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Feat: add log processor docs (#6)
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Ethan Foo
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# jsonDecode
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# normalize
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## 功能
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用于日志切分处理。
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属于source interceptor。可指定只被某些source使用。
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## 具体参数
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### processors
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| `类型` | `是否必填` | `默认值` | `含义` |
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| ------- | ----------- | --------- | ------- |
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| map数组 | 必填 | 无 | 所有的处理processor数组 |
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配置的processor将按照顺序依次执行。包括以下：
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#### regex
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将指定字段进行正则提取。
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| `字段` | `类型` | `是否必填` | `默认值` | `含义` |
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| ---------- | ----------- | ----------- | --------- | -------- |
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| regex.pattern | string | 必填 | 无 | 正则解析规则 |
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| regex.target | string | 非必填 | body | 正则解析的目标字段 |
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!!! example
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```yaml
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interceptors:
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- type: normalize
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processors:
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- regex:
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pattern: '(?<ip>\S+) (?<id>\S+) (?<u>\S+) (?<time>\[.*?\]) (?<url>\".*?\") (?<status>\S+) (?<size>\S+)'
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```
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使用以上的正则表达式，可以将以下示例的日志：
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```
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10.244.0.1 - - [13/Dec/2021:12:40:48 +0000] "GET / HTTP/1.1" 404 683
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```
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转换成：
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```
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"ip": "10.244.0.1",
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"id": "-",
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"u": "-",
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"time": "[13/Dec/2021:12:40:48 +0000]",
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"url": "\"GET / HTTP/1.1\"",
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"status": "404",
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"s": "683"
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```
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具体配置的时候，建议先使用一些正则调试工具 (https://regex101.com/) 验证是否可以匹配。
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#### jsonDecode
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将指定字段json解析提取。
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| `字段` | `类型` | `是否必填` | `默认值` | `含义` |
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| ---------- | ----------- | ----------- | --------- | -------- |
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| jsonDecode.target | string | 非必填 | body | json decode的目标字段 |
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!!! example
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```yaml
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interceptors:
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- type: normalize
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processors:
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- jsonDecode: ~
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```
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#### split
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将指定字段通过分隔符进行提取。
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| `字段` | `类型` | `是否必填` | `默认值` | `含义` |
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| ---------- | ----------- | ----------- | --------- | -------- |
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| split.target | string | 非必填 | body | split的目标字段 |
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| split.separator | string | 必填 | 无 | 分隔符 |
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| split.max | int | 非必填 | -1 | 通过分割符分割后得到的最多的字段数 |
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| split.keys | string数组 | 必填 | 无 | 分割后字段对应的key |
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!!! example
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=== "base"
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```yaml
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interceptors:
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- type: normalize
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processors:
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- split:
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separator: '|'
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keys: ["time", "order", "service", "price"]
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```
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使用以上split配置可以将日志：
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```
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2021-08-08|U12345|storeCenter|13.14
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```
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转换成：
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```
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"time": "2021-08-08"
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"order": "U12345"
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"service": "storeCenter"
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"price: 13.14
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```
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=== "max"
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```yaml
