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Golang Observability Opentelemetry

  • 293 installs
  • 63 repo stars
  • Updated July 18, 2026
  • bobmatnyc/claude-mpm-skills

golang-observability-opentelemetry is a Claude Code skill that instruments Go services with OpenTelemetry traces, metrics, and correlated logs for developers who need distributed debugging and SLO visibility.

About

golang-observability-opentelemetry is a Claude Code skill for adding production-grade observability to Go microservices using the OpenTelemetry SDK. The skill guides instrumenting HTTP and gRPC handlers, configuring OTLP exporters, propagating trace context across service boundaries, and correlating structured logs with span IDs for distributed debugging. Developers reach for it when standing up a new Go API, retrofitting legacy services before an on-call rotation, or aligning telemetry with an existing Grafana, Jaeger, or Honeycomb backend. It focuses on practical Go patterns—middleware hooks, resource attributes, metric instruments, and sampler configuration—rather than generic tracing theory. Use it when SLO dashboards need real request latency data or cross-service failures require trace-linked log queries.

  • OpenTelemetry Go SDK
  • distributed tracing spans
  • metrics and exporters
  • log correlation
  • context propagation

Golang Observability Opentelemetry by the numbers

  • 293 all-time installs (skills.sh)
  • Ranked #338 of 1,435 DevOps & CI/CD skills by installs in the Skillselion catalog
  • Data as of Aug 1, 2026 (Skillselion catalog sync)
npx skills add https://github.com/bobmatnyc/claude-mpm-skills --skill golang-observability-opentelemetry

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Installs293
repo stars63
Last updatedJuly 18, 2026
Repositorybobmatnyc/claude-mpm-skills

How do you add OpenTelemetry to a Go microservice?

Instrument Go services with OpenTelemetry traces, metrics, and correlated logs for distributed debugging and SLO visibility.

Who is it for?

Go backend engineers shipping microservices who need traces, metrics, and correlated logs before production on-call coverage.

Skip if: Frontend-only teams or repos without Go services that only need browser Real User Monitoring instead of server-side OTLP instrumentation.

When should I use this skill?

A Go service lacks distributed tracing, SLO dashboards need latency metrics, or the user asks to add OpenTelemetry to handlers and exporters.

What you get

OTel SDK wiring, trace propagators, metric instruments, log correlation hooks, and exporter configuration in Go service code.

  • OTel instrumentation code
  • exporter configuration
  • log correlation setup

Files

SKILL.mdMarkdownGitHub ↗

Go Observability with OpenTelemetry

Overview

Modern Go applications require comprehensive observability through the three pillars: traces, metrics, and logs. OpenTelemetry provides vendor-neutral instrumentation for distributed tracing, Prometheus offers powerful metrics collection, and Go's slog package (1.21+) delivers structured logging with minimal overhead.

Key Features:

  • 🔍 OpenTelemetry: Distributed tracing with context propagation
  • 📊 Prometheus: Metrics collection with /metrics endpoint
  • 📝 Structured Logging: slog with JSON formatting and correlation IDs
  • 🎯 Auto-Instrumentation: HTTP/gRPC middleware patterns
  • 💚 Health Checks: Kubernetes-ready readiness/liveness probes
  • 🔄 Graceful Shutdown: Clean exporter shutdown and signal handling

When to Use This Skill

Activate this skill when:

  • Instrumenting microservices for production observability
  • Setting up distributed tracing across service boundaries
  • Creating operational dashboards with Prometheus/Grafana
  • Debugging production performance issues or bottlenecks
  • Implementing SLOs and monitoring SLIs
  • Adding observability to existing Go applications
  • Correlating logs, traces, and metrics for debugging

Core Observability Principles

The Three Pillars

1. Traces: Understand request flow across distributed systems 2. Metrics: Measure system behavior and performance over time 3. Logs: Record discrete events for debugging and audit

Correlation Strategy

All three pillars must share common identifiers:

  • Trace ID: Links all operations in a request
  • Span ID: Identifies specific operation within trace
  • Request ID: Correlates logs with traces and metrics

