Merged in feature/common-metrics (pull request #73)
Add common metrics * add common metrics and sample for using * updates * attempt integration * wip * working stubs generate * docs * comments * Merge branch 'main' of bitbucket.org:aarete/query-orchestration into feature/common-metrics * runner metrics all * exclude generated from the coverage * fix lint * refactor metrics * change .gen filename * new gen * Merge branch 'main' of bitbucket.org:aarete/query-orchestration into feature/common-metrics * docs * main merge * refactor * add to generate * merge main
This commit is contained in:
Jay Brown
+110
-77
@@ -27,99 +27,73 @@ import (
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)
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func main() {
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// Create a context that we can cancel
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ctx, cancel := context.WithCancel(context.Background())
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defer cancel()
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// Define metrics configuration
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// This example shows all supported metric types and their configurations
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standardDefinitions := prometheus.NewStandardMetricDefinitions()
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// Define metrics configuration using StandardMetricDefinitions
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config := prometheus.MetricsConfig{
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Port: 8080,
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Namespace: "myapp",
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Subsystem: "api",
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// When ServeHttp is true, the package will start its own HTTP server
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// If you want to use your own HTTP server (e.g., with Echo middleware),
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// set this to false and configure your server to handle the /metrics endpoint
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ServeHttp: true,
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Definitions: []prometheus.MetricDefinition{
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{
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// Counter: Only increases, never decreases
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Type: prometheus.Counter,
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Name: "api_requests_total",
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Help: "Total number of API requests",
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Labels: []string{"method", "endpoint", "status"},
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},
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{
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// Gauge: Can increase and decrease
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Type: prometheus.Gauge,
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Name: "active_users",
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Help: "Number of currently active users",
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Labels: []string{"user_type"},
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},
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{
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// Histogram: Tracks distribution of values
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Type: prometheus.Histogram,
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Name: "request_duration_seconds",
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Help: "Request duration distribution",
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Labels: []string{"endpoint"},
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Buckets: []float64{0.1, 0.5, 1, 2, 5}, // Define your bucket boundaries
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},
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{
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// Summary: Calculates quantiles over a sliding time window
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Type: prometheus.Summary,
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Name: "response_size_bytes",
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Help: "Response size distribution",
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Labels: []string{"endpoint"},
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Objectives: map[float64]float64{
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0.5: 0.05, // 50th percentile with 5% error
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0.9: 0.01, // 90th percentile with 1% error
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0.99: 0.001, // 99th percentile with 0.1% error
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// Start with standard metrics and append our custom one
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Definitions: append(standardDefinitions,
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prometheus.MetricDefinition{
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Type: prometheus.Counter,
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Name: "test_custom_events_total",
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Help: "Total number of custom test events",
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Labels: []string{
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"event_type",
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"priority",
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},
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},
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},
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),
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}
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// Create new metrics instance with context
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metrics, err := prometheus.New(ctx, config)
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if err != nil {
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log.Fatalf("Failed to create metrics: %v", err)
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}
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// Start a goroutine to simulate metric recording
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go simulateMetrics(ctx, metrics)
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// Set up graceful shutdown
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sigChan := make(chan os.Signal, 1)
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signal.Notify(sigChan, syscall.SIGINT, syscall.SIGTERM)
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fmt.Println("Running... Press Ctrl+C to exit")
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// Wait for interrupt signal
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<-sigChan
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fmt.Println("\nShutting down...")
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// Cancel context to stop metric simulation
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cancel()
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// Create a timeout context for shutdown
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shutdownCtx, shutdownCancel := context.WithTimeout(context.Background(), 5*time.Second)
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defer shutdownCancel()
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// Gracefully shutdown the metrics server
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if err := metrics.Shutdown(shutdownCtx); err != nil {
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log.Printf("Error shutting down metrics server: %v", err)
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}
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}
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// simulateMetrics demonstrates how to record different types of metrics
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// in a concurrent environment. It takes a context for cancellation and
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// the metrics instance.
