881 lines
27 KiB
Rust
881 lines
27 KiB
Rust
/*!
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Performance Integration Tests
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Tests performance characteristics with SLA validation and scaling tests.
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This module validates the platform meets performance requirements under
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realistic production load conditions.
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## Test Categories
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1. **Latency SLA Validation**: P50, P95, P99 latency requirements
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2. **Throughput Scaling**: Requests per second scaling with resources
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3. **Memory Usage**: Memory efficiency under sustained load
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4. **GPU Utilization**: GPU efficiency and resource management
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5. **Concurrent Load**: Performance under concurrent requests
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6. **Resource Scaling**: Auto-scaling behavior and resource allocation
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7. **Performance Regression**: Detecting performance regressions
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## TDD Approach
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Each test establishes baseline performance metrics and validates:
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1. Performance meets defined SLAs
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2. Scaling behavior is predictable and efficient
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3. Resource utilization is optimal
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4. Performance degrades gracefully under stress
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5. No performance regressions from previous versions
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*/
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use anyhow::Result;
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use std::collections::BTreeMap;
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use std::sync::atomic::{AtomicU64, Ordering};
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use std::sync::Arc;
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use std::time::{Duration, Instant};
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use tokio::sync::Semaphore;
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use tokio::time::sleep;
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use tracing::{info, warn, debug};
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use parking_lot::RwLock;
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use crate::common::TestContext;
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/// Service Level Objectives for different operation types
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#[derive(Debug, Clone)]
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pub struct SloConfig {
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/// P50 latency target
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pub p50_latency_ms: u64,
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/// P95 latency target
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pub p95_latency_ms: u64,
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/// P99 latency target
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pub p99_latency_ms: u64,
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/// P999 latency target
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pub p999_latency_ms: u64,
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/// Minimum throughput (requests per second)
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pub min_throughput_rps: f64,
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/// Maximum error rate (0.0 to 1.0)
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pub max_error_rate: f64,
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/// Maximum memory growth per 1000 requests (MB)
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pub max_memory_growth_mb: u64,
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}
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impl Default for SloConfig {
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fn default() -> Self {
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Self {
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p50_latency_ms: 10,
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p95_latency_ms: 50,
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p99_latency_ms: 100,
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p999_latency_ms: 500,
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min_throughput_rps: 100.0,
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max_error_rate: 0.01,
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max_memory_growth_mb: 100,
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}
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}
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}
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impl SloConfig {
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/// SLO config for inference operations (stricter)
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pub fn inference() -> Self {
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Self {
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p50_latency_ms: 5,
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p95_latency_ms: 20,
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p99_latency_ms: 50,
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p999_latency_ms: 200,
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min_throughput_rps: 500.0,
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max_error_rate: 0.001,
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max_memory_growth_mb: 50,
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}
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}
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/// SLO config for batch operations (more lenient)
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pub fn batch() -> Self {
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Self {
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p50_latency_ms: 100,
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p95_latency_ms: 500,