OpenTelemetry Integration

Installation

go get go.opentelemetry.io/otel
go get go.opentelemetry.io/otel/sdk
go get go.opentelemetry.io/otel/exporters/jaeger
go get go.opentelemetry.io/contrib/instrumentation/net/http/otelhttp

Basic Setup

package main

import (
    "context"
    "log"

    "go.opentelemetry.io/otel"
    "go.opentelemetry.io/otel/exporters/jaeger"
    "go.opentelemetry.io/otel/sdk/resource"
    sdktrace "go.opentelemetry.io/otel/sdk/trace"
    semconv "go.opentelemetry.io/otel/semconv/v1.21.0"
)

func initTracer(serviceName string) (*sdktrace.TracerProvider, error) {
    // Create Jaeger exporter
    exporter, err := jaeger.New(jaeger.WithCollectorEndpoint(
        jaeger.WithEndpoint("http://localhost:14268/api/traces"),
    ))
    if err != nil {
        return nil, err
    }

    // Create resource with service name
    res, err := resource.Merge(
        resource.Default(),
        resource.NewWithAttributes(
            semconv.SchemaURL,
            semconv.ServiceName(serviceName),
            semconv.ServiceVersion("1.0.0"),
        ),
    )
    if err != nil {
        return nil, err
    }

    // Create tracer provider
    tp := sdktrace.NewTracerProvider(
        sdktrace.WithBatcher(exporter),
        sdktrace.WithResource(res),
        sdktrace.WithSampler(sdktrace.AlwaysSample()), // Use probability sampler in production
    )

    otel.SetTracerProvider(tp)
    return tp, nil
}

func main() {
    tp, err := initTracer("order-service")
    if err != nil {
        log.Fatal(err)
    }
    defer func() {
        if err := tp.Shutdown(context.Background()); err != nil {
            log.Printf("Error shutting down tracer: %v", err)
        }
    }()

    // Application code...
}

Creating Spans

import (
    "context"

    "go.opentelemetry.io/otel"
    "go.opentelemetry.io/otel/attribute"
    "go.opentelemetry.io/otel/codes"
    "go.opentelemetry.io/otel/trace"
)

func ProcessOrder(ctx context.Context, order Order) error {
    tracer := otel.Tracer("order-service")
    ctx, span := tracer.Start(ctx, "ProcessOrder")
    defer span.End()

    // Add attributes
    span.SetAttributes(
        attribute.String("order.id", order.ID),
        attribute.Int("order.items", len(order.Items)),
        attribute.Float64("order.total", order.Total),
    )

    // Validate order (creates child span)
    if err := validateOrder(ctx, order); err != nil {
        span.RecordError(err)
        span.SetStatus(codes.Error, "validation failed")
        return err
    }

    // Fulfill order
    if err := fulfillOrder(ctx, order); err != nil {
        span.RecordError(err)
        span.SetStatus(codes.Error, "fulfillment failed")
        return err
    }

    span.SetStatus(codes.Ok, "order processed successfully")
    return nil
}

func validateOrder(ctx context.Context, order Order) error {
    _, span := otel.Tracer("order-service").Start(ctx, "validateOrder")
    defer span.End()

    // Validation logic...
    return nil
}

HTTP Middleware Instrumentation

import (
    "net/http"

    "go.opentelemetry.io/contrib/instrumentation/net/http/otelhttp"
)

func main() {
    // Wrap handler with automatic tracing
    handler := http.HandlerFunc(orderHandler)
    wrappedHandler := otelhttp.NewHandler(handler, "order-handler")

    http.Handle("/orders", wrappedHandler)
    http.ListenAndServe(":8080", nil)
}

// Manual instrumentation for more control
func orderHandler(w http.ResponseWriter, r *http.Request) {
    ctx := r.Context()
    tracer := otel.Tracer("order-service")

    ctx, span := tracer.Start(ctx, "orderHandler")
    defer span.End()

    // Extract order ID from request
    orderID := r.URL.Query().Get("id")
    span.SetAttributes(attribute.String("order.id", orderID))