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func simulateMetrics(ctx context.Context, metrics *prometheus.Metrics) {
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// Sample data for simulation
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endpoints := []string{"/api/users", "/api/products", "/api/orders"}
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methods := []string{"GET", "POST", "PUT", "DELETE"}
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statuses := []string{"200", "400", "500"}
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userTypes := []string{"free", "premium", "enterprise"}
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errorTypes := []string{"none", "validation", "database", "timeout"}
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dependencies := []string{"database", "cache", "auth-service", "email-service"}
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cacheOperations := []string{"hit", "miss", "set", "eviction"}
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taskTypes := []string{"cleanup", "indexing", "backup", "sync"}
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taskStatuses := []string{"running", "queued", "failed"}
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results := []string{"success", "failure", "timeout"}
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components := []string{"api", "database", "cache", "auth"}
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queueNames := []string{"main-queue", "background-queue", "notification-queue"}
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resourceTypes := []string{"cpu", "memory", "disk", "network"}
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// Custom metric sample data
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eventTypes := []string{"scheduled", "triggered", "manual"}
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priorities := []string{"low", "medium", "high"}
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ticker := time.NewTicker(2 * time.Second)
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defer ticker.Stop()
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@@ -129,46 +103,105 @@ func simulateMetrics(ctx context.Context, metrics *prometheus.Metrics) {
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case <-ctx.Done():
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return
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case <-ticker.C:
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// Simulate request counter (Counter type)
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// Simulate standard metrics
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// 1. Requests total
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endpoint := endpoints[rand.Intn(len(endpoints))]
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method := methods[rand.Intn(len(methods))]
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status := statuses[rand.Intn(len(statuses))]
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errorType := errorTypes[rand.Intn(len(errorTypes))]
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err := metrics.RecordMetric("api_requests_total", 1, map[string]string{
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"method": method,
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"endpoint": endpoint,
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"status": status,
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})
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err := metrics.RecordRequestsTotal(1.0, endpoint, method, endpoint, status, errorType)
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if err != nil {
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log.Printf("Error recording request metric: %v", err)
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log.Printf("Error recording requests metric: %v", err)
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}
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// Simulate active users (Gauge type)
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userType := userTypes[rand.Intn(len(userTypes))]
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activeUsers := rand.Float64() * 100
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err = metrics.RecordMetric("active_users", activeUsers, map[string]string{
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"user_type": userType,
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})
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if err != nil {
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log.Printf("Error recording active users metric: %v", err)
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}
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// Simulate request duration (Histogram type)
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// 2. Request duration
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duration := rand.Float64() * 3 // Random duration between 0 and 3 seconds
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err = metrics.RecordMetric("request_duration_seconds", duration, map[string]string{
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"endpoint": endpoint,
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})
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err = metrics.RecordRequestDurationSeconds(duration, endpoint, method, endpoint, status)
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if err != nil {
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log.Printf("Error recording duration metric: %v", err)
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}
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// Simulate response size (Summary type)
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responseSize := rand.Float64() * 5000 // Random size between 0 and 5000 bytes
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err = metrics.RecordMetric("response_size_bytes", responseSize, map[string]string{
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"endpoint": endpoint,
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// 3. Active operations
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activeOps := rand.Float64() * 50
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err = metrics.RecordActiveOperations(activeOps, method)
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if err != nil {
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log.Printf("Error recording active operations metric: %v", err)
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}
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// 4. Resource usage
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resourceType := resourceTypes[rand.Intn(len(resourceTypes))]
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err = metrics.RecordResourceUsage(rand.Float64()*100, resourceType, "main-instance")
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if err != nil {
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log.Printf("Error recording resource usage metric: %v", err)
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}
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// 5. Dependency health
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dep := dependencies[rand.Intn(len(dependencies))]
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health := rand.Float64() // Random health score between 0 and 1
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err = metrics.RecordDependencyHealth(health, dep, "external_service")
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if err != nil {
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log.Printf("Error recording dependency health metric: %v", err)
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}
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// 6. Cache operations
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cacheOp := cacheOperations[rand.Intn(len(cacheOperations))]
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result := results[rand.Intn(len(results))]
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err = metrics.RecordCacheOperationsTotal(1.0, cacheOp, "main-cache", result)
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if err != nil {
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log.Printf("Error recording cache operations metric: %v", err)
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}
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// 7. Cache operation duration
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err = metrics.RecordCacheOperationDurationSeconds(rand.Float64()*0.1, cacheOp, result)
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if err != nil {
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log.Printf("Error recording cache duration metric: %v", err)
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}
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// 8. Background tasks
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taskType := taskTypes[rand.Intn(len(taskTypes))]
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taskStatus := taskStatuses[rand.Intn(len(taskStatuses))]
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err = metrics.RecordBackgroundTasks(rand.Float64()*10, taskType, taskStatus)
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if err != nil {
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log.Printf("Error recording background tasks metric: %v", err)
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}
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// 9. Active connections
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err = metrics.RecordActiveConnections(rand.Float64()*100, "http")
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if err != nil {
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log.Printf("Error recording active connections metric: %v", err)
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}
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// 10. Queue length
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queueName := queueNames[rand.Intn(len(queueNames))]
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err = metrics.RecordQueueLength(rand.Float64()*50, queueName)
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if err != nil {
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log.Printf("Error recording queue length metric: %v", err)
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}
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// 11. Errors total
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component := components[rand.Intn(len(components))]
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err = metrics.RecordErrorsTotal(1.0, component, errorType)
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if err != nil {
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log.Printf("Error recording errors total metric: %v", err)
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}
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// 12. Items in progress
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err = metrics.RecordItemsInProgress(rand.Float64()*20, endpoint, component)
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if err != nil {
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log.Printf("Error recording items in progress metric: %v", err)
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}
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// Custom metric (still using RecordMetric since it's not part of the generated stubs)
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eventType := eventTypes[rand.Intn(len(eventTypes))]
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priority := priorities[rand.Intn(len(priorities))]
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err = metrics.RecordMetric("test_custom_events_total", 1, map[string]string{
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"event_type": eventType,
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"priority": priority,
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})
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if err != nil {
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log.Printf("Error recording response size metric: %v", err)
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log.Printf("Error recording custom event metric: %v", err)
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}
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}
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}
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