Pulse/internal/ai/baseline/store_test.go
rcourtman d29b3c2324 test(baseline): add tests for trend prediction
Add comprehensive tests for CalculateTrend function:
- TestCalculateTrend_InsufficientData: <5 samples returns nil
- TestCalculateTrend_IncreasingTrend: detects critical/warning trends
- TestCalculateTrend_DecreasingTrend: correctly identifies declining usage
- TestCalculateTrend_StableTrend: stable patterns return DaysToFull=-1
- TestFormatDays: human-readable time formatting
2025-12-21 11:31:58 +00:00

306 lines
8.1 KiB
Go

package baseline
import (
"math"
"testing"
"time"
)
func TestLearn_Basic(t *testing.T) {
store := NewStore(StoreConfig{MinSamples: 10})
// Create 50 data points with mean ~50 and some variance
points := make([]MetricPoint, 50)
now := time.Now()
for i := 0; i < 50; i++ {
points[i] = MetricPoint{
Value: 50 + float64(i%10) - 5, // Values from 45-54
Timestamp: now.Add(-time.Duration(50-i) * time.Minute),
}
}
err := store.Learn("test-vm", "vm", "cpu", points)
if err != nil {
t.Fatalf("Learn failed: %v", err)
}
baseline, ok := store.GetBaseline("test-vm", "cpu")
if !ok {
t.Fatal("Baseline not found after learning")
}
// Check mean is around 50
if math.Abs(baseline.Mean-50) > 1 {
t.Errorf("Expected mean ~50, got %f", baseline.Mean)
}
// Check stddev is reasonable (should be ~3 for our data)
if baseline.StdDev < 1 || baseline.StdDev > 5 {
t.Errorf("Expected stddev ~3, got %f", baseline.StdDev)
}
if baseline.SampleCount != 50 {
t.Errorf("Expected 50 samples, got %d", baseline.SampleCount)
}
}
func TestLearn_InsufficientData(t *testing.T) {
store := NewStore(StoreConfig{MinSamples: 50})
// Only 10 points, not enough
points := make([]MetricPoint, 10)
for i := 0; i < 10; i++ {
points[i] = MetricPoint{Value: float64(i)}
}
err := store.Learn("test-vm", "vm", "cpu", points)
if err != nil {
t.Fatalf("Learn should not error on insufficient data: %v", err)
}
_, ok := store.GetBaseline("test-vm", "cpu")
if ok {
t.Error("Should not have baseline with insufficient data")
}
}
func TestIsAnomaly(t *testing.T) {
store := NewStore(StoreConfig{MinSamples: 10})
// Create stable data around 50 with low variance
points := make([]MetricPoint, 100)
for i := 0; i < 100; i++ {
points[i] = MetricPoint{
Value: 50 + float64(i%3) - 1, // Values 49, 50, 51
}
}
store.Learn("test-vm", "vm", "cpu", points)
// Test normal value
isAnomaly, zScore := store.IsAnomaly("test-vm", "cpu", 50)
if isAnomaly {
t.Errorf("50 should not be anomaly, zScore=%f", zScore)
}
// Test slightly high - with stddev ~0.82, 51 is within 2 std devs
isAnomaly, zScore = store.IsAnomaly("test-vm", "cpu", 51)
if isAnomaly {
t.Errorf("51 should not be anomaly with this variance, zScore=%f", zScore)
}
// Test very high (should be anomaly)
isAnomaly, zScore = store.IsAnomaly("test-vm", "cpu", 60)
if !isAnomaly {
t.Errorf("60 should be anomaly, zScore=%f", zScore)
}
// Test very low (should be anomaly)
isAnomaly, zScore = store.IsAnomaly("test-vm", "cpu", 40)
if !isAnomaly {
t.Errorf("40 should be anomaly, zScore=%f", zScore)
}
}
func TestCheckAnomaly_Severity(t *testing.T) {
store := NewStore(StoreConfig{MinSamples: 10})
// Create very stable data with known statistics
// Mean = 50, StdDev = 1
points := make([]MetricPoint, 100)
for i := 0; i < 100; i++ {
// Alternate between 49, 50, 51 for stddev ~1
points[i] = MetricPoint{Value: 50 + float64(i%3) - 1}
}
store.Learn("test-vm", "vm", "cpu", points)
baseline, _ := store.GetBaseline("test-vm", "cpu")
testCases := []struct {
value float64
expectedSeverity AnomalySeverity
}{
{50, AnomalyNone}, // Mean
{50 + baseline.StdDev*1.5, AnomalyNone}, // 1.5 std devs - normal
{50 + baseline.StdDev*2.2, AnomalyLow}, // 2.2 std devs
{50 + baseline.StdDev*2.7, AnomalyMedium}, // 2.7 std devs
{50 + baseline.StdDev*3.5, AnomalyHigh}, // 3.5 std devs
{50 + baseline.StdDev*4.5, AnomalyCritical}, // 4.5 std devs
}
for _, tc := range testCases {
severity, _, _ := store.CheckAnomaly("test-vm", "cpu", tc.value)
if severity != tc.expectedSeverity {
t.Errorf("Value %f: expected severity %s, got %s", tc.value, tc.expectedSeverity, severity)
}
}
}
func TestGetResourceBaseline(t *testing.T) {
store := NewStore(StoreConfig{MinSamples: 10})
