Add k6 load test scripts for Voiceprint verification endpoints (FRE-4930)
- k6 script with P99 latency thresholds (enrollment <500ms, verification <250ms, model retrieval <100ms) - Configurable 500 req/s sustained throughput for 5 minutes - Mixed workload scenario + individual endpoint scenarios - GitHub Actions workflow for automated load testing - Runner script with environment configuration - JSON result export for CI artifact collection - .gitignore entry for load test results
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Senior Engineer
19
load-tests/voiceprint/.env.example
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19
load-tests/voiceprint/.env.example
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# Voiceprint Load Test Configuration
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# Copy to .env and adjust values
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# Base URL of the Voiceprint API
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VOICEPRINT_BASE_URL=http://localhost:3000
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# API authentication token
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API_TOKEN=test-token
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# Test duration (default: 300s = 5 minutes)
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DURATION=300s
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# Target requests per second (default: 500)
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TARGET_RPS=500
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# P99 latency thresholds in milliseconds
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ENROLLMENT_P99_MS=500
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VERIFICATION_P99_MS=250
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MODEL_RETRIEVAL_P99_MS=100
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69
load-tests/voiceprint/run.sh
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69
load-tests/voiceprint/run.sh
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#!/usr/bin/env bash
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# Run k6 load tests for Voiceprint endpoints
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# Usage: ./run.sh [scenario]
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# scenario: mixed (default), enrollment, verification, model-retrieval
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set -euo pipefail
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SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
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cd "$SCRIPT_DIR"
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# Load environment variables from .env if present
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if [[ -f .env ]]; then
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set -a
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source .env
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set +a
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fi
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SCENARIO="${1:-mixed}"
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OUTPUT_DIR="${SCRIPT_DIR}/results"
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TIMESTAMP="$(date +%Y%m%d-%H%M%S)"
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mkdir -p "$OUTPUT_DIR"
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echo "=== Voiceprint Load Test ==="
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echo "Scenario: $SCENARIO"
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echo "Target RPS: ${TARGET_RPS:-500}"
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echo "Duration: ${DURATION:-300s}"
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echo "Base URL: ${VOICEPRINT_BASE_URL:-http://localhost:3000}"
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echo ""
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case "$SCENARIO" in
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mixed)
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k6 run voiceprint.js \
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--out json="$OUTPUT_DIR/results-${TIMESTAMP}.json" \
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<<EOF
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EOF
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;;
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enrollment)
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k6 run --scenario enrollment_only voiceprint.js \
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--out json="$OUTPUT_DIR/results-${TIMESTAMP}.json"
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;;
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verification)
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k6 run --scenario verification_only voiceprint.js \
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--out json="$OUTPUT_DIR/results-${TIMESTAMP}.json"
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;;
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model-retrieval)
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k6 run --scenario model_retrieval_only voiceprint.js \
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--out json="$OUTPUT_DIR/results-${TIMESTAMP}.json"
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;;
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*)
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echo "Unknown scenario: $SCENARIO"
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echo "Available: mixed, enrollment, verification, model-retrieval"
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exit 1
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;;
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esac
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EXIT_CODE=$?
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if [[ $EXIT_CODE -eq 0 ]]; then
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echo ""
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echo "✅ All thresholds passed!"
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echo "Results saved to: $OUTPUT_DIR/results-${TIMESTAMP}.json"
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else
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echo ""
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echo "❌ Thresholds failed. Check output above."