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p99_latency_ms: 1000,
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p999_latency_ms: 5000,
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min_throughput_rps: 10.0,
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max_error_rate: 0.01,
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max_memory_growth_mb: 500,
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}
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}
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}
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/// Latency histogram for tracking percentiles
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#[derive(Debug, Default)]
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pub struct LatencyHistogram {
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samples: RwLock<Vec<Duration>>,
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}
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impl LatencyHistogram {
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pub fn new() -> Self {
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Self {
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samples: RwLock::new(Vec::new()),
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}
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}
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pub fn record(&self, latency: Duration) {
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self.samples.write().push(latency);
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}
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pub fn percentile(&self, p: f64) -> Option<Duration> {
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let mut samples = self.samples.read().clone();
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if samples.is_empty() {
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return None;
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}
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samples.sort();
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let idx = ((p / 100.0) * (samples.len() - 1) as f64).round() as usize;
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Some(samples[idx])
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}
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pub fn p50(&self) -> Option<Duration> {
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self.percentile(50.0)
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}
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pub fn p95(&self) -> Option<Duration> {
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self.percentile(95.0)
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}
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pub fn p99(&self) -> Option<Duration> {
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self.percentile(99.0)
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}
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pub fn p999(&self) -> Option<Duration> {
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self.percentile(99.9)
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}
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pub fn mean(&self) -> Option<Duration> {
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let samples = self.samples.read();
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if samples.is_empty() {
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return None;
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}
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let total: Duration = samples.iter().sum();
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Some(total / samples.len() as u32)
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}
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pub fn count(&self) -> usize {
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self.samples.read().len()
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}
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pub fn clear(&self) {
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self.samples.write().clear();
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}
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}
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/// Throughput tracker
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#[derive(Debug)]
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pub struct ThroughputTracker {
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requests: AtomicU64,
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successes: AtomicU64,
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errors: AtomicU64,
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start_time: RwLock<Instant>,
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window_requests: RwLock<BTreeMap<u64, u64>>, // second -> count
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}
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impl Default for ThroughputTracker {
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fn default() -> Self {
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Self::new()
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}
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}
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impl ThroughputTracker {
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pub fn new() -> Self {
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Self {
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requests: AtomicU64::new(0),
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successes: AtomicU64::new(0),
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errors: AtomicU64::new(0),
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start_time: RwLock::new(Instant::now()),
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window_requests: RwLock::new(BTreeMap::new()),
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}
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}
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pub fn record_request(&self, success: bool) {
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self.requests.fetch_add(1, Ordering::Relaxed);
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if success {
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self.successes.fetch_add(1, Ordering::Relaxed);
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} else {
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self.errors.fetch_add(1, Ordering::Relaxed);
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}
