forked from mirrors/statsd_exporter
Adding docs for new options
Signed-off-by: Pedro Tanaka <pedro.tanaka@shopify.com>
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11
README.md
11
README.md
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@ -403,6 +403,8 @@ mappings:
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observer_type: histogram
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observer_type: histogram
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histogram_options:
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histogram_options:
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buckets: [ 0.01, 0.025, 0.05, 0.1 ]
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buckets: [ 0.01, 0.025, 0.05, 0.1 ]
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native_histogram_bucket_factor: 1.1
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native_histogram_max_buckets: 256
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name: "my_timer"
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name: "my_timer"
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labels:
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labels:
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provider: "$2"
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provider: "$2"
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@ -416,6 +418,11 @@ values](https://godoc.org/github.com/prometheus/client_golang/prometheus#pkg-var
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are used for the histogram buckets:
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are used for the histogram buckets:
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`[.005, .01, .025, .05, .1, .25, .5, 1, 2.5, 5, 10]`.
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`[.005, .01, .025, .05, .1, .25, .5, 1, 2.5, 5, 10]`.
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`+Inf` is added automatically.
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`+Inf` is added automatically.
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If your Prometheus server is enabled to scrape native histograms (v2.40.0+),
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then you can set the `native_histogram_bucket_factor` to configure precision of the
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buckets in the sparse histogram. More about this in the original [client_golang docs](https://github.com/prometheus/client_golang/blob/449b46435075e6e069e05af920fe028b941033cf/prometheus/histogram.go#L399-L430).
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Also, a configuration of the maximum number of buckets can be set with `native_histogram_max_buckets`, this
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avoids the histograms to grow too large in memory. More about this in the original [client_golang docs](https://github.com/prometheus/client_golang/blob/449b46435075e6e069e05af920fe028b941033cf/prometheus/histogram.go#L443-L467).
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`observer_type` is only used when the statsd metric type is a timer, histogram, or distribution.
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`observer_type` is only used when the statsd metric type is a timer, histogram, or distribution.
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`buckets` is only used when the statsd metric type is one of these, and the `observer_type` is set to `histogram`.
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`buckets` is only used when the statsd metric type is one of these, and the `observer_type` is set to `histogram`.
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@ -470,6 +477,8 @@ defaults:
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observer_type: histogram
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observer_type: histogram
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histogram_options:
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histogram_options:
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buckets: [.005, .01, .025, .05, .1, .25, .5, 1, 2.5 ]
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buckets: [.005, .01, .025, .05, .1, .25, .5, 1, 2.5 ]
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native_histogram_bucket_factor: 1.1
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native_histogram_max_buckets: 256
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summary_options:
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summary_options:
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quantiles:
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quantiles:
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- quantile: 0.99
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- quantile: 0.99
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@ -549,7 +558,7 @@ Possible values for `match_metric_type` are `gauge`, `counter` and `observer`.
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There is a cache used to improve the performance of the metric mapping, that can greatly improvement performance.
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There is a cache used to improve the performance of the metric mapping, that can greatly improvement performance.
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The cache has a default maximum of 1000 unique statsd metric names -> prometheus metrics mappings that it can store.
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The cache has a default maximum of 1000 unique statsd metric names -> prometheus metrics mappings that it can store.
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This maximum can be adjust using the `statsd.cache-size` flag.
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This maximum can be adjusted using the `statsd.cache-size` flag.
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If the maximum is reached, entries are by default rotated using the [least recently used replacement policy](https://en.wikipedia.org/wiki/Cache_replacement_policies#Least_recently_used_(LRU)). This strategy is optimal when memory is constrained as only the most recent entries are retained.
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If the maximum is reached, entries are by default rotated using the [least recently used replacement policy](https://en.wikipedia.org/wiki/Cache_replacement_policies#Least_recently_used_(LRU)). This strategy is optimal when memory is constrained as only the most recent entries are retained.
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