50051, 50053)
• Existing load test framework targets HTTP REST APIs
• No gRPC load testing tools available (ghz not installed, go not available)
• API Gateway (Agent 6) still building - HTTP/gRPC translation layer not ready

RECOMMENDATION: Implement gRPC-native load testing infrastructure before production deployment.

---

Current Service Architecture

Services Running

✅ trading_service:
   - gRPC: localhost:50051
   - Health: localhost:8080/health (HTTP only)

✅ ml_training_service:
   - gRPC: localhost:50053

⏳ api_gateway:
   - Building (Agent 6 in progress)
   - Will provide HTTP→gRPC translation

Protocol Analysis

┌─────────────────────────────────────────────────────┐
│ CURRENT STATE                                       │
├─────────────────────────────────────────────────────┤
│                                                     │
│  Load Test Framework                               │
│  (HTTP-based)                                      │
│       │                                            │
│       │ POST /trading/orders                       │
│       │ GET /trading/positions                     │
│       ▼                                            │
│   ❌ No HTTP API available                         │
│                                                     │
│  Services Expose:                                  │
│    ✓ gRPC (50051, 50053)                          │
│    ✓ Health HTTP (8080) - limited                 │
│    ✗ REST API endpoints                           │
│                                                     │
└─────────────────────────────────────────────────────┘

---

Existing Load Test Framework Analysis

Location

/home/jgrusewski/Work/foxhunt/services/api_gateway/load_tests/

Framework Capabilities

// Cargo.toml dependencies
- reqwest: HTTP client
- tonic: gRPC support (AVAILABLE but unused)
- hdrhistogram: Latency metrics
- prometheus: Metrics collection
- sysinfo: System monitoring

Test Scenarios Implemented

1. Normal Load: 1K clients, 60s duration
2. Spike Load: 0→10K ramp-up
3. Sustained Load: 100 clients, 24h
4. Stress Test: Incremental until failure

Current Implementation Issues

// File: authenticated_client.rs (lines 54-67)
pub async fn submit_order(&self, client_id: usize, order: TestOrder) -> Result<RequestMetric> {
    let start = Instant::now();

    let result = self.client
        .post(format!("{}/trading/orders", self.gateway_url))  // ❌ HTTP endpoint
        .header("Authorization", format!("Bearer {}", self.jwt_token))
        .json(&order)
        .send()
        .await;
    // ...
}

// ISSUE: Expects HTTP REST API, but services only expose gRPC

---

Production gRPC Load Testing Strategy

Option 1: ghz (Recommended for Quick Testing)

Tool: github.com/bojand/ghz

Installation:

# Requires Go
go install github.com/bojand/ghz/cmd/ghz@latest

Usage:

# Normal Load Test (1K connections, 60s)
ghz --insecure \
    --proto=tli/proto/trading.proto \
    --call=trading.TradingService/GetPositions \
    --connections=1000 \
    --concurrency=1000 \
    --duration=60s \
    --rps=0 \
    --data='{"account_id":"test-account"}' \
    --metadata='{"authorization":"Bearer TOKEN"}' \
    localhost:50051

# Spike Test (10K connections)
ghz --insecure \
    --proto=tli/proto/trading.proto \
    --call=trading.TradingService/GetPositions \
    --connections=10000 \
    --concurrency=10000 \
    --duration=30s \
    --rps=0 \
    localhost:50051

# Expected Output:
Summary:
  Count:        120000
  Total:        60.05 s
  Slowest:      15.2 ms
  Fastest:      0.8 ms
  Average:      3.2 ms
  Requests/sec: 2000.0

Response time histogram:
  0.8 [1]     |
  2.3 [45000] |∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎
  3.8 [50000] |∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎
  5.3 [20000] |∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎
  ...

Latency distribution:
  10% in 1.5 ms
  25% in 2.1 ms
  50% in 2.8 ms
  75% in 3.9 ms
  90% in 5.2 ms
  95% in 7.1 ms
  99% in 12.3 ms

Pros:

• Production-ready gRPC load testing
• Detailed latency histograms
• Native proto support
• Connection pooling
• Concurrent request control

Cons:

• Requires Go installation
• Not integrated with existing framework

---

Option 2: Enhance Existing Framework (Recommended for Integration)

Approach: Add gRPC client support to existing Rust load test framework.

Implementation:

// File: services/api_gateway/load_tests/src/clients/grpc_client.rs (NEW)

use tonic::transport::Channel;
use tonic::metadata::MetadataValue;
use std::time::Instant;
use anyhow::Result;

// Import generated proto code
use trading_proto::trading_service_client::TradingServiceClient;
use trading_proto::{GetPositionsRequest, SubmitOrderRequest};

pub struct GrpcAuthenticatedClient {
    trading_client: TradingServiceClient<Channel>,
    jwt_token: String,
}

impl GrpcAuthenticatedClient {
    pub async fn new(grpc_url: String, jwt_token: String) -> Result<Self> {
        let channel = Channel::from_shared(grpc_url)?
            .connect()
            .await?;

        let trading_client = TradingServiceClient::new(channel);

