zpm

func Bytes ¶

func Bytes(format expfmt.Format, opts ...expfmt.EncoderOption) (string, error)

Bytes ➕

@Summary Exports metrics as raw bytes in the specified format.
@Description This function exports the metrics as raw bytes in a specified format, allowing for further processing or transport.
@Tags metrics
@Produce application/octet-stream
@Param format query string true "The format to export the metrics in (e.g., 'text/plain')"
@Param options query string false "Additional encoding options"
@Usage Export metrics for machine-to-machine communication or internal processing.

func Counter ¶

func Counter(name string) *counter

Counter ➕

@Summary Creates a new counter metric.
@Description This function creates a counter, a cumulative metric that only increases. Suitable for tracking things like requests served, errors, etc.
@Tags metrics
@Produce text/plain
@Param name query string true "Name of the counter metric"
@Usage Tracking events such as processed jobs or HTTP requests.
@Misuse ❌ Using for fluctuating values (use Gauge instead).
@Misuse ❌ Decreasing a counter (use Gauge for that).
@Pros ✅ Ideal for cumulative data.
@Pros ✅ Works seamlessly with `rate()` and `increase()` Prometheus functions.
@Cons ⚠️ Cannot be decremented.
@Tricks 🔍 Use `rate()` for trend analysis over time.

func Export ¶

func Export(w io.Writer, expFormat expfmt.Format, opts ...expfmt.EncoderOption) error

Export ➕

@Summary Exports metrics in a specified format.
@Description This function exports cumulative metrics, such as counters, in a desired format. Common use cases include exporting metrics for Prometheus scraping.
@Tags metrics
@Produce text/plain
@Param format query string true "The format to export the metrics in, e.g., 'text/plain'"
@Param options query string false "Additional encoding options"
@Usage Export metrics like processed jobs, HTTP request counts, etc.
@Misuse ❌ Using for fluctuating values (use Gauge for that).
@Misuse ❌ Attempting to decrease a counter (use Gauge instead).
@Pros ✅ Efficient for tracking incremental data.
@Pros ✅ Works well with `rate()` and `increase()` for Prometheus queries.
@Cons ⚠️ Cannot be decremented, reset is needed on restart.
@Tricks 🔍 Use `rate()` to track trends over time.

func Gauge ¶

func Gauge(name string) *gauge

Gauge ⚖️

@Summary Creates a new gauge metric.
@Description This function creates a gauge, a metric that can increase or decrease. Suitable for tracking values like temperature, memory usage, or concurrent requests.
@Tags metrics
@Produce text/plain
@Param name query string true "Name of the gauge metric"
@Usage Tracking instantaneous values like RAM usage, active users.
@Misuse ❌ Using for cumulative counts (use Counter instead).
@Pros ✅ Works well for instantaneous values.
@Pros ✅ Can both increase and decrease over time.
@Cons ⚠️ Quick fluctuations may make trend analysis challenging.
@Tricks 📊 Use `avg_over_time()` to smooth out variations and identify trends.

func Histogram ¶

func Histogram(name string) *histogram

Histogram 📊

@Summary Creates a histogram metric for sampling observations.
@Description This function creates a histogram, which samples observations and categorizes them into configurable buckets. Useful for tracking durations or distributions.
@Tags metrics
@Produce text/plain
@Param name query string true "Name of the histogram metric"
@Usage Tracking response times, request sizes, or latencies.
@Misuse ❌ Too many buckets can lead to excessive memory usage.
@Pros ✅ Captures both the count and sum of observations.
@Pros ✅ Useful for estimating quantiles and understanding distributions.
@Cons ⚠️ Requires predefined bucket configuration.
@Cons ⚠️ `histogram_quantile()` can produce misleading results with small samples.
@Tricks ⚡ Use the `le` label (`le="+Inf"`) to track total count. 🛠️ Use `rate()` on `_bucket` metrics for percentile estimations.

func NewStorage ¶

func NewStorage() *storage

func RuntimeFuncName ¶

func RuntimeFuncName(skip int) string

func String ¶

func String(format expfmt.Format, opts ...expfmt.EncoderOption) (string, error)

String ➕

@Summary Exports metrics as a string in the specified format.
@Description This function exports the metrics as a string, supporting formats such as text/plain for Prometheus scraping or others as specified.
@Tags metrics
@Produce text/plain
@Param format query string true "The format to export the metrics in (e.g., 'text/plain')"
@Param options query string false "Additional encoding options"
@Usage Export metrics in a human-readable format or for Prometheus scraping.
@Misuse ❌ Using for non-cumulative metrics (use appropriate types).
@Tricks 📊 Use `rate()` in Prometheus queries for trend analysis.

func Summary ¶

func Summary(name string) *summary

Summary 💡

@Summary Creates a summary metric for tracking dynamic quantiles.
@Description This function creates a summary, a metric that calculates quantiles and total observations on the client side. Ideal for latency tracking where dynamic quantiles are needed.
@Tags metrics
@Produce text/plain
@Param name query string true "Name of the summary metric"
@Usage Tracking request durations with precomputed quantiles, useful for latency analysis.
@Misuse ❌ Hard to aggregate across multiple instances (unlike Histograms).
@Pros ✅ Provides dynamic quantiles without predefined buckets.
@Cons ⚠️ Requires more memory than Histograms.
@Tricks 🎯 Use `quantile(0.95, rate(my_summary{quantile!=""}[5m]))` to estimate the 95th percentile of request durations.