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interceptors:
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- type: normalize
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processors:
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- split:
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separator: ' '
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max: 2
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keys: ["time", "content"]
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```
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通过增加`max`参数，可以控制最多分割的字段。
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比如以下日志:
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```
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2021-08-08 U12345 storeCenter 13.14
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```
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可以通过以上配置提取为:
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```
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"time": "2021-08-08"
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"content": "U12345 storeCenter 13.14"
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```
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#### drop
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丢弃指定字段。
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| `字段` | `类型` | `是否必填` | `默认值` | `含义` |
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| ---------- | ----------- | ----------- | --------- | -------- |
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| drop.target | string数组 | 必填 | 无 | drop的字段 |
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!!! example
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```yaml
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interceptors:
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- type: normalize
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processors:
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- drop:
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target: ["id", "body"]
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```
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#### rename
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重命名指定字段。
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| `字段` | `类型` | `是否必填` | `默认值` | `含义` |
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| ---------- | ----------- | ----------- | --------- | -------- |
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| rename.target | 数组 | 必填 | 无 | |
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| rename.target[n].from | string | 必填 | 无 | rename的目标 |
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| rename.target[n].to | string | 必填 | 无 | rename后的名称 |
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!!! example
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```yaml
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interceptors:
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- type: normalize
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processors:
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- rename:
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target:
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- from: "hello"
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to: "world"
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```
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#### add
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新增字段。
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| `字段` | `类型` | `是否必填` | `默认值` | `含义` |
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| ---------- | ----------- | ----------- | --------- | -------- |
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| add.target | map | 必填 | 无 | 新增的key:value值 |
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!!! example
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```yaml
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interceptors:
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- type: normalize
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processors:
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- add:
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target:
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hello: world
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```
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#### timestamp
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转换时间格式。
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| `字段` | `类型` | `是否必填` | `默认值` | `含义` |
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| ---------- | ----------- | ----------- | --------- | -------- |
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| timestamp.target | 数组 | 必填 | 无 | |
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| timestamp.target[n].from | string | 必填 | 无 | 指定转换时间格式的字段 |
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| timestamp.target[n].fromLayout | string | 必填 | 无 | 指定字段的时间格式(golang形式) |
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| timestamp.target[n].toLayout | string | 必填 | 无 | 转换后的时间格式(golang形式)，另外可为`unix`和`unix_ms` |
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| timestamp.target[n].toType | string | 非必填 | 无 | 转换后的时间字段类型 |
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!!! example
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```yaml
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interceptors:
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- type: normalize
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processors:
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- timestamp:
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target:
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- from: logtime
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fromLayout: ""
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toLayout: "unix"
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```
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以上的layout参数需要填写golang形式，可参考：
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```
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const (
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Layout = "01/02 03:04:05PM '06 -0700" // The reference time, in numerical order.