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// Track per-second requests
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let elapsed_secs = self.start_time.read().elapsed().as_secs();
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let mut window = self.window_requests.write();
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*window.entry(elapsed_secs).or_insert(0) += 1;
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}
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pub fn throughput(&self) -> f64 {
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let elapsed = self.start_time.read().elapsed().as_secs_f64();
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if elapsed == 0.0 {
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return 0.0;
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}
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self.requests.load(Ordering::Relaxed) as f64 / elapsed
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}
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pub fn error_rate(&self) -> f64 {
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let total = self.requests.load(Ordering::Relaxed);
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if total == 0 {
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return 0.0;
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}
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self.errors.load(Ordering::Relaxed) as f64 / total as f64
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}
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pub fn success_rate(&self) -> f64 {
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1.0 - self.error_rate()
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}
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pub fn total_requests(&self) -> u64 {
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self.requests.load(Ordering::Relaxed)
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}
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pub fn reset(&self) {
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self.requests.store(0, Ordering::Relaxed);
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self.successes.store(0, Ordering::Relaxed);
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self.errors.store(0, Ordering::Relaxed);
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*self.start_time.write() = Instant::now();
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self.window_requests.write().clear();
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}
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}
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/// Memory usage tracker
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#[derive(Debug)]
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pub struct MemoryTracker {
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initial_rss: AtomicU64,
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peak_rss: AtomicU64,
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samples: RwLock<Vec<u64>>,
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}
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impl Default for MemoryTracker {
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fn default() -> Self {
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Self::new()
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}
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}
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impl MemoryTracker {
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pub fn new() -> Self {
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let current = Self::get_current_rss();
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Self {
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initial_rss: AtomicU64::new(current),
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peak_rss: AtomicU64::new(current),
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samples: RwLock::new(vec![current]),
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}
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}
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fn get_current_rss() -> u64 {
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// Simplified memory measurement - in production would use sysinfo
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// Returns simulated memory in bytes
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1024 * 1024 * 100 // 100 MB baseline
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}
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pub fn sample(&self) {
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let current = Self::get_current_rss();
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self.samples.write().push(current);
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// Update peak
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let mut peak = self.peak_rss.load(Ordering::Relaxed);
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while current > peak {
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match self.peak_rss.compare_exchange_weak(
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peak,
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current,
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Ordering::Relaxed,
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Ordering::Relaxed,
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) {
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Ok(_) => break,
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Err(actual) => peak = actual,
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}
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}
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}
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pub fn growth_mb(&self) -> i64 {
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let current = Self::get_current_rss();
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let initial = self.initial_rss.load(Ordering::Relaxed);
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(current as i64 - initial as i64) / (1024 * 1024)
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}
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pub fn peak_mb(&self) -> u64 {
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self.peak_rss.load(Ordering::Relaxed) / (1024 * 1024)
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}
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}
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/// Load test result
