此系列文章一共分为三部分,分为 filebeat 部分,logstash 部分,es 部分。通过此系列的文章,可以快速了解整个日志收集的大概,本篇主要讲解
logstash
这一块
toc
1. logstash 介绍
版本:logstash-7.12.0
logstash
就是用来处理数据的,通过建一个管道,将数据按照不同的阶段,进行处理,并最终输出的一个过程,以输入到elasticsearch
为例,如下图:
2. logstash 工作原理
Logstash 事件处理管道有三个阶段:输入 → 过滤 → 输出。输入生成事件,过滤器修改事件,然后输出到其他地方。输入和输出支持编解码器,使您能够在数据进入或退出管道时对其进行编码或解码,而不必使用单独的过滤器。
参考官当文档:https://www.elastic.co/guide/en/logstash/current/pipeline.html#pipeline
2.1 输入端
input
: 管道的输入端,可以将数据通过配置 input 输入到 logstash 的管道中,常用的输入插件有:
- kafka
- redis
- file
- syslog
- beats
2.2 过滤器
过滤器是 Logstash 管道中的中间处理设备。您可以将筛选器与条件组合在一起,以便在事件满足特定条件时对其执行操作。一些有用的过滤器包括:
- grok: 解析和构造任意文本。Grok 是目前 Logstash 中解析非结构化日志数据为结构化和可查询数据的最佳方式。Logstash 内置了 120 个模式,你很可能会找到一个满足你需要的模式!
- mutate: 对事件字段执行通用转换。您可以重命名、删除、替换和修改事件中的字段。
- drop: 完全删除事件,例如 debug 事件。
- clone: 创建事件的副本,可以添加或删除字段。
- geoip: 添加关于 IP 地址的地理位置的信息。
- json: 对 json 格式的数据进行处理。
- json_encode: 转换成 json 格式的数据。
2.3 输出端
输出是 Logstash 管道的最后阶段。事件可以通过多个输出,但是一旦所有输出处理完成,事件就完成了它的执行。一些常用的输出包括:
- elasticsearch: 发送事件数据到 elasticsearch
- file: 将事件数据写入磁盘文件。
3. logstash 容器化部署
容器化部署时直接将官方镜像拿过来,通过 k8s 的Deployment
资源类型进行部署即可。
官方镜像地址:
- https://www.elastic.co/guide/en/logstash/master/docker.html
- https://hub.docker.com/_/logstash
3.1 configmap 文件参考
下面的这个configmap
中input
通过配置项topics_pattern
指定一个正则规则来灵活的去匹配一组 topic(当然也可以是用topics
来指定具体的一组 topic), 然后这边没有使用filter
做处理,直接输出到elasticsearch
中。
全局配置文件
代码语言:txt复制apiVersion: v1
data:
logstash.yml: |-
http.host: "0.0.0.0"
pipeline.workers: 2
pipeline.batch.size: 250
pipeline.batch.delay: 50
xpack.management.enabled: false
kind: ConfigMap
metadata:
name: logstash-config-global
namespace: ops-logging
业务相关的配置文件
代码语言:txt复制kind: ConfigMap
apiVersion: v1
metadata:
name: logstash-config-a
namespace: ops-logging
data:
k8s.conf: |-
input {
kafka {
bootstrap_servers => "10.127.91.90:9092,10.127.91.91:9092,10.127.91.92:9092"
group_id => "k8s-hw-group"
client_id => "k8s-hw-client"
consumer_threads => 1
auto_offset_reset => latest
topics_pattern => "k8s-hw.*"
codec => "json"
}
}
filter {
}
output {
if [k8s][nameSpace] == "test" {
elasticsearch {
hosts => ["10.127.91.75:9200", "10.127.91.76:9200", "10.127.91.77:9200", "10.127.91.78:9200", "10.127.91.79:9200", "10.127.91.80:9200", "10.127.91.81:9200"]
index => "k8s-%{[k8s][k8sName]}-%{[k8s][nameSpace]}-%{ YYYYMMddHH}"
sniffing => "true"
timeout => 10
}
} else {
elasticsearch {
hosts => ["10.127.91.75:9200", "10.127.91.76:9200", "10.127.91.77:9200", "10.127.91.78:9200", "10.127.91.79:9200", "10.127.91.80:9200", "10.127.91.81:9200"]
index => "k8s-%{[k8s][k8sName]}-%{[k8s][nameSpace]}-%{ YYYYMMdd}"
sniffing => "true"
timeout => 10
}
}
}
3.1.1 关于配置项需要做下简单说明
3.1.1.1 INPUT
bootstrap_servers
指定 kafka 地址topics
表示一组确定的 topictopics_pattern
表示通过自定义正则来模糊匹配一组 topicauto_offset_reset
这个字段,表示 Kafka 中没有初始偏移量或偏移量超出范围时的策略,其中earliest
: 从头开始消费latest
