# Filters as processors

You can use any [filter](https://docs.fluentbit.io/manual/data-pipeline/filters) as a processor in Fluent Bit.

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Only [YAML configuration files](https://docs.fluentbit.io/manual/administration/configuring-fluent-bit/yaml) support processors.
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## Examples

The following examples show how to configure filters as processors.

### Grep

In this example, the [Grep](https://docs.fluentbit.io/manual/data-pipeline/filters/grep) filter is used as an input processor to filter log events based on a regular expression pattern:

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{% tab title="fluent-bit.yaml" %}

```yaml
parsers:
    - name: json
      format: json

pipeline:
    inputs:
        - name: tail
          path: /var/log/example.log
          parser: json

          processors:
              logs:
                  - name: grep
                    regex: log aa
    outputs:
        - name: stdout
          match: '*'
```

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### Lua

In this example configuration, an input plugin uses the [Lua](https://docs.fluentbit.io/manual/data-pipeline/filters/lua) filter as a processor to add a new key `hostname` with the value `monox`. Then, an output plugin adds a new key named `output` with the value `new data`.

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{% tab title="fluent-bit.yaml" %}

```yaml
  service:
    log_level: info
    http_server: on
    http_listen: 0.0.0.0
    http_port: 2021
  pipeline:
    inputs:
      - name: random
        tag: test-tag
        interval_sec: 1
        processors:
          logs:
            - name: modify
              add: hostname monox
            - name: lua
              call: append_tag
              code: |
                  function append_tag(tag, timestamp, record)
                     new_record = record
                     new_record["tag"] = tag
                     return 1, timestamp, new_record
                  end
    outputs:
      - name: stdout
        match: '*'
        processors:
          logs:
            - name: lua
              call: add_field
              code: |
                  function add_field(tag, timestamp, record)
                     new_record = record
                     new_record["output"] = "new data"
                     return 1, timestamp, new_record
                  end
```

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