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ANSIC = "Mon Jan _2 15:04:05 2006"
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UnixDate = "Mon Jan _2 15:04:05 MST 2006"
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RubyDate = "Mon Jan 02 15:04:05 -0700 2006"
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RFC822 = "02 Jan 06 15:04 MST"
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RFC822Z = "02 Jan 06 15:04 -0700" // RFC822 with numeric zone
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RFC850 = "Monday, 02-Jan-06 15:04:05 MST"
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RFC1123 = "Mon, 02 Jan 2006 15:04:05 MST"
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RFC1123Z = "Mon, 02 Jan 2006 15:04:05 -0700" // RFC1123 with numeric zone
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RFC3339 = "2006-01-02T15:04:05Z07:00"
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RFC3339Nano = "2006-01-02T15:04:05.999999999Z07:00"
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Kitchen = "3:04PM"
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// Handy time stamps.
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Stamp = "Jan _2 15:04:05"
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StampMilli = "Jan _2 15:04:05.000"
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StampMicro = "Jan _2 15:04:05.000000"
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StampNano = "Jan _2 15:04:05.000000000"
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)
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```
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还可以根据实际情况修改。
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# 配置设计
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# 数据格式
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!!! info
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了解Loggie内部数据格式的设计，能帮助我们配置合适的日志处理和日志格式转换
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## 结构设计
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在Loggie内部的日志数据，会被存储为如下`key:value`的格式：
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!!! example
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```json
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"body": "xxxxxxx",
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"key1": "value1",
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"key2": "value2"
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```
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其中`body`为source接收到的原始内容，比如日志采集source，这里的`body`为文件采集到的原始日志数据。
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其他的字段，在Loggie内部被统一称为header。header里一般包括：
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- 系统保留字段。统一system开头，比如systemPipelineName、systemSourceName、systemState等
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- 用户使用的字段。比如用户自己添加到source里的fields字段，用户切分日志后得到的字段等
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默认Json格式输出示例如下：
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!!! example
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```json
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{
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"body": "01-Dec-2021 03:13:58.298 INFO [main] Starting service [Catalina]",
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"fields": {
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"test": "demo"
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},
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"systemPipelineName": "svcA",
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"systemSourceName": "accesslog",
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"systemState": {
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"nextOffset": 2790,
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"filename": "/tmp/log/a.log",
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"collectTime": "2021-12-12T11:58:12.141267+08:00",
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"contentBytes": 160,
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"jobUid": "39100914-16777234",
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"lineNumber": 39,
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"offset": 2630
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}
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}
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```
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## 格式转换
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如果以上的格式不满足需求，可以使用sink里的 **codec** 修改输出的字段：
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- [配置](../../reference/pipelines/sink/codec.md)
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- [使用示例](../best-practice/log-format.md)
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## 日志切分
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对于原始日志数据的切分与处理，请使用 **normalize interceptor**：
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- [配置](../../reference/pipelines/interceptor/normalize.md)
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- [使用示例](../best-practice/log-process.md)
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!!! caution
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格式转换和日志切分两者区别：
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- normalize interceptor除了可以drop `body`字段外，无法修改系统保留的字段（修改可能影响内部逻辑）。codec.transformer可以任意修改字段，但存在反序列化的性能开销。
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- normalize interceptor可以通过配置`belongTo`指定关联source使用，codec.transformer则为pipeline级别，同时可以在系统配置中使用defaults来全局生效。
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# 日志切分与处理
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> Loggie可使用[normalize interceptor](../../reference/pipelines/interceptor/normalize.md)来进行日志的切分和处理，将日志数据进行结构化的提取，同时可以对提取后的字段进行处理。
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> 建议先了解Loggie内部日志数据[schema设计](../architecture/schema.md)。
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!!! caution
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normalize interceptor只用于用户日志的处理，并不能转换system开头的系统保留字段，系统保留字段请参考[日志格式转换](./log-format.md)。
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## 需求场景
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最主要的是对日志进行切分解析提取和处理。
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比如以下日志：
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```