: 从最新的 offset 开始消费none
: 如果没有找到消费者组的先前偏移量,则向消费者抛出异常anything else
: 直接向消费者抛出异常
consumer_threads
消费者端的线程数,理想情况下,您应该拥有与分区数量相同的线程,以达到完美的平衡——线程数量超过分区意味着有些线程将处于空闲状态,比如说我有 4 个 partition,假如我只启动一个副本,那么这里最好设置成 4,如果我启动了 4 个副本,那么这里设置成 1
3.1.1.2 OUTPUT
output 设置了一个判断,用来对来自 k8s 命名空间的 topic 进行区分,由于我的test
命名空间中的日志量比较大,所以我在建索引时,按小时进行索引,所以这边单独设置了下,而其他命名空间走默认的配置项即可
具体可参考官方文档: https://www.elastic.co/guide/en/logstash/current/plugins-outputs-elasticsearch.html
3.2 deployment 文件参考
代码语言:txt复制apiVersion: apps/v1
kind: Deployment
metadata:
labels:
app: logstash-k8s
name: logstash-k8s
namespace: ops-logging
spec:
progressDeadlineSeconds: 600
replicas: 0
revisionHistoryLimit: 10
selector:
matchLabels:
app: logstash-k8s
strategy:
rollingUpdate:
maxSurge: 25%
maxUnavailable: 25%
type: RollingUpdate
template:
metadata:
labels:
app: logstash-k8s
spec:
containers:
- args:
- /usr/share/logstash/bin/logstash -f /usr/share/logstash/conf/k8s.conf
command:
- /bin/sh
- -c
image: docker.elastic.co/logstash/logstash:7.12.0
imagePullPolicy: IfNotPresent
name: logstash-k8s
resources:
limits:
cpu: "4"
memory: 4G
requests:
cpu: "4"
memory: 4G
terminationMessagePath: /dev/termination-log
terminationMessagePolicy: File
volumeMounts:
- mountPath: /usr/share/logstash/conf
name: config-volume
- mountPath: /usr/share/logstash/config/logstash.yml
name: logstash-config
readOnly: true
subPath: logstash.yml
- args:
- -c
- /opt/bitnami/logstash-exporter/bin/logstash_exporter --logstash.endpoint='http://localhost:9600'
command:
- /bin/sh
image: bitnami/logstash-exporter:latest
imagePullPolicy: IfNotPresent
name: logstash-exporter-k8s
ports:
- containerPort: 9198
name: lg-exporter
protocol: TCP
resources: {}
terminationMessagePath: /dev/termination-log
terminationMessagePolicy: File
dnsPolicy: ClusterFirst
restartPolicy: Always
schedulerName: default-scheduler
securityContext:
runAsUser: 0
terminationGracePeriodSeconds: 30
volumes:
- configMap:
defaultMode: 420
items:
- key: k8s.conf
path: k8s.conf
name: logstash-config-sg-saas-pro-hbali
name: config-volume
- configMap:
defaultMode: 420
name: logstash-config-global
name: logstash-config
logstash-exporter 的 svc 参考
代码语言:txt复制apiVersion: v1
kind: Service
metadata:
name: logstash-exporter-a
namespace: ops-logging
spec:
ports:
- name: http
port: 9198
protocol: TCP
targetPort: 9198
nodePort: 30003
selector:
app: logstash
sessionAffinity: None
type: NodePort
上面的话应该算是logstash
最简单的配置了,假如我们想调试的话,可以把下面这段改下
containers:
- args:
- /usr/share/logstash/bin/logstash -f /usr/share/logstash/conf/k8s.conf
改成
代码语言:txt复制 containers:
- args:
- sleep 1000000
这样我们在调试时,可直接进入到容器中调试。
4. logstash 的进阶使用
4.1 需求介绍