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#[derive(Debug)]
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pub struct LoadTestResult {
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pub duration: Duration,
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pub total_requests: u64,
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pub successful_requests: u64,
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pub failed_requests: u64,
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pub p50_latency: Duration,
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pub p95_latency: Duration,
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pub p99_latency: Duration,
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pub p999_latency: Duration,
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pub mean_latency: Duration,
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pub throughput_rps: f64,
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pub error_rate: f64,
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pub peak_memory_mb: u64,
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pub memory_growth_mb: i64,
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}
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impl LoadTestResult {
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pub fn check_slo(&self, slo: &SloConfig) -> Vec<String> {
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let mut violations = Vec::new();
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if self.p50_latency.as_millis() as u64 > slo.p50_latency_ms {
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violations.push(format!(
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"P50 latency {}ms exceeds SLO {}ms",
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self.p50_latency.as_millis(),
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slo.p50_latency_ms
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));
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}
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if self.p95_latency.as_millis() as u64 > slo.p95_latency_ms {
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violations.push(format!(
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"P95 latency {}ms exceeds SLO {}ms",
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self.p95_latency.as_millis(),
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slo.p95_latency_ms
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));
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}
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if self.p99_latency.as_millis() as u64 > slo.p99_latency_ms {
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violations.push(format!(
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"P99 latency {}ms exceeds SLO {}ms",
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self.p99_latency.as_millis(),
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slo.p99_latency_ms
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));
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}
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if self.throughput_rps < slo.min_throughput_rps {
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violations.push(format!(
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"Throughput {:.1} rps below SLO {:.1} rps",
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self.throughput_rps,
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slo.min_throughput_rps
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));
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}
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if self.error_rate > slo.max_error_rate {
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violations.push(format!(
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"Error rate {:.2}% exceeds SLO {:.2}%",
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self.error_rate * 100.0,
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slo.max_error_rate * 100.0
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));
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}
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violations
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}
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}
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/// Simulated workload for testing
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#[derive(Clone)]
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pub struct SimulatedWorkload {
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base_latency: Duration,
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latency_variance: Duration,
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error_rate: f64,
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memory_per_request_bytes: u64,
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}
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impl SimulatedWorkload {
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pub fn inference() -> Self {
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Self {
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base_latency: Duration::from_millis(5),
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latency_variance: Duration::from_millis(2),
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error_rate: 0.001,
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memory_per_request_bytes: 1024,
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}
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}
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pub fn batch() -> Self {
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Self {
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base_latency: Duration::from_millis(50),
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latency_variance: Duration::from_millis(20),
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error_rate: 0.005,
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memory_per_request_bytes: 10240,
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}
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}
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pub async fn execute(&self) -> Result<Duration, String> {
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let start = Instant::now();
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// Simulate variable latency
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let variance_ms = (rand::random::<f64>() - 0.5) * 2.0 * self.latency_variance.as_millis() as f64;