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01-Dec-2021 03:13:58.298 INFO [main] Starting service [Catalina]
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```
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我们可能会需要将其中的日期、日志级别解析出来，最终形成：
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```json
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{
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"time": "01-Dec-2021 03:13:58.298",
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"level": "INFO",
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"message": "[main] Starting service [Catalina]"
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}
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```
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这种结构化的数据，存储的时候便于过滤查询，或者根据日志里的时间来排序，而不是采集的时间戳，或者根据日志级别进行一些过滤，可以方便查询到ERROR级别的日志等等。
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当然不仅仅是像以上tomcat的运维类日志，还有诸如业务的一些订单等等日志，都有类似的需求和使用场景。
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## 功能
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目前已经支持的功能有：
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- regex: 正则切分提取日志
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- jsonDecode: 解析提取json格式的日志
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- split: 通过分隔符来提取日志
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- add/rename/drop指定字段
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- timestamp: 转换指定字段的时间格式
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normalize可以配置内部的processor顺序执行。
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## 配置示例
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日志切分处理在Loggie Agent端或者Loggie中转机侧均可，取决于我们是否需要中转机，以及希望日志处理这种CPU密集型的计算是分布在Agent上，由各个节点承担，还是希望在中转机集群中集中进行。
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下面以采集tomcat服务的标准输出和access日志为例，展示如何对标准输出格式进行处理和access日志进行字段切分。
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简单起见，示例使用CRD实例配置下发在Agent，同时使用dev sink直接输出处理结果展示。
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### sink
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创建如下的sink用于演示，将采集处理后的日志打印在所属节点Loggie的日志中。
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!!! example
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```yaml
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apiVersion: loggie.io/v1beta1
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kind: Sink
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metadata:
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name: default
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spec:
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sink: |
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type: dev
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printEvents: true
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codec:
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type: json
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pretty: true
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```
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### interceptor
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根据实际环境创建如下的interceptor。
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!!! example
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=== "docker"
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```yaml
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apiVersion: loggie.io/v1beta1
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kind: Interceptor
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metadata:
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name: tomcat
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spec:
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interceptors: |
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- type: normalize
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name: stdproc
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belongTo: ["stdout"]
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processors:
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- jsonDecode: ~
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- drop:
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target: ["stream", "time", "body"]
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- rename:
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target:
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- from: "log"
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to: "message"
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- type: normalize
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name: accproc
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belongTo: ["access"]
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processors:
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- regex:
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pattern: '(?<ip>\S+) (?<id>\S+) (?<u>\S+) (?<time>\[.*?\]) (?<url>\".*?\") (?<status>\S+) (?<size>\S+)'
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```
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=== "containerd"
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```yaml
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apiVersion: loggie.io/v1beta1
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kind: Interceptor
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metadata:
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name: tomcat
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spec:
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interceptors: |
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- type: normalize
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name: stdproc
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belongTo: ["stdout"]
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processors:
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- split:
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separator: ' '
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max: 4
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keys: ["time", "std", "F", "message"]
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- drop:
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target: ["time", "std", "F", "body"]
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- type: normalize