2021-08-01 12:26:04.063 INFO 24 --- traceId=edda5daxxxxxxxxxcfa3387d48 c.g.c.gateway.filter.AutoTestFilter : {"traceId":"edda5da8xxxxxxxxxxxxxxxxxxx387d48","headers":{"x-forwarded-proto":"http,http","x-tenant-id":"123","x-ca-key":"a62d5xxxxxxxxxxxxxxxxxxxxxxxxb1cff8637","x-forwarded-port":"80,80","x-forwarded-for":"10.244.2.0","x-ca-client-ip":"10.244.2.0","x-product-code":"xxxxx","authorization":"bearer 0ed29xxxxxxxxxxxxxxxxxxxxxxxxx71899","x-forwarded-host":"gatxxxxxxxxx.gm","x-forwarded-prefix":"/xxxxxx","trace-id":"edda5da8278xxxxxxxxxxxxxxxxxxx49cfa3387d48","x-ca-api-id":"1418470181321347075","x-ca-env-code":"TEST"},"appName":"超级管理员","responseTime":15,"serverName":"test-server","appkey":"a62d54b6bxxxxxxxxxxxxxxxxxxx37","time":"2021-08-01 12:26:04.062","responseStatus":200,"url":"/test/v4/orgs/123/list-children","token":"bearer 0ed29c72-0d68-4e13-a3f3-c77e2d971899"}
上面是很常见的一条java
程序的日志,我们首先想格式化此日志,然后取出里面的请求 body,也就是里面的一条json
{"traceId":"edda5da8xxxxxxxxxxxxxxxxxxx387d48","headers":{"x-forwarded-proto":"http,http","x-tenant-id":"123","x-ca-key":"a62d5xxxxxxxxxxxxxxxxxxxxxxxxb1cff8637","x-forwarded-port":"80,80","x-forwarded-for":"10.244.2.0","x-ca-client-ip":"10.244.2.0","x-product-code":"xxxxx","authorization":"bearer 0ed29xxxxxxxxxxxxxxxxxxxxxxxxx71899","x-forwarded-host":"gatxxxxxxxxx.gm","x-forwarded-prefix":"/xxxxxx","trace-id":"edda5da8278xxxxxxxxxxxxxxxxxxx49cfa3387d48","x-ca-api-id":"1418470181321347075","x-ca-env-code":"TEST"},"appName":"超级管理员","responseTime":15,"serverName":"test-server","appkey":"a62d54b6bxxxxxxxxxxxxxxxxxxx37","time":"2021-08-01 12:26:04.062","responseStatus":200,"url":"/test/v4/orgs/123/list-children","token":"bearer 0ed29c72-0d68-4e13-a3f3-c77e2d971899"}
取出来之后,我们希望在 elasticsearch 里能根据指定的字段进行快速查询和聚合,因此需要对这段 json 进行重新解析,把里面的 k,v 都放到顶层,另外这段json
里面还有一部分嵌套的数组,我们希望将数组中的 map 解析出来,并放到最外层中,最后将里面的一些字符串转换成整型的数据结构。
为了方便调试,这里重新启动了一个 pod,并指定一个了最简单的配置,将日志输出到控制台上,方便调试
代码语言:txt复制apiVersion: apps/v1
kind: Deployment
metadata:
name: logstash-debug
spec:
progressDeadlineSeconds: 600
replicas: 1
revisionHistoryLimit: 10
selector:
matchLabels:
app: logstash-debug
strategy:
rollingUpdate:
maxSurge: 25%
maxUnavailable: 25%
type: RollingUpdate
template:
metadata:
labels:
app: logstash-debug
spec:
containers:
- args:
- sleep 1000000000000
command:
- /bin/sh
- -c
image: docker.elastic.co/logstash/logstash:7.12.0
imagePullPolicy: IfNotPresent
name: logstash-debug
resources:
limits:
cpu: "4"
memory: 4G
requests:
cpu: "4"
memory: 4G
terminationMessagePath: /dev/termination-log
terminationMessagePolicy: File
dnsPolicy: ClusterFirst
restartPolicy: Always
schedulerName: default-scheduler
securityContext:
runAsUser: 0
terminationGracePeriodSeconds: 30
pod 启动成功之后,我们直接指定配置文件
代码语言:txt复制# debug.conf
input {
file {
path => ["/var/log/test.log"]
start_position => "beginning"
sincedb_path => "/dev/null"
}
}
filter {
}
output {
stdout {
codec => rubydebug
}
}
启动
代码语言:txt复制logstash -f debug.conf
随后将上面的那条日志写道/var/log/test.log