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let actual_latency_ms = (self.base_latency.as_millis() as f64 + variance_ms).max(0.0) as u64;
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sleep(Duration::from_millis(actual_latency_ms)).await;
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// Simulate errors
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if rand::random::<f64>() < self.error_rate {
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return Err("Simulated error".to_string());
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}
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Ok(start.elapsed())
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}
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}
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/// Performance integration test suite
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pub struct PerformanceIntegrationTests {
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config: crate::IntegrationTestConfig,
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}
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impl PerformanceIntegrationTests {
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pub fn new(config: crate::IntegrationTestConfig) -> Self {
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Self { config }
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}
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/// Run all performance integration tests
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pub async fn run_all_tests(&self) -> Result<crate::TestResults> {
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let mut results = crate::TestResults::new();
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info!("Starting Performance Integration Tests");
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// Latency tests
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crate::integration_test!("latency_sla_test",
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|| self.test_latency_sla(), &mut results);
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crate::integration_test!("throughput_scaling_test",
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|| self.test_throughput_scaling(), &mut results);
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crate::integration_test!("memory_efficiency_test",
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|| self.test_memory_efficiency(), &mut results);
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if !self.config.skip_gpu_tests {
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crate::integration_test!("gpu_utilization_test",
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|| self.test_gpu_utilization(), &mut results);
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}
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crate::integration_test!("concurrent_load_test",
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|| self.test_concurrent_load(), &mut results);
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crate::integration_test!("resource_scaling_test",
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|| self.test_resource_scaling(), &mut results);
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crate::integration_test!("slo_compliance_test",
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|| self.test_slo_compliance(), &mut results);
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Ok(results)
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}
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/// Test latency SLA compliance
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async fn test_latency_sla(&self) -> Result<()> {
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info!("Testing latency SLA compliance...");
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let mut ctx = TestContext::new();
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let histogram = LatencyHistogram::new();
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let workload = SimulatedWorkload::inference();
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let slo = SloConfig::inference();
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// Run 1000 requests to gather latency distribution
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for _ in 0..1000 {
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match workload.execute().await {
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Ok(latency) => histogram.record(latency),
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Err(_) => {} // Ignore errors for latency test
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}
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}
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let p50 = histogram.p50().unwrap_or_default();
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let p95 = histogram.p95().unwrap_or_default();
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let p99 = histogram.p99().unwrap_or_default();
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let p999 = histogram.p999().unwrap_or_default();
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info!(
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"Latency percentiles: P50={:?}, P95={:?}, P99={:?}, P99.9={:?}",
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p50, p95, p99, p999
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);
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// Check against SLOs
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assert!(
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p50.as_millis() as u64 <= slo.p50_latency_ms * 2, // Allow 2x for CI variance
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"P50 latency {}ms exceeds relaxed SLO {}ms",
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p50.as_millis(),
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slo.p50_latency_ms * 2
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);
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assert!(
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p95.as_millis() as u64 <= slo.p95_latency_ms * 2,
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"P95 latency {}ms exceeds relaxed SLO {}ms",
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p95.as_millis(),
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slo.p95_latency_ms * 2
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);
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ctx.cleanup().await?;
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info!("Latency SLA test passed");
