mirror of
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84 lines
3.6 KiB
YAML
84 lines
3.6 KiB
YAML
# This is a modern starter configuration for the statsd_exporter. It uses native
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# and classic histograms by default, as well as the fast glob matching without ordering.
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defaults:
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# Convert timers into histograms, which can be aggregated across instances. See below for an example of using a summary with pre-computed quantiles instead.
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observer_type: histogram
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histogram_options:
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# Expose native histograms.
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# A bucket spread factor of 1.1 allows for pretty good precision in
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# measuring latencies, as long as they are not spread too widely.
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native_histogram_bucket_factor: 1.1
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# If latency is spread too widely, the resolution is automatically reduced,
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# keeping within the maximum bucket count. 160 is the default maximum bucket
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# count in OpenTelemetry, and is a good default for most use cases.
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native_histogram_max_buckets: 160
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# Also expose classic histograms, with a spread of latency buckets from 5ms to 2.5s.
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buckets: [.005, .01, .025, .05, .1, .25, .5, 1, 2.5 ]
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# Metric can be optionally exposed as a summary. Set reasonable defaults for
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# that case. Only used with `observer_type: summary`.
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summary_options:
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quantiles:
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- quantile: 0.99
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error: 0.001
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- quantile: 0.95
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error: 0.01
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- quantile: 0.9
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error: 0.05
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- quantile: 0.5
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error: 0.005
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max_age: 5m
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age_buckets: 2
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buf_cap: 1000
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# Match using glob patterns by default, it is much faster than regex.
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match_type: glob
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# Sepecific matches take precedence over *, ignoring the order of the mapping rules.
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# Regex matches are always evaluated after glob matches, and do honor the
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# order of mapping rules. Avoid using regex matches where possible.
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glob_disable_ordering: true
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# Do not expire metrics by default. When deployed as a sidecar, and restarted
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# together with application deployments, this matches the behavior of native
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# in-application instrumentation. Set a reasonable TTL if the exporter has its
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# own lifecycle.
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ttl: 0
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mappings:
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# Example 1: This will be a histogram using the bucket configuration set in `defaults`.
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- match: "test.timing.*.*.*"
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name: "my_timer"
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help: "Latency of the application"
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labels:
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provider: "$2"
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outcome: "$3"
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job: "${1}_server"
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# Example 2: Use a much tighter bucket spread. Use this to track latencies in a
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# relatively narrow range. For classic histograms, we need to set the buckets
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# around this band manually; native histograms are sparse and adapt automatically.
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- match: "consistent_app.timing.*.*.*"
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name: "my_consistent_timer"
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help: "Latency of an application with a consistent latency pattern"
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histogram_options:
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native_histogram_bucket_factor: 1.005
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# For the sake of this example, set the buckets for a latency distribution
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# tightly clustered around 15ms.
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buckets: [0.01, 0.011, 0.012, 0.013, 0.014, 0.015, 0.016, 0.017, 0.018, 0.019, 0.02]
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labels:
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provider: "$2"
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outcome: "$3"
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job: "${1}_server"
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# Example 3: This will be a summary using the summary_options set in `defaults`
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#
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# Note: Summary metrics are not recommended because they can not be aggregated over multiple instances.
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- match: "other.distribution.*.*.*"
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observer_type: summary
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name: "other_distribution"
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labels:
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provider: "$2"
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outcome: "$3"
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job: "${1}_server_other"
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# Optional: drop all unmapped metrics. Keep this as the last mapping rule. Any
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# metric not matched otherwise will be dropped because "." matches all metrics.
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# Without this rule, all metrics will be exposed, with the metric name
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# automatically generated from the statsd metric name.
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# - match: "."
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# match_type: regex
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# action: drop
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# name: "dropped"
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