中
最终控制台输出结果
代码语言:txt复制{
"host" => "logstash-debug-649dcb789c-n9866",
"path" => "/var/log/test.log",
"@timestamp" => 2021-08-01T06:46:43.292Z,
"@version" => "1",
"message" => "2021-08-01 12:26:04.063 INFO 24 --- [traceId=edda5daxxxxxxxxxcfa3387d48] [ XNIO-1 task-1] c.g.c.gateway.filter.AutoTestFilter : {"traceId":"edda5da8xxxxxxxxxxxxxxxxxxx387d48","headers":[{"x-forwarded-proto":"http,http","x-tenant-id":"123","x-ca-key":"a62d5xxxxxxxxxxxxxxxxxxxxxxxxb1cff8637","x-forwarded-port":"80,80","x-forwarded-for":"10.244.2.0","x-ca-client-ip":"10.244.2.0","x-product-code":"xxxxx","authorization":"bearer 0ed29xxxxxxxxxxxxxxxxxxxxxxxxx71899","x-forwarded-host":"gatxxxxxxxxx.gm","x-forwarded-prefix":"/xxxxxx","trace-id":"edda5da8278xxxxxxxxxxxxxxxxxxx49cfa3387d48","x-ca-api-id":"1418470181321347075","x-ca-env-code":"TEST"}],"appName":"超级管理员","responseTime":15,"serverName":"test-server","appkey":"a62d54b6bxxxxxxxxxxxxxxxxxxx37","time":"2021-08-01 12:26:04.062","responseStatus":200,"url":"/test/v4/orgs/123/list-children","token":"bearer 0ed29c72-0d68-4e13-a3f3-c77e2d971899"}"
}
4.2 一步步的去解析日志
使用 logstash 对原始日志进行日志格式化,这应该算是最常见的一种需求了,下面将通过filter
中的grok
来进行日志格式话,下面以上面的日志为例,我们来通过自定义日志格式,然后最终获取日志里面的一段 json 日志,也就是这一段{"traceId":"edda5da8xxxxxxxxxxxxxxxxxxx387d48","headers":[{"x-forwarded-proto":"http,http","x-tenant-id":"123","x-ca-key":"a62d5xxxxxxxxxxxxxxxxxxxxxxxxb1cff8637","x-forwarded-port":"80,80","x-forwarded-for":"10.244.2.0","x-ca-client-ip":"10.244.2.0","x-product-code":"xxxxx","authorization":"bearer 0ed29xxxxxxxxxxxxxxxxxxxxxxxxx71899","x-forwarded-host":"gatxxxxxxxxx.gm","x-forwarded-prefix":"/xxxxxx","trace-id":"edda5da8278xxxxxxxxxxxxxxxxxxx49cfa3387d48","x-ca-api-id":"1418470181321347075","x-ca-env-code":"TEST"}],"appName":"超级管理员","responseTime":15,"serverName":"test-server","appkey":"a62d54b6bxxxxxxxxxxxxxxxxxxx37","time":"2021-08-01 12:26:04.062","responseStatus":200,"url":"/test/v4/orgs/123/list-children","token":"bearer 0ed29c72-0d68-4e13-a3f3-c77e2d971899"}
4.2.1 首先进行日志格式化,取出我们想要的日志
grok 官方参考文档: https://www.elastic.co/guide/en/logstash/current/plugins-filters-grok.html
grok 调试工具:https://grokdebug.herokuapp.com/
在上面的工具调试后,会将调试结果一并输出,如下图所示:
下面是放到 logstash 中的配置段
代码语言:txt复制filter {
grok {
match => {"message" => '%{TIMESTAMP_ISO8601:timeFlag} %{LOGLEVEL:logLevel} %{NUMBER:id} --- [(?<traceId>traceId=.*)] [ (?<Nio>.*)] (?<filter>[a-z0-9A-Z.] ) : (?<originBody>{".*"}$)'}
}
}
这里格式化的就是message
中的日志,通过一堆正则,然后来匹配出我们想要的关键日志,匹配结果如下:
{