    // Process order with propagated context
    order, err := fetchOrder(ctx, orderID)
    if err != nil {
        span.RecordError(err)
        http.Error(w, "Order not found", http.StatusNotFound)
        return
    }

    // ... handle response
}

Prometheus Metrics

Installation

go get github.com/prometheus/client_golang/prometheus
go get github.com/prometheus/client_golang/prometheus/promhttp

Metric Types and Patterns

package metrics

import (
    "github.com/prometheus/client_golang/prometheus"
    "github.com/prometheus/client_golang/prometheus/promauto"
)

var (
    // Counter: Monotonically increasing value
    httpRequestsTotal = promauto.NewCounterVec(
        prometheus.CounterOpts{
            Name: "http_requests_total",
            Help: "Total number of HTTP requests",
        },
        []string{"method", "path", "status"},
    )

    // Gauge: Value that can go up or down
    activeConnections = promauto.NewGauge(
        prometheus.GaugeOpts{
            Name: "active_connections",
            Help: "Number of active connections",
        },
    )

    // Histogram: Observations bucketed by value
    httpRequestDuration = promauto.NewHistogramVec(
        prometheus.HistogramOpts{
            Name:    "http_request_duration_seconds",
            Help:    "HTTP request duration in seconds",
            Buckets: prometheus.DefBuckets, // [0.005, 0.01, 0.025, 0.05, 0.1, 0.25, 0.5, 1, 2.5, 5, 10]
        },
        []string{"method", "path"},
    )

    // Summary: Similar to histogram but calculates quantiles
    dbQueryDuration = promauto.NewSummaryVec(
        prometheus.SummaryOpts{
            Name:       "db_query_duration_seconds",
            Help:       "Database query duration",
            Objectives: map[float64]float64{0.5: 0.05, 0.9: 0.01, 0.99: 0.001},
        },
        []string{"query_type"},
    )
)

Metrics Middleware

import (
    "net/http"
    "strconv"
    "time"

    "github.com/prometheus/client_golang/prometheus/promhttp"
)

// Metrics middleware that instruments all HTTP handlers
func MetricsMiddleware(next http.Handler) http.Handler {
    return http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
        start := time.Now()

        // Track active connections
        activeConnections.Inc()
        defer activeConnections.Dec()

        // Wrap response writer to capture status code
        rw := &responseWriter{ResponseWriter: w, statusCode: http.StatusOK}

        // Call next handler
        next.ServeHTTP(rw, r)

        // Record metrics
        duration := time.Since(start).Seconds()
        httpRequestDuration.WithLabelValues(r.Method, r.URL.Path).Observe(duration)
        httpRequestsTotal.WithLabelValues(r.Method, r.URL.Path, strconv.Itoa(rw.statusCode)).Inc()
    })
}

type responseWriter struct {
    http.ResponseWriter
    statusCode int
}

func (rw *responseWriter) WriteHeader(code int) {
    rw.statusCode = code
    rw.ResponseWriter.WriteHeader(code)
}

// Expose metrics endpoint
func main() {
    http.Handle("/metrics", promhttp.Handler())

    handler := MetricsMiddleware(http.HandlerFunc(orderHandler))
    http.Handle("/orders", handler)

    http.ListenAndServe(":8080", nil)
}

Custom Metrics Example

func ProcessPayment(ctx context.Context, payment Payment) error {
    timer := prometheus.NewTimer(dbQueryDuration.WithLabelValues("payment_insert"))
    defer timer.ObserveDuration()

    // Process payment
    if err := db.InsertPayment(payment); err != nil {
        httpRequestsTotal.WithLabelValues("POST", "/payments", "500").Inc()
        return err
    }

    httpRequestsTotal.WithLabelValues("POST", "/payments", "200").Inc()
    return nil
}

