Enum openmetrics_parser::OpenMetricsType

pub enum OpenMetricsType {
    Counter,
    Gauge,
    Histogram,
    GaugeHistogram,
    StateSet,
    Summary,
    Info,
    Unknown,
}

Variants

Counter

A Counter that only goes up Counters measure discrete events. Common examples are the number of HTTP requests received, CPU seconds spent, or bytes sent. For counters how quickly they are increasing over time is what is of interest to a user. A MetricPoint in a Metric with the type Counter MUST have one value called Total. A Total is a non-NaN and MUST be monotonically non-decreasing over time, starting from 0. A MetricPoint in a Metric with the type Counter SHOULD have a Timestamp value called Created. This can help ingestors discern between new metrics and long-running ones it did not see before. A MetricPoint in a Metric’s Counter’s Total MAY reset to 0. If present, the corresponding Created time MUST also be set to the timestamp of the reset. A MetricPoint in a Metric’s Counter’s Total MAY have an exemplar.

Gauge

A Gauge that can go up or down https://github.com/OpenObservability/OpenMetrics/blob/main/specification/OpenMetrics.md#gauge Gauges are current measurements, such as bytes of memory currently used or the number of items in a queue. For gauges the absolute value is what is of interest to a user. A MetricPoint in a Metric with the type gauge MUST have a single value. Gauges MAY increase, decrease, or stay constant over time. Even if they only ever go in one direction, they might still be gauges and not counters. The size of a log file would usually only increase, a resource might decrease, and the limit of a queue size may be constant. A gauge MAY be used to encode an enum where the enum has many states and changes over time, it is the most efficient but least user friendly.

Histogram

A Histogram that has a number of buckets that count events, and a _sum and count https://github.com/OpenObservability/OpenMetrics/blob/main/specification/OpenMetrics.md#histogram Histograms measure distributions of discrete events. Common examples are the latency of HTTP requests, function runtimes, or I/O request sizes. A Histogram MetricPoint MUST contain at least one bucket, and SHOULD contain Sum, and Created values. Every bucket MUST have a threshold and a value. Histogram MetricPoints MUST have at least a bucket with an +Inf threshold. Buckets MUST be cumulative. As an example for a metric representing request latency in seconds its values for buckets with thresholds 1, 2, 3, and +Inf MUST follow value_1 <= value_2 <= value_3 <= value+Inf. If ten requests took 1 second each, the values of the 1, 2, 3, and +Inf buckets MUST equal 10. The +Inf bucket counts all requests. If present, the Sum value MUST equal the Sum of all the measured event values. Bucket thresholds within a MetricPoint MUST be unique. Semantically, Sum, and buckets values are counters so MUST NOT be NaN or negative. Negative threshold buckets MAY be used, but then the Histogram MetricPoint MUST NOT contain a sum value as it would no longer be a counter semantically. Bucket thresholds MUST NOT equal NaN. Count and bucket values MUST be integers. A Histogram MetricPoint SHOULD have a Timestamp value called Created. This can help ingestors discern between new metrics and long-running ones it did not see before. A Histogram’s Metric’s LabelSet MUST NOT have a “le” label name. Bucket values MAY have exemplars. Buckets are cumulative to allow monitoring systems to drop any non-+Inf bucket for performance/anti-denial-of-service reasons in a way that loses granularity but is still a valid Histogram.

GaugeHistogram

GaugeHistograms measure current distributions. Common examples are how long items have been waiting in a queue, or size of the requests in a queue. A GaugeHistogram MetricPoint MUST have at least one bucket with an +Inf threshold, and SHOULD contain a Gsum value. Every bucket MUST have a threshold and a value. The buckets for a GaugeHistogram follow all the same rules as for a Histogram. The bucket and Gsum of a GaugeHistogram are conceptually gauges, however bucket values MUST NOT be negative or NaN. If negative threshold buckets are present, then sum MAY be negative. Gsum MUST NOT be NaN. Bucket values MUST be integers. A GaugeHistogram’s Metric’s LabelSet MUST NOT have a “le” label name. Bucket values can have exemplars. Each bucket covers the values less and or equal to it, and the value of the exemplar MUST be within this range. E Exemplars SHOULD be put into the bucket with the highest value. A bucket MUST NOT have more than one exemplar.

StateSet

StateSets represent a series of related boolean values, also called a bitset. If ENUMs need to be encoded this MAY be done via StateSet. A point of a StateSet metric MAY contain multiple states and MUST contain one boolean per State. States have a name which are Strings. A StateSet Metric’s LabelSet MUST NOT have a label name which is the same as the name of its MetricFamily. If encoded as a StateSet, ENUMs MUST have exactly one Boolean which is true within a MetricPoint. This is suitable where the enum value changes over time, and the number of States isn’t much more than a handful.

Summary

Summaries also measure distributions of discrete events and MAY be used when Histograms are too expensive and/or an average event size is sufficient. They MAY also be used for backwards compatibility, because some existing instrumentation libraries expose precomputed quantiles and do not support Histograms. Precomputed quantiles SHOULD NOT be used, because quantiles are not aggregatable and the user often can not deduce what timeframe they cover. A Summary MetricPoint MAY consist of a Count, Sum, Created, and a set of quantiles. Semantically, Count and Sum values are counters so MUST NOT be NaN or negative. Count MUST be an integer. A MetricPoint in a Metric with the type Summary which contains Count or Sum values SHOULD have a Timestamp value called Created. This can help ingestors discern between new metrics and long-running ones it did not see before. Created MUST NOT relate to the collection period of quantile values. Quantiles are a map from a quantile to a value. An example is a quantile 0.95 with value 0.2 in a metric called myapp_http_request_duration_seconds which means that the 95th percentile latency is 200ms over an unknown timeframe. If there are no events in the relevant timeframe, the value for a quantile MUST be NaN. A Quantile’s Metric’s LabelSet MUST NOT have “quantile” label name. Quantiles MUST be between 0 and 1 inclusive. Quantile values MUST NOT be negative. Quantile values SHOULD represent the recent values. Commonly this would be over the last 5-10 minutes.

Info

Info metrics are used to expose textual information which SHOULD NOT change during process lifetime. Common examples are an application’s version, revision control commit, and the version of a compiler. A MetricPoint of an Info Metric contains a LabelSet. An Info MetricPoint’s LabelSet MUST NOT have a label name which is the same as the name of a label of the LabelSet of its Metric. Info MAY be used to encode ENUMs whose values do not change over time, such as the type of a network interface. MetricFamilies of type Info MUST have an empty Unit string.

Unknown

Unknown SHOULD NOT be used. Unknown MAY be used when it is impossible to determine the types of individual metrics from 3rd party systems. A point in a metric with the unknown type MUST have a single value.

Trait Implementations

impl Clone for OpenMetricsType

fn clone(&self) -> OpenMetricsType

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for OpenMetricsType

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for OpenMetricsType

fn default() -> Self

Returns the “default value” for a type.

impl PartialEq for OpenMetricsType

fn eq(&self, other: &OpenMetricsType) -> bool

This method tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

This method tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl TryFrom<&str> for OpenMetricsType

type Error = ParseError

The type returned in the event of a conversion error.

fn try_from(value: &str) -> Result<Self, Self::Error>

Performs the conversion.

impl Copy for OpenMetricsType

impl StructuralPartialEq for OpenMetricsType