"message" => "2021-08-01 12:26:04.063 INFO 24 --- [traceId=edda5daxxxxxxxxxcfa3387d48] [ XNIO-1 task-1] c.g.c.gateway.filter.AutoTestFilter : {"traceId":"edda5da8xxxxxxxxxxxxxxxxxxx387d48","headers":[{"x-forwarded-proto":"http,http","x-tenant-id":"123","x-ca-key":"a62d5xxxxxxxxxxxxxxxxxxxxxxxxb1cff8637","x-forwarded-port":"80,80","x-forwarded-for":"10.244.2.0","x-ca-client-ip":"10.244.2.0","x-product-code":"xxxxx","authorization":"bearer 0ed29xxxxxxxxxxxxxxxxxxxxxxxxx71899","x-forwarded-host":"gatxxxxxxxxx.gm","x-forwarded-prefix":"/xxxxxx","trace-id":"edda5da8278xxxxxxxxxxxxxxxxxxx49cfa3387d48","x-ca-api-id":"1418470181321347075","x-ca-env-code":"TEST"}],"appName":"超级管理员","responseTime":15,"serverName":"test-server","appkey":"a62d54b6bxxxxxxxxxxxxxxxxxxx37","time":"2021-08-01 12:26:04.062","responseStatus":200,"url":"/test/v4/orgs/123/list-children","token":"bearer 0ed29c72-0d68-4e13-a3f3-c77e2d971899"}",
"id" => "24",
"Nio" => " XNIO-1 task-1",
"@timestamp" => 2021-08-01T07:25:09.041Z,
"filter" => "c.g.c.gateway.filter.AutoTestFilter",
"traceId" => "traceId=edda5daxxxxxxxxxcfa3387d48",
"timeFlag" => "2021-08-01 12:26:04.063",
"path" => "/var/log/test.log",
"originBody" => "{"traceId":"edda5da8xxxxxxxxxxxxxxxxxxx387d48","headers":[{"x-forwarded-proto":"http,http","x-tenant-id":"123","x-ca-key":"a62d5xxxxxxxxxxxxxxxxxxxxxxxxb1cff8637","x-forwarded-port":"80,80","x-forwarded-for":"10.244.2.0","x-ca-client-ip":"10.244.2.0","x-product-code":"xxxxx","authorization":"bearer 0ed29xxxxxxxxxxxxxxxxxxxxxxxxx71899","x-forwarded-host":"gatxxxxxxxxx.gm","x-forwarded-prefix":"/xxxxxx","trace-id":"edda5da8278xxxxxxxxxxxxxxxxxxx49cfa3387d48","x-ca-api-id":"1418470181321347075","x-ca-env-code":"TEST"}],"appName":"超级管理员","responseTime":15,"serverName":"test-server","appkey":"a62d54b6bxxxxxxxxxxxxxxxxxxx37","time":"2021-08-01 12:26:04.062","responseStatus":200,"url":"/test/v4/orgs/123/list-children","token":"bearer 0ed29c72-0d68-4e13-a3f3-c77e2d971899"}",
"@version" => "1",
"host" => "logstash-debug-649dcb789c-n9866",
"logLevel" => "INFO"
}
4.2.1 删除不必要的字段
经过处理之后,我们可以看到新加了一个字段名叫做originBody
,我们真正想要的就是这段,其他的字段都不需要,因此把没有用的字段删除, 这里用到了mutate
中的remove_field
来删除字段,关于该字段的具体使用可以参考其官方文档:https://www.elastic.co/guide/en/logstash/current/plugins-filters-mutate.html#plugins-filters-mutate-remove_field
filter {
grok {
match => {"message" => '%{TIMESTAMP_ISO8601:timeFlag} %{LOGLEVEL:logLevel} %{NUMBER:id} --- [(?<traceId>traceId=.*)] [ (?<Nio>.*)] (?<filter>[a-z0-9A-Z.] ) : (?<originBody>{".*"}$)'}
}
mutate {
remove_field => ["message", "timeFlag", "logLevel", "id", "traceId", "Nio", "filter"]
}
}
经过此次处理后,会去掉message
字段,结果如下所示:
{
"path" => "/var/log/test.log",
"originBody" => "{"traceId":"edda5da8xxxxxxxxxxxxxxxxxxx387d48","headers":[{"x-forwarded-proto":"http,http","x-tenant-id":"123","x-ca-key":"a62d5xxxxxxxxxxxxxxxxxxxxxxxxb1cff8637","x-forwarded-port":"80,80","x-forwarded-for":"10.244.2.0","x-ca-client-ip":"10.244.2.0","x-product-code":"xxxxx","authorization":"bearer 0ed29xxxxxxxxxxxxxxxxxxxxxxxxx71899","x-forwarded-host":"gatxxxxxxxxx.gm","x-forwarded-prefix":"/xxxxxx","trace-id":"edda5da8278xxxxxxxxxxxxxxxxxxx49cfa3387d48","x-ca-api-id":"1418470181321347075","x-ca-env-code":"TEST"}],"appName":"超级管理员","responseTime":15,"serverName":"test-server","appkey":"a62d54b6bxxxxxxxxxxxxxxxxxxx37","time":"2021-08-01 12:26:04.062","responseStatus":200,"url":"/test/v4/orgs/123/list-children","token":"bearer 0ed29c72-0d68-4e13-a3f3-c77e2d971899"}",