// Learn multiple metrics
cpuPoints := make([]MetricPoint, 50)
memPoints := make([]MetricPoint, 50)
for i := 0; i < 50; i++ {
cpuPoints[i] = MetricPoint{Value: 30}
memPoints[i] = MetricPoint{Value: 70}
}
store.Learn("test-vm", "vm", "cpu", cpuPoints)
store.Learn("test-vm", "vm", "memory", memPoints)
rb, ok := store.GetResourceBaseline("test-vm")
if !ok {
t.Fatal("Resource baseline not found")
}
if rb.ResourceType != "vm" {
t.Errorf("Expected resource type 'vm', got '%s'", rb.ResourceType)
}
if len(rb.Metrics) != 2 {
t.Errorf("Expected 2 metrics, got %d", len(rb.Metrics))
}
if rb.Metrics["cpu"] == nil {
t.Error("CPU metric baseline missing")
}
if rb.Metrics["memory"] == nil {
t.Error("Memory metric baseline missing")
}
}
func TestPercentiles(t *testing.T) {
values := []float64{1, 2, 3, 4, 5, 6, 7, 8, 9, 10}
percentiles := computePercentiles(values)
// P50 should be ~5.5 for 1-10
if percentiles[50] < 5 || percentiles[50] > 6 {
t.Errorf("P50 should be ~5.5, got %f", percentiles[50])
}
// P5 should be close to 1
if percentiles[5] < 1 || percentiles[5] > 2 {
t.Errorf("P5 should be ~1, got %f", percentiles[5])
}
// P95 should be close to 10
if percentiles[95] < 9 || percentiles[95] > 10 {
t.Errorf("P95 should be ~10, got %f", percentiles[95])
}
}
func TestComputeStats(t *testing.T) {
// Test mean and stddev with known values
values := []float64{2, 4, 4, 4, 5, 5, 7, 9} // Mean = 5, Stddev = 2 (sample)
mean := computeMean(values)
if mean != 5 {
t.Errorf("Expected mean 5, got %f", mean)
}
stddev := computeStdDev(values)
// Sample stddev of [2,4,4,4,5,5,7,9] is approximately 2.14, not exactly 2
if math.Abs(stddev-2.14) > 0.1 {
t.Errorf("Expected stddev ~2.14, got %f", stddev)
}
}
func TestCalculateTrend_InsufficientData(t *testing.T) {
// Less than 5 samples should return nil
samples := []float64{10, 20, 30}
result := CalculateTrend(samples, 30)
if result != nil {
t.Error("Expected nil for insufficient data")
}
}
func TestCalculateTrend_IncreasingTrend(t *testing.T) {
// Simulate hourly samples increasing by 1% per hour
// 24 samples = 1 day, so 24% increase per day
samples := make([]float64, 48) // 2 days of data
for i := 0; i < 48; i++ {
samples[i] = 50 + float64(i) // 50, 51, 52, ...
}
result := CalculateTrend(samples, 97) // Currently at 97%
if result == nil {
t.Fatal("Expected non-nil result for increasing trend")
}
// Should be trending toward full
if result.DaysToFull <= 0 {
t.Errorf("Expected positive DaysToFull for increasing trend, got %d", result.DaysToFull)
}
// With 24% increase per day and 3% remaining, should be full very soon
if result.Severity != "critical" && result.Severity != "warning" {
t.Errorf("Expected critical or warning severity, got %s", result.Severity)
}
}
func TestCalculateTrend_DecreasingTrend(t *testing.T) {
// Simulate hourly samples decreasing
samples := make([]float64, 48)
for i := 0; i < 48; i++ {
samples[i] = 80 - float64(i)*0.5 // 80, 79.5, 79, ...
}
result := CalculateTrend(samples, 56)
if result == nil {
t.Fatal("Expected non-nil result for decreasing trend")
}
// Should indicate decreasing (DaysToFull = -1)
if result.DaysToFull != -1 {
t.Errorf("Expected DaysToFull=-1 for decreasing trend, got %d", result.DaysToFull)
}
if result.Severity != "info" {
t.Errorf("Expected info severity for decreasing trend, got %s", result.Severity)
}
}
func TestCalculateTrend_StableTrend(t *testing.T) {
// Simulate stable usage around 50%
samples := make([]float64, 48)
for i := 0; i < 48; i++ {
samples[i] = 50 + float64(i%3-1)*0.01 // Tiny fluctuations
}
result := CalculateTrend(samples, 50)
if result == nil {
t.Fatal("Expected non-nil result for stable trend")
}
// Should indicate stable (DaysToFull = -1)
if result.DaysToFull != -1 {
t.Errorf("Expected DaysToFull=-1 for stable trend, got %d", result.DaysToFull)
}
}
func TestFormatDays(t *testing.T) {
testCases := []struct {
days int
expected string
}{
{0, "now"},
{1, "1 day"},
{5, "5 days"},
{7, "~1 week"},
{14, "~2 weeks"},
{30, "~1 month"},
{60, "~2 months"},
{400, ">1 year"},
}
for _, tc := range testCases {
result := formatDays(tc.days)
if result != tc.expected {
t.Errorf("formatDays(%d): expected %q, got %q", tc.days, tc.expected, result)
}
}
}