Structured Logging with slog

Basic Setup (Go 1.21+)

package main

import (
    "context"
    "log/slog"
    "os"
)

func initLogger() *slog.Logger {
    // JSON logger for production
    handler := slog.NewJSONHandler(os.Stdout, &slog.HandlerOptions{
        Level: slog.LevelInfo,
        AddSource: true, // Include file:line information
    })

    logger := slog.New(handler)
    slog.SetDefault(logger) // Set as default logger
    return logger
}

func main() {
    logger := initLogger()

    logger.Info("service starting",
        "service", "order-service",
        "version", "1.0.0",
        "port", 8080,
    )
}

Context-Aware Logging

import (
    "context"
    "log/slog"

    "go.opentelemetry.io/otel/trace"
)

// Add trace context to logger
func LoggerWithTrace(ctx context.Context) *slog.Logger {
    span := trace.SpanFromContext(ctx)
    spanCtx := span.SpanContext()

    return slog.With(
        "trace_id", spanCtx.TraceID().String(),
        "span_id", spanCtx.SpanID().String(),
    )
}

func HandleRequest(ctx context.Context, req Request) error {
    logger := LoggerWithTrace(ctx)

    logger.Info("processing request",
        "request_id", req.ID,
        "method", req.Method,
        "path", req.Path,
    )

    if err := processRequest(ctx, req); err != nil {
        logger.Error("request failed",
            "error", err,
            "duration_ms", time.Since(req.StartTime).Milliseconds(),
        )
        return err
    }

    logger.Info("request completed successfully",
        "duration_ms", time.Since(req.StartTime).Milliseconds(),
    )
    return nil
}

Log Levels and Structured Fields

func ProcessOrder(ctx context.Context, order Order) error {
    logger := LoggerWithTrace(ctx).With(
        "order_id", order.ID,
        "user_id", order.UserID,
    )

    logger.Debug("validating order", "items", len(order.Items))

    if len(order.Items) == 0 {
        logger.Warn("empty order received")
        return ErrEmptyOrder
    }

    logger.Info("order validation passed")

    if err := fulfillOrder(ctx, order); err != nil {
        logger.Error("fulfillment failed",
            "error", err,
            slog.Group("order_details",
                "total", order.Total,
                "items", len(order.Items),
            ),
        )
        return err
    }

    logger.Info("order processed successfully",
        "total", order.Total,
    )
    return nil
}

Health Checks and Graceful Shutdown

Health Check Endpoints

import (
    "context"
    "database/sql"
    "encoding/json"
    "net/http"
    "time"
)

type HealthChecker struct {
    db *sql.DB
    // Add other dependencies
}

type HealthStatus struct {
    Status      string            `json:"status"`
    Version     string            `json:"version"`
    Checks      map[string]string `json:"checks"`
    Timestamp   time.Time         `json:"timestamp"`
}

// Liveness probe - is the app running?
func (hc *HealthChecker) LivenessHandler(w http.ResponseWriter, r *http.Request) {
    w.Header().Set("Content-Type", "application/json")
    w.WriteHeader(http.StatusOK)
    json.NewEncoder(w).Encode(map[string]string{
        "status": "alive",
    })
}

// Readiness probe - is the app ready to serve traffic?
func (hc *HealthChecker) ReadinessHandler(w http.ResponseWriter, r *http.Request) {
    ctx, cancel := context.WithTimeout(r.Context(), 5*time.Second)
    defer cancel()

    status := HealthStatus{
        Status:    "ready",
        Version:   "1.0.0",
        Checks:    make(map[string]string),
        Timestamp: time.Now(),
    }

    // Check database
    if err := hc.db.PingContext(ctx); err != nil {
        status.Status = "not_ready"
        status.Checks["database"] = "unhealthy: " + err.Error()
        w.WriteHeader(http.StatusServiceUnavailable)
    } else {
        status.Checks["database"] = "healthy"
    }

    // Add more dependency checks (Redis, external APIs, etc.)

    w.Header().Set("Content-Type", "application/json")
    if status.Status == "ready" {
        w.WriteHeader(http.StatusOK)
    }
    json.NewEncoder(w).Encode(status)
}

