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Counter, gauge, and histogram base metrics for Go
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daniel-nichter/go-metrics
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Package metrics provides base metric types: counter, gauge, and histogram.
This package differs from other Go metric packages in three significant ways:
Metrics: Only base metric types are provide (counter, gauge, histogram). There are no sinks, registries, or derivative metric types. These should be implement by other packages which import this package.
Sampling: Only"Algorithm R" by Jeffrey Vitter is used to sample values for Gauge and Histogram. The reservoir size is fixed at 2,000. Testing with real-world values shows that smaller and larger sizes yield no benefit.And the true maximum value is kept and reported, which is not a feature of the original Algorithm R but critical for application performance monitoring.
Percentiles: Both nearest rank and linear interpolation are used calculate percentile values. If the sample is full (>= 2,000 values), nearest rank is used; else, "Definition 8"--better known as "R8"--is used (Hyndman and Fan (1996)). Testing with real-world values shows that this combination produces more accurate P999 (99.9th percentile) values, which is the gold standard for high-performance, low-latency applications.
This is not a full-feature metrics package with various sampling algorithms, data sinks, etc. It isnot right for:
- Streaming metrics (never resetting sample)
- Trending or smoothing (1/5/15 min. moving avg.)
- Derivative/hybrid metrics (timers, sets, etc.)
Those requirements are better handled by specialized algorithms, higher-level code abstractions, and metrics system like Datadog, SignalFx, Prometheus, etc. For example, trending/smoothing should be computed from time series data rather than storing and reporting 1/5/15 minutes of data.
This package does one thing very well: base app metrics:counters, gauges, and histograms. It is right for:
- Latency/response time in micro and milliseconds (with spikes >1s)
- 99.9th percentile—the gold standard for high-performance, low-latency apps
- Building block for an open-source program to provide its own metrics
Doing only one things makes it very easy to understand and use.Read the docs to see how.
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Counter, gauge, and histogram base metrics for Go
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