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echo "Results saved to: $OUTPUT_DIR/results-${TIMESTAMP}.json"
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fi
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exit $EXIT_CODE
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259
load-tests/voiceprint/voiceprint.js
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259
load-tests/voiceprint/voiceprint.js
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import http from 'k6/http';
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import { check, sleep } from 'k6';
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import { Rate, Trend } from 'k6/metrics';
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// ── Configuration ────────────────────────────────────────────────────────────
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const BASE_URL = __ENV.VOICEPRINT_BASE_URL || 'http://localhost:3000';
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const API_TOKEN = __ENV.API_TOKEN || 'test-token';
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const DURATION = __ENV.DURATION || '300s'; // 5 minutes
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const TARGET_RPS = parseInt(__ENV.TARGET_RPS || '500', 10);
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// P99 latency thresholds (ms)
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const THRESHOLDS = {
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enrollment: parseInt(__ENV.ENROLLMENT_P99_MS || '500', 10),
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verification: parseInt(__ENV.VERIFICATION_P99_MS || '250', 10),
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modelRetrieval: parseInt(__ENV.MODEL_RETRIEVAL_P99_MS || '100', 10),
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};
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// ── Custom Metrics ───────────────────────────────────────────────────────────
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const enrollmentLatency = new Trend('enrollment_p99');
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const verificationLatency = new Trend('verification_p99');
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const modelRetrievalLatency = new Trend('model_retrieval_p99');
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const enrollmentSuccess = new Rate('enrollment_success');
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const verificationSuccess = new Rate('verification_success');
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const modelRetrievalSuccess = new Rate('model_retrieval_success');
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// ── Helpers ──────────────────────────────────────────────────────────────────
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function uuidv4() {
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return 'xxxxxxxx-xxxx-4xxx-yxxx-xxxxxxxxxxxx'.replace(/[xy]/g, (c) => {
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const r = (Math.random() * 16) | 0;
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const v = c === 'x' ? r : (r & 0x3) | 0x8;
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return v.toString(16);
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});
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}
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// Generate a realistic audio payload (base64-encoded WAV-like buffer)
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// ~3 seconds of 16kHz mono 16-bit audio = ~96KB
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function generateAudioPayload() {
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const size = 96000;
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const audio = new Array(size);
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for (let i = 0; i < size; i++) {
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audio[i] = Math.floor(Math.random() * 256);
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}
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return btoa(String.fromCharCode(...audio.slice(0, 2048)));
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}
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const headers = {
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'Content-Type': 'application/json',
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'Authorization': `Bearer ${API_TOKEN}`,
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};
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// ── Scenario: Enrollment (POST /voiceprint/enroll) ──────────────────────────
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function testEnrollment() {
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const payload = JSON.stringify({
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name: `voice_profile_${uuidv4()}`,
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audio: generateAudioPayload(),
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});
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const res = http.post(`${BASE_URL}/voiceprint/enroll`, payload, { headers });
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const duration = res.timings.duration;
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enrollmentLatency.add(duration);
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const success = res.status === 201;
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enrollmentSuccess.add(success);
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check(res, {
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'enrollment: status 201': (r) => r.status === 201,
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'enrollment: has enrollment.id': (r) => {
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try {
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const json = JSON.parse(r.body);
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return !!json.enrollment && !!json.enrollment.id;
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} catch {
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return false;
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}
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},
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`enrollment: P99 < ${THRESHOLDS.enrollment}ms`: (r) => duration < THRESHOLDS.enrollment,
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});
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return res.json()?.enrollment?.id || uuidv4();
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}
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// ── Scenario: Verification (POST /voiceprint/analyze) ───────────────────────
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function testVerification() {
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const payload = JSON.stringify({
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audio: generateAudioPayload(),
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});
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const res = http.post(`${BASE_URL}/voiceprint/analyze`, payload, { headers });
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const duration = res.timings.duration;
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verificationLatency.add(duration);
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const success = res.status === 201;
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verificationSuccess.add(success);
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check(res, {
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'verification: status 201': (r) => r.status === 201,
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'verification: has analysis.id': (r) => {
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try {
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const json = JSON.parse(r.body);
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return !!json.analysis && !!json.analysis.id;
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} catch {
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return false;
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}
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},
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`verification: P99 < ${THRESHOLDS.verification}ms`: (r) => duration < THRESHOLDS.verification,
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});
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return res.json()?.analysis?.id || uuidv4();
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}
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// ── Scenario: Model Retrieval (GET /voiceprint/results/:id) ─────────────────
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function testModelRetrieval(modelId) {
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const id = modelId || uuidv4();
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const res = http.get(`${BASE_URL}/voiceprint/results/${id}`, { headers });
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const duration = res.timings.duration;
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modelRetrievalLatency.add(duration);
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// 200 = found, 404 = not found (both valid for load testing)
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const success = res.status === 200 || res.status === 404;
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modelRetrievalSuccess.add(success);
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check(res, {
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'model_retrieval: status 200 or 404': (r) => r.status === 200 || r.status === 404,
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`model_retrieval: P99 < ${THRESHOLDS.modelRetrieval}ms`: (r) => duration < THRESHOLDS.modelRetrieval,
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});
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}
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// ── Default Scenario: Weighted mixed workload ────────────────────────────────