Graceful Shutdown

import (
    "context"
    "net/http"
    "os"
    "os/signal"
    "syscall"
    "time"
)

func main() {
    // Initialize tracer
    tp, err := initTracer("order-service")
    if err != nil {
        log.Fatal(err)
    }

    // Setup HTTP server
    server := &http.Server{
        Addr:    ":8080",
        Handler: setupRoutes(),
    }

    // Channel for shutdown signals
    shutdown := make(chan os.Signal, 1)
    signal.Notify(shutdown, os.Interrupt, syscall.SIGTERM)

    // Start server in goroutine
    go func() {
        slog.Info("server starting", "port", 8080)
        if err := server.ListenAndServe(); err != http.ErrServerClosed {
            log.Fatal(err)
        }
    }()

    // Wait for shutdown signal
    <-shutdown
    slog.Info("shutdown signal received")

    // Create shutdown context with timeout
    ctx, cancel := context.WithTimeout(context.Background(), 30*time.Second)
    defer cancel()

    // Shutdown HTTP server
    slog.Info("shutting down HTTP server")
    if err := server.Shutdown(ctx); err != nil {
        slog.Error("HTTP server shutdown error", "error", err)
    }

    // Shutdown tracer provider (flush spans)
    slog.Info("shutting down tracer")
    if err := tp.Shutdown(ctx); err != nil {
        slog.Error("tracer shutdown error", "error", err)
    }

    slog.Info("shutdown complete")
}

Complete Instrumentation Example

package main

import (
    "context"
    "database/sql"
    "log/slog"
    "net/http"
    "os"
    "time"

    "github.com/prometheus/client_golang/prometheus/promhttp"
    "go.opentelemetry.io/contrib/instrumentation/net/http/otelhttp"
    "go.opentelemetry.io/otel"
    "go.opentelemetry.io/otel/attribute"
)

type Server struct {
    db     *sql.DB
    logger *slog.Logger
}

func (s *Server) orderHandler(w http.ResponseWriter, r *http.Request) {
    ctx := r.Context()

    // Get tracer and create span
    tracer := otel.Tracer("order-service")
    ctx, span := tracer.Start(ctx, "orderHandler")
    defer span.End()

    // Create context-aware logger with trace ID
    logger := s.logger.With(
        "trace_id", span.SpanContext().TraceID().String(),
        "request_id", r.Header.Get("X-Request-ID"),
    )

    orderID := r.URL.Query().Get("id")
    span.SetAttributes(attribute.String("order.id", orderID))

    logger.Info("fetching order", "order_id", orderID)

    // Fetch order from database
    order, err := s.fetchOrder(ctx, orderID)
    if err != nil {
        span.RecordError(err)
        logger.Error("failed to fetch order", "error", err)
        http.Error(w, "Order not found", http.StatusNotFound)
        return
    }

    logger.Info("order fetched successfully",
        "order_id", orderID,
        "items", len(order.Items),
    )

    // Return order as JSON
    w.Header().Set("Content-Type", "application/json")
    json.NewEncoder(w).Encode(order)
}

func (s *Server) fetchOrder(ctx context.Context, orderID string) (*Order, error) {
    _, span := otel.Tracer("order-service").Start(ctx, "fetchOrder")
    defer span.End()

    // Time database query
    start := time.Now()

    var order Order
    err := s.db.QueryRowContext(ctx, "SELECT * FROM orders WHERE id = ?", orderID).Scan(&order)

    duration := time.Since(start).Seconds()
    dbQueryDuration.WithLabelValues("select_order").Observe(duration)

    return &order, err
}

func setupRoutes(s *Server, hc *HealthChecker) http.Handler {
    mux := http.NewServeMux()

    // Health endpoints (no tracing needed)
    mux.HandleFunc("/health", hc.LivenessHandler)
    mux.HandleFunc("/ready", hc.ReadinessHandler)
    mux.Handle("/metrics", promhttp.Handler())

    // Business endpoints (with tracing)
    orderHandler := http.HandlerFunc(s.orderHandler)
    mux.Handle("/orders", otelhttp.NewHandler(orderHandler, "orders"))