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Ok(())
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}
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/// Test throughput scaling
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async fn test_throughput_scaling(&self) -> Result<()> {
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info!("Testing throughput scaling...");
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let mut ctx = TestContext::new();
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let concurrency_levels = [1, 2, 4, 8];
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let mut throughputs = Vec::new();
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for concurrency in concurrency_levels {
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let tracker = Arc::new(ThroughputTracker::new());
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let workload = SimulatedWorkload::inference();
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let semaphore = Arc::new(Semaphore::new(concurrency));
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let duration = Duration::from_secs(1);
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let start = Instant::now();
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let mut handles = Vec::new();
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while start.elapsed() < duration {
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let permit = semaphore.clone().try_acquire_owned();
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if permit.is_err() {
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sleep(Duration::from_micros(100)).await;
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continue;
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}
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let tracker_clone = tracker.clone();
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let workload_clone = workload.clone();
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handles.push(tokio::spawn(async move {
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let _permit = permit;
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let success = workload_clone.execute().await.is_ok();
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tracker_clone.record_request(success);
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}));
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}
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// Wait for in-flight requests
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for handle in handles {
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let _ = handle.await;
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}
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let rps = tracker.throughput();
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throughputs.push((concurrency, rps));
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info!("Concurrency {}: {:.1} rps", concurrency, rps);
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}
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// Verify throughput scales (at least somewhat) with concurrency
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if throughputs.len() >= 2 {
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let (_, first_rps) = throughputs[0];
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let (_, last_rps) = throughputs[throughputs.len() - 1];
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assert!(
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last_rps >= first_rps * 1.5,
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"Throughput should scale with concurrency: first={first_rps:.1}, last={last_rps:.1}"
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);
|
|
}
|
|
|
|
ctx.cleanup().await?;
|
|
info!("Throughput scaling test passed");
|
|
Ok(())
|
|
}
|
|
|
|
/// Test memory efficiency under sustained load
|
|
async fn test_memory_efficiency(&self) -> Result<()> {
|
|
info!("Testing memory efficiency...");
|
|
let mut ctx = TestContext::new();
|
|
|
|
let memory = MemoryTracker::new();
|
|
let workload = SimulatedWorkload::inference();
|
|
|
|
// Run sustained load for a short period
|
|
let duration = Duration::from_secs(2);
|
|
let start = Instant::now();
|
|
let mut request_count = 0u64;
|
|
|
|
while start.elapsed() < duration {
|
|
let _ = workload.execute().await;
|
|
request_count += 1;
|
|
|
|
// Sample memory periodically
|
|
if request_count.is_multiple_of(100) {
|
|
memory.sample();
|
|
}
|
|
}
|
|
|
|
let growth = memory.growth_mb();
|
|
let peak = memory.peak_mb();
|
|
|
|
info!(
|
|
"Memory: growth={}MB, peak={}MB after {} requests",
|
|
growth, peak, request_count
|
|
);
|
|
|
|
// Memory growth should be bounded
|
|
assert!(
|
|
growth.abs() < 100,
|
|
"Memory growth {growth}MB should be bounded"
|
|
);
|
|
|
|
ctx.cleanup().await?;
|
|
info!("Memory efficiency test passed");
|
|
Ok(())
|
|
}
|
|
|
|
/// Test GPU utilization (simulated)
|
|
async fn test_gpu_utilization(&self) -> Result<()> {
|
|
info!("Testing GPU utilization...");
|
|
let mut ctx = TestContext::new();
|
|
|
|
// Simulated GPU workload
|
|
// In production, this would use actual GPU operations
|
|
let gpu_tasks = 100;
|
|
let mut gpu_time_ms = 0u64;
|
|
|
|
for _ in 0..gpu_tasks {
|
|
let start = Instant::now();
|
|
// Simulate GPU computation
|
|
sleep(Duration::from_millis(1)).await;
|
|
gpu_time_ms += start.elapsed().as_millis() as u64;
|
|
}
|
|
|
|
let avg_gpu_time = gpu_time_ms as f64 / gpu_tasks as f64;
|
|
info!("Average simulated GPU time: {:.2}ms", avg_gpu_time);
|
|
|
|
// Verify GPU operations complete in reasonable time
|
|
assert!(
|
|
avg_gpu_time < 10.0,
|
|
"GPU operations should be fast: avg={avg_gpu_time:.2}ms"
|
|
);
|
|
|
|
ctx.cleanup().await?;
|
|
info!("GPU utilization test passed");
|
|
Ok(())
|
|
}
|
|
|
|
/// Test concurrent load handling
|
|
async fn test_concurrent_load(&self) -> Result<()> {
|
|
info!("Testing concurrent load handling...");
|
|
let mut ctx = TestContext::new();
|
|
|
|
let histogram = Arc::new(LatencyHistogram::new());
|
|
let tracker = Arc::new(ThroughputTracker::new());
|
|
let workload = SimulatedWorkload::inference();
|
|
let concurrency = 16;
|
|
let semaphore = Arc::new(Semaphore::new(concurrency));
|
|
|
|
let duration = Duration::from_secs(2);
|
|
let start = Instant::now();
|
|
let mut handles = Vec::new();
|
|
|
|
while start.elapsed() < duration {
|
|
let permit = semaphore.clone().try_acquire_owned();
|
|
if permit.is_err() {
|
|
sleep(Duration::from_micros(100)).await;
|
|
continue;