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name: accproc
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belongTo: ["access"]
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processors:
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- regex:
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pattern: '(?<ip>\S+) (?<id>\S+) (?<u>\S+) (?<time>\[.*?\]) (?<url>\".*?\") (?<status>\S+) (?<size>\S+)'
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```
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如果使用docker运行时，默认采集的标准输出为json格式。
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类似：
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```json
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{
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"log":"I0610 08:29:07.698664 Waiting for caches to sync\n",
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"stream":"stderr",
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"time":"2021-06-10T08:29:07.698731204Z"
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}
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```
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我们需要将json格式的原始日志解析，一般还需要drop `stream`和`time`字段，并将其中的`log`字段key改为和其他格式一致的`body`或者`message`。
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|
||||
使用filesource采集后，在Loggie里的原始格式为：
|
||||
```
|
||||
"body": '"log":"I0610 08:29:07.698664 Waiting for caches to sync\n","stream":"stderr", "time":"2021-06-10T08:29:07.698731204Z"'
|
||||
"systemXXX": xxx
|
||||
...
|
||||
```
|
||||
|
||||
在normalize interceptors里，使用:
|
||||
|
||||
1. **`jsonDecode`**:
|
||||
解析并提取字段，将Loggie里存储的日志格式变成：
|
||||
```
|
||||
"body": '"log":"I0610 08:29:07.698664 Waiting for caches to sync\n","stream":"stderr", "time":"2021-06-10T08:29:07.698731204Z"'
|
||||
"log": "I0610 08:29:07.698664 Waiting for caches to sync\n"
|
||||
"stream":"stderr"
|
||||
"time":"2021-06-10T08:29:07.698731204Z"
|
||||
"systemXXX": xxx
|
||||
...
|
||||
```
|
||||
|
||||
1. **`drop`**:
|
||||
将`body`、`stream`和`time`丢弃。（`body`为内置字段表示原始日志数据，仅能丢弃，不能修改）
|
||||
|
||||
3. **`rename`**:
|
||||
将`log`改名为统一的字段比如`message`。
|
||||
|
||||
最终发送的日志格式变成：
|
||||
```
|
||||
"message": "I0610 08:29:07.698664 Waiting for caches to sync\n"
|
||||
"systemXXX": xxx
|
||||
...
|
||||
```
|
||||
|
||||
|
||||
在runtime为containerd时，原始日志如下所示：
|
||||
|
||||
```
|
||||
2021-12-01T03:13:58.298476921Z stderr F INFO [main] Starting service [Catalina]
|
||||
```
|
||||
|
||||
会默认加上类似`2021-12-01T03:13:58.298476921Z stderr F`的前缀，一般我们并不需要这个日志，发送的时候只保留后面数据。
|
||||
和docker的方式类似，我们可以配置split等方式来切分处理。
|
||||
|
||||
另外，由于stdout的日志和access日志格式不一样，所以使用了两个不同的normalize interceptor，配置了不同的processor，需要添加`name`来区分。
|
||||
最重要的是，这里使用了`belongTo`指定关联的`source`，让stdout日志和access日志分别采用不同的处理逻辑。
|
||||
|
||||
### logconfig
|
||||
配置source如下所示：
|
||||
|
||||
!!! example
|
||||
|
||||
```yaml
|
||||
apiVersion: loggie.io/v1beta1
|
||||
kind: LogConfig
|
||||
metadata:
|
||||
name: tomcat
|
||||
namespace: default
|
||||
spec:
|
||||
selector:
|
||||
labelSelector:
|
||||
app: tomcat
|
||||
type: pod
|
||||
pipeline:
|
||||
interceptorRef: tomcat
|
||||
sinkRef: dev
|
||||
sources: |
|
||||
- type: file
|
||||
name: stdout
|
||||
paths:
|
||||
- stdout
|
||||
- type: file
|
||||
name: access
|
||||
paths:
|
||||
- /usr/local/tomcat/logs/localhost_access_log.*.txt
|
||||
```
|
||||
|
||||
注意这里的source.name和上面interceptor配置的belongTo需要关联上。
|
||||
|
||||
创建完以上的cr后，便可以采集指定的Pod日志，并进行切分处理。
|
||||
|
||||
|
||||
|
||||
|
||||
43
nav.yml
43
nav.yml
|
|
@ -19,6 +19,8 @@ nav:
|
|||
- 架构与特性:
|
||||
- 诞生背景: user-guide/architecture/background.md
|
||||
- 设计架构: user-guide/architecture/core-arch.md
|
||||
- 配置设计: user-guide/architecture/config.md
|
||||
- 数据格式: user-guide/architecture/schema.md
|
||||
- 优势与特性: user-guide/architecture/advantages.md
|
||||
- 开源项目对比: user-guide/architecture/compare.md
|
||||
|
||||
|
|
@ -31,7 +33,7 @@ nav:
|
|||
- 采集Kubernetes Events: user-guide/use-in-kubernetes/kube-event-source.md
|
||||
|
||||
- 最佳实践:
|
||||
- 发送日志格式转换: user-guide/best-practice/log-format.md
|
||||
- 日志格式转换: user-guide/best-practice/log-format.md
|
||||
- 日志切分与处理: user-guide/best-practice/log-process.md
|
||||
- 日志定时清理: user-guide/best-practice/log-clean.md
|
||||
|
||||
|
|
@ -53,26 +55,25 @@ nav:
|
|||
- 全局:
|
||||
- 启动参数与日志配置: reference/global/args.md
|
||||
- 系统配置: reference/global/system.md
|
||||
- Pipelines:
|
||||
- Overview: reference/pipelines/overview.md
|
||||
- Source:
|
||||
- file: reference/pipelines/source/file.md
|
||||
- kafka: reference/pipelines/source/kafka.md
|
||||
- kubeEvent: reference/pipelines/source/kubeEvent.md
|
||||
- Sink:
|
||||
- elasticsearch: reference/pipelines/sink/elasticsearch.md
|
||||
- kafka: reference/pipelines/sink/kafka.md
|
||||
- dev: reference/pipelines/sink/dev.md
|
||||
- grpc: reference/pipelines/sink/grpc.md
|
||||
- Interceptor:
|
||||
- jsonDecode: reference/pipelines/interceptor/jsonDecode.md
|
||||
- limit: reference/pipelines/interceptor/limit.md
|
||||
- logalert: reference/pipelines/interceptor/logalert.md
|
||||
- metrics: reference/pipelines/interceptor/metrics.md
|
||||
- retry: reference/pipelines/interceptor/retry.md
|
||||
- Queue:
|
||||
- channel: reference/pipelines/queue/channel.md
|
||||
- memeory: reference/pipelines/queue/memory.md
|
||||
- Source:
|
||||
- file: reference/pipelines/source/file.md
|
||||
- kafka: reference/pipelines/source/kafka.md
|
||||
- kubeEvent: reference/pipelines/source/kubeEvent.md
|
||||
- Sink:
|
||||
- elasticsearch: reference/pipelines/sink/elasticsearch.md
|
||||
- kafka: reference/pipelines/sink/kafka.md
|
||||
- dev: reference/pipelines/sink/dev.md
|
||||
- grpc: reference/pipelines/sink/grpc.md
|
||||
- codec: reference/pipelines/sink/codec.md
|
||||
- Interceptor:
|
||||
- normalize: reference/pipelines/interceptor/normalize.md
|
||||
- limit: reference/pipelines/interceptor/limit.md
|
||||
- logalert: reference/pipelines/interceptor/logalert.md
|
||||
- metrics: reference/pipelines/interceptor/metrics.md
|
||||
- retry: reference/pipelines/interceptor/retry.md
|
||||
- Queue:
|
||||
- channel: reference/pipelines/queue/channel.md
|
||||
- memeory: reference/pipelines/queue/memory.md
|
||||
- Kubernetes CRD:
|
||||
- Overview: reference/discovery/kubernetes/overview.md
|
||||
- LogConfig: reference/discovery/kubernetes/logconfig.md
|
||||
|
|
|
|||
Loading…
Reference in New Issue