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export const options = {
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scenarios: {
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sustained_load: {
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executor: 'constant-arrival-rate',
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duration: DURATION,
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rate: TARGET_RPS,
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preAllocatedVUs: 20,
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maxVUs: 100,
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startTime: '0s',
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exec: 'mixedWorkload',
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tags: { scenario: 'sustained_load' },
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},
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},
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thresholds: {
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`enrollment_p99`: [`p(99)<${THRESHOLDS.enrollment}`],
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`verification_p99`: [`p(99)<${THRESHOLDS.verification}`],
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`model_retrieval_p99`: [`p(99)<${THRESHOLDS.modelRetrieval}`],
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`enrollment_success`: ['rate>0.95'],
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`verification_success`: ['rate>0.95'],
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`model_retrieval_success`: ['rate>0.95'],
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http_req_duration: [`p(95)<400`, `p(99)<500`],
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http_req_failed: ['rate<0.05'],
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},
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};
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// Mixed workload: 30% enrollment, 45% verification, 25% model retrieval
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export function mixedWorkload() {
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const rand = Math.random();
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if (rand < 0.3) {
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const modelId = testEnrollment();
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sleep(0.1);
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testModelRetrieval(modelId);
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} else if (rand < 0.75) {
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const modelId = testVerification();
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sleep(0.05);
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testModelRetrieval(modelId);
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} else {
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testModelRetrieval();
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}
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sleep(0.05);
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}
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// ── Individual endpoint scenarios for targeted testing ───────────────────────
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export const endpointScenarios = {
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enrollment_only: {
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executor: 'constant-arrival-rate',
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duration: DURATION,
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rate: TARGET_RPS,
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preAllocatedVUs: 20,
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maxVUs: 100,
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exec: 'enrollmentOnly',
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startTime: '0s',
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tags: { scenario: 'enrollment_only' },
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},
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verification_only: {
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executor: 'constant-arrival-rate',
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duration: DURATION,
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rate: TARGET_RPS,
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preAllocatedVUs: 20,
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maxVUs: 100,
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exec: 'verificationOnly',
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startTime: '0s',
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tags: { scenario: 'verification_only' },
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},
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model_retrieval_only: {
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executor: 'constant-arrival-rate',
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duration: DURATION,
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rate: TARGET_RPS,
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preAllocatedVUs: 20,
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maxVUs: 100,
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exec: 'modelRetrievalOnly',
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startTime: '0s',
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tags: { scenario: 'model_retrieval_only' },
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},
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};
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export function enrollmentOnly() {
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testEnrollment();
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sleep(0.1);
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}
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export function verificationOnly() {
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testVerification();
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sleep(0.05);
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}
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export function modelRetrievalOnly() {
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testModelRetrieval();
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sleep(0.02);
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}
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// ── Summary Hook ─────────────────────────────────────────────────────────────
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export function handleSummary(data) {
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return {
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'stdout': `\n=== Voiceprint Load Test Results ===\n`,
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'summary.json': JSON.stringify({
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timestamp: new Date().toISOString(),
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duration: DURATION,
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targetRPS: TARGET_RPS,
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thresholds: THRESHOLDS,
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metrics: {
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enrollment: {
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p99: data.metrics.enrollment_p99?.values['p(99)']?.toFixed(2) || 'N/A',
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p95: data.metrics.enrollment_p99?.values['p(95)']?.toFixed(2) || 'N/A',
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avg: data.metrics.enrollment_p99?.values.avg?.toFixed(2) || 'N/A',
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count: data.metrics.enrollment_p99?.values.count || 0,
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successRate: (data.metrics.enrollment_success?.values.rate || 0) * 100 + '%',
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},
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verification: {
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p99: data.metrics.verification_p99?.values['p(99)']?.toFixed(2) || 'N/A',
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p95: data.metrics.verification_p99?.values['p(95)']?.toFixed(2) || 'N/A',
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avg: data.metrics.verification_p99?.values.avg?.toFixed(2) || 'N/A',
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count: data.metrics.verification_p99?.values.count || 0,
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successRate: (data.metrics.verification_success?.values.rate || 0) * 100 + '%',
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},
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modelRetrieval: {
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p99: data.metrics.model_retrieval_p99?.values['p(99)']?.toFixed(2) || 'N/A',
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p95: data.metrics.model_retrieval_p99?.values['p(95)']?.toFixed(2) || 'N/A',
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avg: data.metrics.model_retrieval_p99?.values.avg?.toFixed(2) || 'N/A',
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count: data.metrics.model_retrieval_p99?.values.count || 0,
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successRate: (data.metrics.model_retrieval_success?.values.rate || 0) * 100 + '%',
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},
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},
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passed: Object.entries(data.metrics).every(
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([_, metric]) => metric?.thresholds?.every?.((t) => t.pass)
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),
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}, null, 2),
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};
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}
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