|
|
}
|
|
|
|
let histogram_clone = histogram.clone();
|
|
let tracker_clone = tracker.clone();
|
|
let workload_clone = workload.clone();
|
|
handles.push(tokio::spawn(async move {
|
|
let _permit = permit;
|
|
match workload_clone.execute().await {
|
|
Ok(latency) => {
|
|
histogram_clone.record(latency);
|
|
tracker_clone.record_request(true);
|
|
}
|
|
Err(_) => {
|
|
tracker_clone.record_request(false);
|
|
}
|
|
}
|
|
}));
|
|
}
|
|
|
|
// Wait for all requests
|
|
for handle in handles {
|
|
let _ = handle.await;
|
|
}
|
|
|
|
let total = tracker.total_requests();
|
|
let error_rate = tracker.error_rate();
|
|
let throughput = tracker.throughput();
|
|
let p99 = histogram.p99().unwrap_or_default();
|
|
|
|
info!(
|
|
"Concurrent load: total={}, throughput={:.1} rps, error_rate={:.2}%, P99={:?}",
|
|
total, throughput, error_rate * 100.0, p99
|
|
);
|
|
|
|
// Verify system handles load gracefully
|
|
assert!(error_rate < 0.05, "Error rate {:.2}% too high", error_rate * 100.0);
|
|
assert!(throughput > 10.0, "Throughput {throughput:.1} rps too low");
|
|
|
|
ctx.cleanup().await?;
|
|
info!("Concurrent load test passed");
|
|
Ok(())
|
|
}
|
|
|
|
/// Test resource scaling behavior
|
|
async fn test_resource_scaling(&self) -> Result<()> {
|
|
info!("Testing resource scaling...");
|
|
let mut ctx = TestContext::new();
|
|
|
|
// Simulate auto-scaling by increasing/decreasing concurrency
|
|
let mut current_concurrency = 1;
|
|
let target_latency = Duration::from_millis(10);
|
|
|
|
for iteration in 0..5 {
|
|
let histogram = LatencyHistogram::new();
|
|
let workload = SimulatedWorkload::inference();
|
|
|
|
// Run with current concurrency
|
|
for _ in 0..100 {
|
|
if let Ok(latency) = workload.execute().await {
|
|
histogram.record(latency);
|
|
}
|
|
}
|
|
|
|
let avg_latency = histogram.mean().unwrap_or_default();
|
|
info!(
|
|
"Iteration {}: concurrency={}, avg_latency={:?}",
|
|
iteration, current_concurrency, avg_latency
|
|
);
|
|
|
|
// Scale up/down based on latency
|
|
if avg_latency > target_latency * 2 {
|
|
current_concurrency = (current_concurrency / 2).max(1);
|
|
debug!("Scaling down to {}", current_concurrency);
|
|
} else if avg_latency < target_latency / 2 {
|
|
current_concurrency = (current_concurrency * 2).min(16);
|
|
debug!("Scaling up to {}", current_concurrency);
|
|
}
|
|
}
|
|
|
|
ctx.cleanup().await?;
|
|
info!("Resource scaling test passed");
|
|
Ok(())
|
|
}
|
|
|
|
/// Test comprehensive SLO compliance
|
|
async fn test_slo_compliance(&self) -> Result<()> {
|
|
info!("Testing SLO compliance...");
|
|
let mut ctx = TestContext::new();
|
|
|
|
let histogram = Arc::new(LatencyHistogram::new());
|
|
let tracker = Arc::new(ThroughputTracker::new());
|
|
let memory = MemoryTracker::new();
|
|
let workload = SimulatedWorkload::inference();
|
|
let slo = SloConfig::default(); // Use relaxed SLO for testing
|
|
|
|
// Run sustained load
|
|
let duration = Duration::from_secs(3);
|
|
let start = Instant::now();
|
|
let concurrency = 8;
|
|
let semaphore = Arc::new(Semaphore::new(concurrency));
|
|
let mut handles = Vec::new();
|
|
|
|
while start.elapsed() < duration {
|
|
let permit = semaphore.clone().try_acquire_owned();
|
|
if permit.is_err() {
|
|
sleep(Duration::from_micros(100)).await;
|
|
continue;
|
|
}
|
|
|
|
let histogram_clone = histogram.clone();
|
|
let tracker_clone = tracker.clone();
|
|
let workload_clone = workload.clone();
|
|
handles.push(tokio::spawn(async move {
|
|
let _permit = permit;
|
|
match workload_clone.execute().await {
|
|
Ok(latency) => {
|
|
histogram_clone.record(latency);
|
|
tracker_clone.record_request(true);
|
|
}
|
|
Err(_) => {
|
|
tracker_clone.record_request(false);
|
|
}
|
|
}
|
|
}));
|
|
}
|
|
|
|
for handle in handles {
|
|
let _ = handle.await;
|
|
}
|
|
|
|
memory.sample();
|
|
|
|
let result = LoadTestResult {
|
|
duration: start.elapsed(),
|
|
total_requests: tracker.total_requests(),
|
|
successful_requests: tracker.total_requests() - (tracker.error_rate() * tracker.total_requests() as f64) as u64,
|
|
failed_requests: (tracker.error_rate() * tracker.total_requests() as f64) as u64,
|
|
p50_latency: histogram.p50().unwrap_or_default(),
|
|
p95_latency: histogram.p95().unwrap_or_default(),
|
|
p99_latency: histogram.p99().unwrap_or_default(),
|
|
p999_latency: histogram.p999().unwrap_or_default(),
|
|
mean_latency: histogram.mean().unwrap_or_default(),
|
|
throughput_rps: tracker.throughput(),
|
|
error_rate: tracker.error_rate(),
|
|
peak_memory_mb: memory.peak_mb(),
|
|
memory_growth_mb: memory.growth_mb(),
|
|
};
|
|
|
|
info!(
|
|
"Load test result: requests={}, throughput={:.1} rps, P99={:?}, error_rate={:.3}%",
|
|
result.total_requests,
|
|
result.throughput_rps,
|
|
result.p99_latency,
|
|
result.error_rate * 100.0
|
|
);
|
|
|
|
let violations = result.check_slo(&slo);
|
|
for violation in &violations {
|
|
warn!("SLO violation: {}", violation);
|
|
}
|
|
|
|
// Allow some violations in CI environment
|
|
assert!(
|
|
violations.len() <= 2,
|
|
"Too many SLO violations: {violations:?}"
|
|
);
|
|
|
|
ctx.cleanup().await?;
|
|
info!("SLO compliance test passed");
|
|
Ok(())
|
|
}
|
|
}
|
|
|
|
#[cfg(test)]
|
|
mod tests {
|
|
use super::*;
|
|
|
|
#[test]
|
|
fn test_latency_histogram() {
|
|
let hist = LatencyHistogram::new();
|
|
|
|
for i in 0..100 {
|
|
hist.record(Duration::from_millis(i));
|
|
}
|
|
|
|
assert_eq!(hist.count(), 100);
|
|
|
|
let p50 = hist.p50().unwrap();
|
|
assert!(p50.as_millis() >= 45 && p50.as_millis() <= 55);
|
|
|
|
let p99 = hist.p99().unwrap();
|
|
assert!(p99.as_millis() >= 95);
|
|
}
|
|
|
|
#[test]
|
|
fn test_throughput_tracker() {
|
|
let tracker = ThroughputTracker::new();
|
|
|
|
for _ in 0..100 {
|
|
tracker.record_request(true);
|
|
}
|
|
for _ in 0..5 {
|
|
tracker.record_request(false);
|
|
}
|
|
|
|
assert_eq!(tracker.total_requests(), 105);
|
|
let error_rate = tracker.error_rate();
|
|
assert!((error_rate - 5.0 / 105.0).abs() < 0.01);
|
|
}
|
|
|
|
#[test]
|
|
fn test_slo_check() {
|
|
let result = LoadTestResult {
|
|
duration: Duration::from_secs(10),
|
|
total_requests: 1000,
|
|
successful_requests: 990,
|
|
failed_requests: 10,
|
|
p50_latency: Duration::from_millis(5),
|
|
p95_latency: Duration::from_millis(20),
|
|
p99_latency: Duration::from_millis(50),
|
|
p999_latency: Duration::from_millis(100),
|
|
mean_latency: Duration::from_millis(10),
|
|
throughput_rps: 100.0,
|
|
error_rate: 0.01,
|
|
peak_memory_mb: 200,
|
|
memory_growth_mb: 50,
|
|
};
|
|
|
|
let slo = SloConfig::default();
|
|
let violations = result.check_slo(&slo);
|
|
assert!(violations.is_empty(), "Expected no violations: {:?}", violations);
|
|
}
|
|
}
|