Merge branch '1.4.x' into 1.5.x
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fe50b2019e
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@ -28,7 +28,6 @@ import org.springframework.boot.actuate.metrics.buffer.GaugeBuffers;
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import org.springframework.boot.actuate.metrics.export.Exporter;
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import org.springframework.boot.actuate.metrics.export.MetricCopyExporter;
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import org.springframework.boot.actuate.metrics.repository.InMemoryMetricRepository;
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import org.springframework.boot.actuate.metrics.repository.MetricRepository;
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import org.springframework.boot.actuate.metrics.writer.DefaultCounterService;
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import org.springframework.boot.actuate.metrics.writer.DefaultGaugeService;
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import org.springframework.boot.actuate.metrics.writer.MetricWriter;
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@ -46,12 +45,12 @@ import org.springframework.messaging.MessageChannel;
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* user-facing {@link GaugeService} and {@link CounterService} instances, and also back
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* end repositories to catch the data pumped into them.
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* <p>
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* An {@link InMemoryMetricRepository} is always created unless another
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* {@link MetricRepository} is already provided by the user. In general, even if metric
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* data needs to be stored and analysed remotely, it is recommended to use an in-memory
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* repository to buffer metric updates locally. The values can be exported (e.g. on a
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* periodic basis) using an {@link Exporter}, most implementations of which have
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* optimizations for sending data to remote repositories.
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* In general, even if metric data needs to be stored and analysed remotely, it is
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* recommended to use in-memory storage to buffer metric updates locally as is done by the
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* default {@link InMemoryMetricRepository} (Java 7) or {@link CounterBuffers} and
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* {@link GaugeBuffers} (Java 8). The values can be exported (e.g. on a periodic basis)
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* using an {@link Exporter}, most implementations of which have optimizations for sending
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* data to remote repositories.
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* <p>
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* If Spring Messaging is on the classpath and a {@link MessageChannel} called
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* "metricsChannel" is also available, all metric update events are published additionally
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