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fmt fix
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opentelemetry/src/lib.rs

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//! ```
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//!
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//! See the [examples](https://github.com/open-telemetry/opentelemetry-rust/tree/main/examples) directory for different integration patterns.
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//!
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//!
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//! See the [`trace`] module docs for more information on creating and managing
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//! spans.
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//!
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//! [`opentelemetry-otlp`]. This reduces reporting overhead while ensuring
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//! up-to-date data. The aggregation strategy and export interval can be
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//! customized in the [`opentelemetry_sdk`] based on your use case.
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//!
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//!
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//! ## Choosing the Right Instrument
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//! Selecting the correct instrument is critical for accurately representing
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//! your metrics data:
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//! current state, such as CPU usage, temperature etc.
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//! - Use **Histograms** for measuring the distribution of a value, such as
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//! response times or payload sizes.
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//!
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//!
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//! ### Observable Instruments
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//!
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//!
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//! Counters, UpDownCounters, and Gauges have Observable variants that allow
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//! values to be reported through a callback function. Observable instruments
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//! are ideal when the metric value is managed elsewhere and needs to be
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//!
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//! // Record a measurement by passing the value and a set of attributes.
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//! counter.add(1, &[KeyValue::new("http.client_ip", "83.164.160.102")]);
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//!
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//!
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//! // Create an ObservableCounter and register a callback that reports the measurement.
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//! let _observable_counter = meter
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//! .u64_observable_counter("my_observable_counter")
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//! [examples](https://github.com/open-telemetry/opentelemetry-rust/tree/main/examples/metrics-basic)
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//! directory that show a runnable example with all type of instruments.
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//!
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//!
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//!
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//! See the [`metrics`] module docs for more information on creating and
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//! managing instruments.
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//!

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