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Prometheus go code review

Skill existential-birds/beagle/plugins/beagle-go/skills/prometheus-go-code-review

Reviews Prometheus instrumentation in Go code for proper metric types, labels, and patterns. Use when reviewing code with prometheus/client_golang metrics.From its SKILL.md

Install
npx -y skills add existential-birds/beagle --skill prometheus-go-code-review

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SKILL.md

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Prometheus Go Code Review

Review Checklist

  • Metric types match measurement semantics (Counter/Gauge/Histogram)
  • Labels have low cardinality (no user IDs, timestamps, paths)
  • Metric names follow conventions (snake_case, unit suffix)
  • Histograms use appropriate bucket boundaries
  • Metrics registered once, not per-request
  • Collectors don't panic on race conditions
  • /metrics endpoint exposed and accessible

Hard gates (sequenced)

Complete in order before recording a finding. Skip gates that clearly do not apply to the diff.

  1. Evidence scope — Enumerate the files you are reviewing that touch Prometheus (prometheus/client_golang, promauto, promhttp, or MustRegister). Pass: you have a concrete path list (from the diff or an explicit file set); no repo-wide claim without at least one path.

  2. Label cardinality — For each *Vec or labeled metric in scope, list label names and where values come from (constants, bounded codes, vs request-derived strings). Pass: no label uses unbounded values (e.g. raw user_id, full URL path, timestamps) unless the code uses a bounded mapping and you cite it.

  3. Registration lifecycle — For metric definitions in scope, confirm constructors run once (package-level var, init, or sync.Once), not inside per-request handlers. Pass: no pattern that allocates/registers a new Counter/Histogram/*Vec on every request for the same logical metric.

  4. Finding shape — Each finding names a file (and line or symbol where possible), states which gate (2 or 3) would fail if the issue is real, and ties to observed code. Pass: no standalone style nit when gates 2–3 are satisfied for that code.

Metric Type Selection

MeasurementTypeExample
Requests processedCounterrequests_total
Items in queueGaugequeue_length
Request durationHistogramrequest_duration_seconds
Concurrent connectionsGaugeactive_connections
Errors since startCountererrors_total
Memory usageGaugememory_bytes

Critical Anti-Patterns

1. High Cardinality Labels

// BAD - unique per user/request
counter := promauto.NewCounterVec(
    prometheus.CounterOpts{Name: "requests_total"},
    []string{"user_id", "path"},  // millions of series!
)
counter.WithLabelValues(userID, request.URL.Path).Inc()

// GOOD - bounded label values
counter := promauto.NewCounterVec(
    prometheus.CounterOpts{Name: "requests_total"},
    []string{"method", "status_code"},  // <100 series
)
counter.WithLabelValues(r.Method, statusCode).Inc()

2. Wrong Metric Type

// BAD - using gauge for monotonic value
requestCount := promauto.NewGauge(prometheus.GaugeOpts{
    Name: "http_requests",
})
requestCount.Inc()  // should be Counter!

// GOOD
requestCount := promauto.NewCounter(prometheus.CounterOpts{
    Name: "http_requests_total",
})
requestCount.Inc()

3. Registering Per-Request

// BAD - new metric per request
func handler(w http.ResponseWriter, r *http.Request) {
    counter := prometheus.NewCounter(...)  // creates new each time!
    prometheus.MustRegister(counter)       // panics on duplicate!
}

// GOOD - register once
var requestCounter = promauto.NewCounter(prometheus.CounterOpts{
    Name: "http_requests_total",
})

func handler(w http.ResponseWriter, r *http.Request) {
    requestCounter.Inc()
}

4. Missing Unit Suffix

// BAD
duration := promauto.NewHistogram(prometheus.HistogramOpts{
    Name: "request_duration",  // no unit!
})

// GOOD
duration := promauto.NewHistogram(prometheus.HistogramOpts{
    Name: "request_duration_seconds",  // unit in name
})

Good Patterns

Metric Definition

var (
    httpRequests = promauto.NewCounterVec(
        prometheus.CounterOpts{
            Namespace: "myapp",
            Subsystem: "http",
            Name:      "requests_total",
            Help:      "Total HTTP requests processed",
        },
        []string{"method", "status"},
    )

    httpDuration = promauto.NewHistogramVec(
        prometheus.HistogramOpts{
            Namespace: "myapp",
            Subsystem: "http",
            Name:      "request_duration_seconds",
            Help:      "HTTP request latencies",
            Buckets:   []float64{.005, .01, .025, .05, .1, .25, .5, 1, 2.5, 5, 10},
        },
        []string{"method"},
    )
)

Middleware Pattern

func metricsMiddleware(next http.Handler) http.Handler {
    return http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
        timer := prometheus.NewTimer(httpDuration.WithLabelValues(r.Method))
        defer timer.ObserveDuration()

        wrapped := &responseWriter{ResponseWriter: w, status: 200}
        next.ServeHTTP(wrapped, r)

        httpRequests.WithLabelValues(r.Method, strconv.Itoa(wrapped.status)).Inc()
    })
}

Exposing Metrics

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

func main() {
    http.Handle("/metrics", promhttp.Handler())
    http.ListenAndServe(":9090", nil)
}

Review Questions

  1. Are metric types correct (Counter vs Gauge vs Histogram)?
  2. Are label values bounded (no UUIDs, timestamps, paths)?
  3. Do metric names include units (_seconds, _bytes)?
  4. Are metrics registered once (not per-request)?
  5. Is /metrics endpoint properly exposed?

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