    // Wrap everything with metrics middleware
    return MetricsMiddleware(mux)
}

Decision Trees

When to Use OpenTelemetry

Use OpenTelemetry When:

  • Building distributed systems with multiple services
  • Need to trace requests across service boundaries
  • Debugging performance issues in microservices
  • Want vendor-neutral observability (switch backends easily)
  • Require correlation between traces, metrics, and logs

Don't Use OpenTelemetry When:

  • Building simple monolithic applications
  • Performance overhead is critical (consider sampling)
  • Team lacks observability infrastructure (Jaeger, Zipkin)

When to Use Prometheus

Use Prometheus When:

  • Need time-series metrics for monitoring and alerting
  • Building operational dashboards (Grafana)
  • Measuring SLIs for SLO compliance
  • Tracking business metrics (requests/sec, conversion rates)
  • Kubernetes/containerized environments

Don't Use Prometheus When:

  • Need high-cardinality metrics (Prometheus has limits)
  • Require long-term metric storage (use Thanos/Cortex)
  • Need push-based metrics (Prometheus is pull-based)

When to Use slog

Use slog When:

  • Go 1.21+ projects (standard library, zero dependencies)
  • Need structured logging with JSON output
  • Want high-performance logging with minimal allocations
  • Integrating with log aggregation systems (Loki, ELK)

Don't Use slog When:

  • Go < 1.21 (use zap or zerolog instead)
  • Need complex log routing or filtering (use zap)
  • Require very specific features (audit trails, etc.)

Sampling Strategy Decision

Always Sample When:

  • Development/staging environments
  • Total traffic < 100 requests/sec
  • Debugging specific issues

Probabilistic Sampling When:

  • Production with moderate traffic (100-10K req/sec)
  • Sample rate: 1-10% typically

Tail-Based Sampling When:

  • High traffic production (>10K req/sec)
  • Only sample errors and slow requests
  • Requires tail-sampling processor (OpenTelemetry Collector)

Anti-Patterns to Avoid

❌ Not Propagating Context

WRONG: Breaking trace context

func processOrder(order Order) error {
    // Creates new context, loses trace!
    ctx := context.Background()
    return validateOrder(ctx, order)
}

CORRECT: Propagate context through call chain

func processOrder(ctx context.Context, order Order) error {
    // Propagates trace context
    return validateOrder(ctx, order)
}

❌ Cardinality Explosion

WRONG: Unbounded label values

// user_id can have millions of values!
httpRequests.WithLabelValues(r.Method, r.URL.Path, userID).Inc()

CORRECT: Use bounded labels

// Only method and path (bounded values)
httpRequests.WithLabelValues(r.Method, r.URL.Path).Inc()
// Track user-specific metrics separately if needed

❌ Logging Sensitive Data

WRONG: Exposing PII and secrets

logger.Info("user login",
    "email", user.Email,        // PII!
    "password", user.Password,  // CRITICAL!
    "token", authToken,         // SECRET!
)

CORRECT: Redact sensitive information

logger.Info("user login",
    "user_id", user.ID,  // Safe identifier
    "method", "password",
)

❌ Not Closing Spans

WRONG: Span leaks memory

func processOrder(ctx context.Context) error {
    ctx, span := tracer.Start(ctx, "processOrder")
    // Missing defer span.End()!

    if err := validate(); err != nil {
        return err  // Span never closed!
    }

    return nil
}

CORRECT: Always defer span.End()

func processOrder(ctx context.Context) error {
    ctx, span := tracer.Start(ctx, "processOrder")
    defer span.End()  // Always runs

    if err := validate(); err != nil {
        span.RecordError(err)
        return err
    }

    return nil
}

❌ Synchronous Metric Export

WRONG: Blocking requests with metric export

// Synchronous export blocks HTTP handler
exporter := jaeger.New(jaeger.WithCollectorEndpoint(...))
tp := sdktrace.NewTracerProvider(
    sdktrace.WithSyncer(exporter),  // BAD: Synchronous!
)

