Add project layout information to the README (#40)
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README.md
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README.md
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@ -37,6 +37,30 @@ The number of reasons why you'd want to collect metrics is too large to list out
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- Scoped metrics for effortless nesting.
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- Bundled with Prometheus pull endpoint capabilities by default.
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## project layout
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Metrics provide a way to gather metrics from your application. Exporters provide a way to get data outside of the application and observers tell the exporters what format to use.
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Application developers can use the `metrics-runtime` crate to get running quickly.
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* [`metrics`]: Provides macros similar to the `log` crate.
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* [`metrics-core`]: Defines foundational traits for interoperable metrics libraries.
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* [`metrics-exporter-http`]: Exports metrics over an HTTP server.
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* [`metrics-exporter-log`]: Exports metrics by outputting to console using the `log` crate.
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* [`metrics-observer-json`]: Encodes metrics in the JSON format.
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* [`metrics-observer-prometheus`]: Encodes metrics in the Prometheus exposition format.
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* [`metrics-observer-text`]: Encodes metrics as text suitable for console logging.
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* [`metrics-runtime`]: A batteries included metrics library.
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* [`metrics-util`]: Helper library used in the metrics ecosystem.
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## performance
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High. `metrics` is fast enough that you'll barely notice the overhead.
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@ -41,4 +41,4 @@ The number of reasons why you'd want to collect metrics is too large to list out
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High. `metrics` is fast enough that you'll barely notice the overhead.
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There is a `benchmark` example in the crate that can be run to see the type of performance acheivable on your system. A 2015 MacBook Pro (4c/8t, 2.1GHz) can push over 5 million samples per second from a single thread.
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There is a `benchmark` example in the crate that can be run to see the type of performance achievable on your system. A 2015 MacBook Pro (4c/8t, 2.1GHz) can push over 5 million samples per second from a single thread.
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