界面已本地化;技能介绍与说明文档按所选语言由 AI 自动翻译,代码、命令、路径和专业术语保留原文,以原作者文档为准。
探索技能
设计与创意 · SKILL.md

go-observability

go-observability

【设计与创意】Structured logging, distributed tracing, metrics, and health checks for Go services. Covers slog, OpenTelemetry, Prometheus, and observability best practices. Use when: "add logging", "structured logs", "add tracing", "OpenTelemetry", "add metrics", "Prometheus", "observability", "instrument this code". Not for: pprof profiling (go-performance-review…

独立 GitHub 快照 · 自动分类 · 以原作者文档为准

技能说明

GitHub

name: go-observability description: > Structured logging, distributed tracing, metrics, and health checks for Go services. Covers slog, OpenTelemetry, Prometheus, and observability best practices. Use when: "add logging", "structured logs", "add tracing", "OpenTelemetry", "add metrics", "Prometheus", "observability", "instrument this code". Not for: pprof profiling (go-performance-review), error handling (go-error-handling), health endpoints (go-api-design). user-invocable: true license: MIT compatibility: Designed for Claude Code or similar AI coding agents working on Go projects. Requires the Go toolchain. allowed-tools: Read Edit Write Glob Grep Bash(go:) Bash(gofmt:) metadata: author: eduardo-sl version: "1.2.0"

Go Observability

Observability is not optional for production services. Every service must produce structured logs, expose metrics, and propagate trace context. Use the stdlib log/slog for logging and OpenTelemetry for tracing and metrics.

Detailed reference material, loaded on demand:

  • references/slog.md — handler setup, logger injection, child loggers.
  • references/tracing.md — tracer provider, spans, propagation, shutdown.
  • references/metrics.md — metric definitions, HTTP instrumentation.

Read a reference file only when the section below is not enough.

1. Structured Logging with slog

Use log/slog (Go 1.21+) with a JSON handler in production. Every line is key-value pairs, never a formatted sentence:

// ✅ Good — structured, leveled
logger.Info("user created", slog.String("user_id", user.ID), slog.Duration("latency", elapsed))

// ❌ Bad — unparseable in production
log.Printf("user %s created in %v", user.ID, elapsed)

Inject the logger as a dependency; never reach for a package-level global. Derive child loggers with logger.With(...) so component, method and request ID are attached once instead of at every call site. See references/slog.md.

Log levels — use them consistently

LevelUse for
DebugVerbose diagnostic info, disabled in production
InfoNormal operations: request received, job completed
WarnRecoverable issues: retry succeeded, deprecated usage
ErrorFailures requiring attention: DB down, external call failed

NEVER log at Error level for expected conditions (user not found → Info or Warn).

Sensitive data — NEVER log

  • Passwords, tokens, API keys
  • Full credit card numbers, SSNs
  • Raw request bodies containing PII
// ✅ Good — redacted
logger.Info("auth attempt", slog.String("user", email), slog.Bool("success", ok))

// ❌ Bad — leaks credentials
logger.Info("auth attempt", slog.String("password", password))

2. Distributed Tracing with OpenTelemetry

Start a span for every operation worth seeing on a waterfall — inbound requests, DB calls, outbound HTTP, meaningful business steps — and always defer span.End().

Rules the reference examples follow:

  • Name the span after the operation (GetUser, db.query), never after the fully-qualified function, and never doStuff.
  • On failure call span.RecordError(err) and span.SetStatus(codes.Error, ...), or the trace shows a green span for a failed request.
  • Pass ctx down the whole chain. A context.Background() mid-chain silently starts a new trace and breaks the parent link.

Setup and examples in references/tracing.md.

3. Metrics with OpenTelemetry / Prometheus

TypeUse forExample
CounterMonotonically increasing valuesRequests total, errors total
GaugeValues that go up and downActive connections, queue depth
HistogramDistribution of valuesRequest latency, response size

Naming is <namespace>_<subsystem>_<name>_<unit>:

http_request_duration_seconds     ✅ (unit in name)
http_requests_total               ✅ (counter with _total suffix)
db_connections_active             ✅ (gauge, no suffix needed)
user_signups                      ❌ (missing _total for counter)
requestLatency                    ❌ (camelCase, no unit)

Keep cardinality bounded. Label with the route pattern, method and status — never a user ID, request ID or raw r.URL.Path, each of which mints a new time series per value and eventually takes the metrics backend down.

Definitions and middleware in references/metrics.md.

4. Connecting Logs, Traces, and Metrics

A log line without a trace ID cannot be joined to the request that produced it. Pull trace.SpanContextFromContext(ctx) and attach trace_id and span_id to the logger at the top of each handler or service method.

5. Graceful Shutdown of Telemetry

The batch span processor holds spans in memory. Call tp.Shutdown(ctx) with its own timeout on the way out, or the last seconds before a crash — the interesting ones — never reach the collector.

Both examples in references/tracing.md.

Verification Checklist

  1. All logging uses log/slog with structured key-value pairs, not fmt.Printf or log.Printf
  2. Logger is injected as a dependency, not used as a global
  3. No sensitive data (passwords, tokens, PII) in log output
  4. Trace context is propagated through all function calls via context.Context
  5. Spans are created for significant operations (DB calls, HTTP requests, business logic)
  6. Spans record errors with span.RecordError(err) and set error status
  7. Metrics follow naming conventions: _seconds, _total, _bytes
  8. No high-cardinality labels (user IDs, request IDs) in metrics
  9. Telemetry providers are shut down gracefully on service exit
  10. Trace IDs are included in log entries for correlation
我的收藏