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Merge pull request #2012 from fluent/lynettemiles/sc-143159/final-vale-cleanup-for-concepts
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concepts/buffering.md

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Fluent Bit buffering strategies are designed to solve problems associated with backpressure and general delivery failures. Fluent Bit offers a primary buffering mechanism in memory and an optional secondary one using the file system. With this hybrid solution you can accommodate any use case safely and keep a high performance while processing your data.
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These mechanisms aren't mutually exclusive. When data is ready to be processed or delivered it's always be in memory, while other data in the queue might be in the file system until is ready to be processed and moved up to memory.
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These mechanisms aren't mutually exclusive. When data is ready to be processed or delivered it's always be in memory. Other data in the queue might be in the file system until is ready to be processed and moved up to memory.
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To learn more about the buffering configuration in Fluent Bit, see [Buffering and Storage](../administration/buffering-and-storage.md).

concepts/data-pipeline/router.md

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Routing reads the `Input` `Tag` and the `Output` `Match` rules. If data has a `Tag` that doesn't match at routing time, the data is deleted.
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## Routing with Wildcard
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## Routing with wildcards
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Routing is flexible enough to support wildcards in the `Match` pattern. The following example defines a common destination for both sources of data:
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The match rule is set to `my_*`, which matches any Tag starting with `my_`.
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## Routing with Regex
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## Routing with regular expressions
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Routing also provides support for regular expressions with the `Match_Regex` pattern, allowing for more complex and precise matching criteria. The following example demonstrates how to route data from sources based on a regular expression:
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concepts/key-concepts.md

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- Match
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- Structured Message
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## Event or Record
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## Events or records
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Every incoming piece of data that belongs to a log or a metric that's retrieved by Fluent Bit is considered an _Event_ or a _Record_.
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