Prometheus Go Code Review

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name: prometheus-go-code-review description: Reviews Prometheus instrumentation in Go code for proper metric types, labels, and patterns. Use when reviewing code with prometheus/client_golang metrics.

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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

| Measurement | Type | Example | |-------------|------|---------| | Requests processed | Counter | requests_total | | Items in queue | Gauge | queue_length | | Request duration | Histogram | request_duration_seconds | | Concurrent connections | Gauge | active_connections | | Errors since start | Counter | errors_total | | Memory usage | Gauge | memory_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?