# Filters

In production environments you need full control of the data you're collecting. Filtering lets you alter the collected data before delivering it to a destination.

{% @mermaid/diagram content="graph LR
accTitle: Fluent Bit data pipeline
accDescr: A diagram of the Fluent Bit data pipeline, which includes input, a parser, a filter, a buffer, routing, and various outputs.
A\[Input] --> B\[Parser]
B --> C\[Filter]
C --> D\[Buffer]
D --> E((Routing))
E --> F\[Output 1]
E --> G\[Output 2]
E --> H\[Output 3]
style C stroke:darkred,stroke-width:2px;" %}

Filtering is implemented through plugins. Each available filter can be used to match, exclude, or enrich your logs with specific metadata.

Fluent Bit support many filters. A common use case for filtering is Kubernetes deployments. Every pod log needs the proper metadata associated with it.

Like input plugins, filters run in an instance context, which has its own independent configuration. Configuration keys are often called *properties*.


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.fluentbit.io/manual/4.1/data-pipeline/filters.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.