CORRECT: Use batching for async export

// Batching exports asynchronously
tp := sdktrace.NewTracerProvider(
    sdktrace.WithBatcher(exporter),  // GOOD: Async batching
)

❌ Missing Graceful Shutdown

WRONG: Losing traces on shutdown

func main() {
    tp, _ := initTracer("service")
    // Missing shutdown - spans lost!
    http.ListenAndServe(":8080", nil)
}

CORRECT: Shutdown exporters properly

func main() {
    tp, _ := initTracer("service")
    defer tp.Shutdown(context.Background())

    // Handle signals and graceful shutdown
    server.ListenAndServe()
}

Best Practices

1. Context Propagation: Always pass context.Context through call chains 2. Bounded Labels: Keep metric label cardinality under 1000 combinations 3. Sampling: Use probabilistic sampling in high-traffic production 4. Correlation IDs: Include trace_id in logs for correlation 5. Health Checks: Implement both /health (liveness) and /ready (readiness) 6. Graceful Shutdown: Flush traces and metrics before exit 7. Error Recording: Use span.RecordError() for automatic error tracking 8. Metric Naming: Follow Prometheus naming conventions (_total, _seconds) 9. Log Levels: Use appropriate levels (Debug, Info, Warn, Error) 10. Auto-Instrumentation: Use middleware for HTTP/gRPC when possible

Metric Naming Conventions

Follow Prometheus best practices:

Counter Metrics (always increasing):

  • http_requests_total (not http_requests)
  • payment_transactions_total
  • errors_total

Gauge Metrics (can go up or down):

  • active_connections
  • queue_size
  • memory_usage_bytes

Histogram/Summary Metrics (observations):

  • http_request_duration_seconds (not _milliseconds)
  • db_query_duration_seconds
  • response_size_bytes

Label Naming:

  • Use method, not http_method
  • Use status, not status_code or http_status
  • Use snake_case, not camelCase

Resources

Official Documentation:

  • OpenTelemetry Go: https://opentelemetry.io/docs/instrumentation/go/
  • Prometheus Client Library: https://github.com/prometheus/client_golang
  • Go slog Package: https://pkg.go.dev/log/slog

Recent Guides (2025):

  • "Observability in Go: What Real Engineers Are Saying in 2025" (Quesma Blog)
  • "Monitoring Go Apps with OpenTelemetry Metrics" (Better Stack, 2025)
  • Prometheus Best Practices: https://prometheus.io/docs/practices/naming/

Related Skills:

  • golang-web-frameworks: HTTP server patterns and middleware
  • golang-testing-strategies: Testing instrumented code
  • verification-before-completion: Validating observability setup

Quick Reference

Initialize OpenTelemetry

tp, _ := initTracer("service-name")
defer tp.Shutdown(context.Background())

Create Spans

ctx, span := otel.Tracer("name").Start(ctx, "operation")
defer span.End()
span.SetAttributes(attribute.String("key", "value"))

Define Metrics

counter := promauto.NewCounterVec(opts, []string{"label"})
histogram := promauto.NewHistogramVec(opts, []string{"label"})

Structured Logging

logger := slog.With("trace_id", traceID)
logger.Info("message", "key", value)

Health Checks

http.HandleFunc("/health", livenessHandler)
http.HandleFunc("/ready", readinessHandler)

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Token Estimate: ~5,000 tokens (entry point + full content) Version: 1.0.0 Last Updated: 2025-12-03

Related skills

How it compares

Use for hands-on Go OTel SDK wiring; choose APM agent docs when a vendor-managed auto-instrumentation agent is already mandated.

FAQ

What telemetry does golang-observability-opentelemetry add?

golang-observability-opentelemetry instruments Go services with OpenTelemetry traces, metrics, and correlated logs. The skill wires OTLP exporters and context propagation so developers can debug cross-service failures and track SLOs.

Which Go workloads does this skill target?

golang-observability-opentelemetry focuses on Go HTTP and gRPC microservices needing production observability. Developers use it when retrofitting legacy Go APIs or bootstrapping telemetry before on-call rotations.

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