
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)
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| Installs | 293 |
|---|---|
| repo stars | ★ 63 |
| Last updated | July 18, 2026 |
| Repository | bobmatnyc/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
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/otelhttpBasic 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/promhttpMetric 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(nothttp_requests)payment_transactions_totalerrors_total
Gauge Metrics (can go up or down):
active_connectionsqueue_sizememory_usage_bytes
Histogram/Summary Metrics (observations):
http_request_duration_seconds(not_milliseconds)db_query_duration_secondsresponse_size_bytes
Label Naming:
- Use
method, nothttp_method - Use
status, notstatus_codeorhttp_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)---
Token Estimate: ~5,000 tokens (entry point + full content) Version: 1.0.0 Last Updated: 2025-12-03
{
"name": "golang-observability-opentelemetry",
"version": "1.0.0",
"category": "toolchain",
"toolchain": "golang",
"framework": "observability",
"tags": [
"observability",
"golang",
"opentelemetry",
"prometheus",
"tracing",
"metrics",
"logging",
"slog"
],
"entry_point_tokens": 150,
"full_tokens": 6126,
"related_skills": [
"golang-http-frameworks",
"golang-testing-strategies"
],
"author": "Claude MPM",
"license": "MIT"
}
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.