        Ok(Self {
            trading_client,
            jwt_token,
        })
    }

    pub async fn get_positions(&mut self, client_id: usize) -> Result<RequestMetric> {
        let start = Instant::now();

        let mut request = tonic::Request::new(GetPositionsRequest {
            account_id: Some(format!("test-account-{}", client_id)),
            symbol: None,
        });

        // Add JWT to metadata
        let token: MetadataValue<_> = format!("Bearer {}", self.jwt_token)
            .parse()?;
        request.metadata_mut().insert("authorization", token);

        let result = self.trading_client.get_positions(request).await;
        let latency = start.elapsed();

        let status = match result {
            Ok(_) => RequestStatus::Success,
            Err(e) => {
                if e.code() == tonic::Code::Unavailable {
                    RequestStatus::CircuitBreakerOpen
                } else if e.code() == tonic::Code::ResourceExhausted {
                    RequestStatus::RateLimited
                } else {
                    RequestStatus::Error
                }
            }
        };

        Ok(RequestMetric {
            timestamp: chrono::Utc::now(),
            client_id,
            service: ServiceType::Trading,
            latency,
            status,
            error_type: None,
        })
    }

    pub async fn submit_order(&mut self, client_id: usize, order: TestOrder) -> Result<RequestMetric> {
        let start = Instant::now();

        let mut request = tonic::Request::new(SubmitOrderRequest {
            symbol: order.symbol,
            side: match order.side.as_str() {
                "buy" => 1,  // OrderSide::Buy
                "sell" => 2, // OrderSide::Sell
                _ => 0,
            },
            quantity: order.quantity,
            order_type: match order.order_type.as_str() {
                "market" => 1,  // OrderType::Market
                "limit" => 2,   // OrderType::Limit
                _ => 0,
            },
            price: None,
            stop_price: None,
            account_id: format!("test-account-{}", client_id),
            metadata: std::collections::HashMap::new(),
        });

        let token: MetadataValue<_> = format!("Bearer {}", self.jwt_token).parse()?;
        request.metadata_mut().insert("authorization", token);

        let result = self.trading_client.submit_order(request).await;
        let latency = start.elapsed();

        let status = match result {
            Ok(_) => RequestStatus::Success,
            Err(e) => {
                if e.code() == tonic::Code::Unavailable {
                    RequestStatus::CircuitBreakerOpen
                } else if e.code() == tonic::Code::ResourceExhausted {
                    RequestStatus::RateLimited
                } else {
                    RequestStatus::Error
                }
            }
        };

        Ok(RequestMetric {
            timestamp: chrono::Utc::now(),
            client_id,
            service: ServiceType::Trading,
            latency,
            status,
            error_type: None,
        })
    }
}

Required Changes:

1. Add proto compilation to build.rs
2. Create grpc_client.rs module
3. Update normal_load.rs to support both HTTP and gRPC
4. Add CLI flag: --protocol [http|grpc]

Pros:

• Integrated with existing metrics/reporting
• Reuses test scenarios
• No external dependencies
• Consistent reporting format

Cons:

• Requires code changes
• Proto compilation setup
• More development effort

---

Option 3: Custom Rust gRPC Load Tester (NEW Project)

Approach: Create standalone gRPC load testing tool.

Project Structure:

services/grpc_load_tester/
├── Cargo.toml
├── build.rs              # Proto compilation
├── proto/                # Symlink to tli/proto/
└── src/
    ├── main.rs           # CLI and orchestration
    ├── client.rs         # gRPC client pool
    ├── metrics.rs        # HDR histogram, percentiles
    └── scenarios.rs      # Load patterns

Cargo.toml:

[package]
name = "grpc_load_tester"
version = "0.1.0"
edition = "2021"

[dependencies]
tokio = { version = "1.42", features = ["full"] }
tonic = { version = "0.14", features = ["transport"] }
prost = "0.13"
hdrhistogram = "7.5"
clap = { version = "4.5", features = ["derive"] }
anyhow = "1.0"
tracing = "0.1"
tracing-subscriber = "0.3"

[build-dependencies]
tonic-build = "0.14"

Usage:

# Build
cargo build --release -p grpc_load_tester

# Run normal load
./target/release/grpc_load_tester normal \
    --endpoint localhost:50051 \
    --clients 1000 \
    --duration 60

# Run spike load
./target/release/grpc_load_tester spike \
    --endpoint localhost:50051 \
    --target-clients 10000 \
    --ramp-up 10 \
    --sustain 60

Pros:

• Clean separation of concerns
• Focused on gRPC load testing
• Reusable across projects
• Fast development

Cons:

• Duplicate effort (metrics, reporting)
• New codebase to maintain

---

Expected Performance Targets

Based on Wave 76 Auth Pipeline Validation

Authentication Pipeline (Wave 76 Agent 11):

• P50: 1.8μs
• P95: 2.5μs
• P99: 3.1μs ✅
• Throughput: >100K req/s

Production Targets for Full Request Cycle:

Component Breakdown:
├─ Auth Pipeline:        3μs    (validated)
├─ gRPC Overhead:       2μs    (estimated)
├─ Service Logic:       3μs    (estimated)
├─ Database Query:      1μs    (HFT-optimized pool)
└─ Serialization:       1μs    (estimated)
                       ─────
Total Expected:        10μs

Target Metrics:
├─ P50 Latency:       <5μs
├─ P95 Latency:       <8μs
├─ P99 Latency:       <10μs
├─ Throughput:        >100K req/s
└─ Error Rate:        <0.1%

Load Test Scenarios

Scenario 1: Normal Load

Clients: 1,000
Duration: 60s
Expected:
  - P99 Latency: <10μs
  - Throughput: 100K-200K req/s
  - Error Rate: <0.1%
  - CPU Usage: <70%
  - Memory: Stable

Scenario 2: Spike Load

Ramp: 0→10,000 clients in 10s
Sustain: 60s at 10K clients
Expected:
  - Initial P99: <10μs
  - Spike P99: <20μs (degradation acceptable)
  - Recovery: <5s back to <10μs
  - Error Rate: <1% during spike
  - No memory leaks

---

Fallback: HTTP Load Test via API Gateway

Current State: API Gateway building (Agent 6)

When Available:

cd /home/jgrusewski/Work/foxhunt

# Wait for API Gateway to complete
# Expected: localhost:50050 (HTTP→gRPC proxy)

# Run existing HTTP load tests
./target/release/load_test_runner normal \
    --gateway-url http://localhost:50050 \
    --num-clients 1000 \
    --duration-secs 60

# Generate report
ls -lh *_load_report.html

Limitations:

• Tests HTTP→gRPC translation overhead
• Doesn't measure pure gRPC performance
• Additional latency from HTTP conversion

Expected Additional Overhead:

Pure gRPC:           10μs P99
HTTP→gRPC Gateway:  +3-5μs
Total:              13-15μs P99

---

Immediate Action Items

Priority 1: Install gRPC Load Testing Tools

# Option A: Install ghz (if Go available)
go install github.com/bojand/ghz/cmd/ghz@latest

# Option B: Use Docker
docker run --rm -v $(pwd)/tli/proto:/proto \
    ghcr.io/bojand/ghz:latest \
    --insecure \
    --proto=/proto/trading.proto \
    --call=trading.TradingService/GetPositions \
    --connections=1000 \
    --duration=60s \
    --data='{"account_id":"test"}' \
    host.docker.internal:50051

Priority 2: Enhance Load Test Framework

# Add gRPC support to existing framework
cd /home/jgrusewski/Work/foxhunt/services/api_gateway/load_tests

# Update Cargo.toml
# Add build.rs for proto compilation
# Create grpc_client.rs
# Update scenarios to support --protocol flag

Priority 3: Wait for API Gateway

# Continue with HTTP-based testing when ready
# Less ideal but validates full stack

---

Architecture Recommendation

For Production Deployment:

┌─────────────────────────────────────────────────────────────┐
│ RECOMMENDED LOAD TESTING ARCHITECTURE                       │
├─────────────────────────────────────────────────────────────┤
│                                                             │
│  ┌───────────────┐                                         │
│  │  ghz (Quick)  │─────→ gRPC Services (Pure Performance) │
│  └───────────────┘                                         │
│                                                             │
│  ┌───────────────────────┐                                 │
│  │ Enhanced Load Tester  │                                 │
│  │  (HTTP + gRPC)        │───┬→ API Gateway (HTTP)         │
│  └───────────────────────┘   │                             │
│                               └→ gRPC Services (Direct)    │
│                                                             │
│  Use Cases:                                                │
│  ├─ ghz: Quick performance validation                      │
│  ├─ Enhanced: CI/CD integration, detailed reports          │
│  └─ Both: Comprehensive production readiness testing       │
│                                                             │
└─────────────────────────────────────────────────────────────┘

---

Conclusion

Current Status

❌ Load testing NOT executed - architecture mismatch

Root Cause

Services expose pure gRPC, existing framework targets HTTP REST

Impact

• Cannot validate P99 <10μs target
• Cannot validate 100K req/s throughput
• Cannot stress test before production
• Performance characteristics unknown

Resolution Path

1. Immediate (1 day): Install ghz, run basic gRPC load tests
2. Short-term (1 week): Enhance existing framework with gRPC support
3. Long-term: Integrate into CI/CD pipeline

Risk Assessment

MEDIUM RISK: Production deployment without load testing validation

Mitigation:

• Wave 76 validated auth pipeline at 3μs P99
• Architecture designed for <10μs target
• Can roll back if performance issues observed
• Recommend staged rollout with monitoring

---

Next Steps for Agent 9+

1. Install ghz OR wait for API Gateway
2. Execute baseline load tests
3. Collect P50/P95/P99 latencies
4. Validate against <10μs P99 target
5. Update this document with actual results

---

Document Status: ARCHITECTURE GAP IDENTIFIED Recommendation: DO NOT PROCEED TO PRODUCTION until load testing validation complete Priority: HIGH - Required before Wave 77 completion