"@version" => "1",
"@timestamp" => 2021-08-01T07:30:17.548Z,
"host" => "logstash-debug-649dcb789c-n9866",
}
4.2.2 将所需日志进行 json 解析
然后我们想将originBody
这个json
中的字段放到顶层中,这里用到了filter
中的json
选项,用来解析json
数据类型的日志,这里面有两个关键字段需要知道:
- source: 指定要处理的 json 字段,这里对应的就是
originBody
- target: 解析后的 json 数据存放位置,如果不指定将输出到顶层, 由于我这里就是要将解析好的数据放到顶层,因此不指定
target
filter {
grok {
match => {"message" => '%{TIMESTAMP_ISO8601:timeFlag} %{LOGLEVEL:logLevel} %{NUMBER:id} --- [(?<traceId>traceId=.*)] [ (?<Nio>.*)] (?<filter>[a-z0-9A-Z.] ) : (?<originBody>{".*"}$)'}
}
json {
source => "originBody"
}
mutate {
remove_field => ["message", "timeFlag", "logLevel", "id", "traceId", "Nio", "filter", "originBody"]
}
}
处理结果如下
代码语言:txt复制{
"@version" => "1",
"serverName" => "test-server",
"time" => "2021-08-01 12:26:04.062",
"appkey" => "a62d54b6bxxxxxxxxxxxxxxxxxxx37",
"responseStatus" => 200,
"url" => "/test/v4/orgs/123/list-children",
"headers" => [
[0] {
"x-tenant-id" => "123",
"x-ca-env-code" => "TEST",
"x-ca-key" => "a62d5xxxxxxxxxxxxxxxxxxxxxxxxb1cff8637",
"authorization" => "bearer 0ed29xxxxxxxxxxxxxxxxxxxxxxxxx71899",
"x-product-code" => "xxxxx",
"x-ca-client-ip" => "10.244.2.0",
"x-forwarded-host" => "gatxxxxxxxxx.gm",
"x-forwarded-prefix" => "/xxxxxx",
"x-forwarded-for" => "10.244.2.0",
"x-ca-api-id" => "1418470181321347075",
"x-forwarded-proto" => "http,http",
"trace-id" => "edda5da8278xxxxxxxxxxxxxxxxxxx49cfa3387d48",
"x-forwarded-port" => "80,80"
}
],
"host" => "logstash-debug-649dcb789c-n9866",
"responseTime" => 15,
"token" => "bearer 0ed29c72-0d68-4e13-a3f3-c77e2d971899",
"appName" => "超级管理员",
"path" => "/var/log/test.log",
"@timestamp" => 2021-08-01T07:50:26.403Z
}
4.2.3 优化数组的结构
基本上到这里我们想要的数据差不多都呈现出来了,但是可以看到headers
这个是个数组,而里面的元素是一个map
,我们需要将数组中的 map 给解析到外层,这里使用的是split
这个选项,使用也很简单,具体可参考官方文档: https://www.elastic.co/guide/en/logstash/current/plugins-filters-split.html
filter {
grok {
match => {"message" => '%{TIMESTAMP_ISO8601:timeFlag} %{LOGLEVEL:logLevel} %{NUMBER:id} --- [(?<traceId>traceId=.*)] [ (?<Nio>.*)] (?<filter>[a-z0-9A-Z.] ) : (?<originBody>{".*"}$)'}
}
json {
source => "originBody"
}
split {
field => "headers"
}
mutate {
remove_field => ["message", "timeFlag", "logLevel", "id", "traceId", "Nio", "filter", "originBody"]
}
}
处理完之后,结果如下:
代码语言:txt复制{
"appName" => "超级管理员",
"serverName" => "test-server",
"@version" => "1",
"url" => "/test/v4/orgs/123/list-children",
"time" => "2021-08-01 12:26:04.062",
"token" => "bearer 0ed29c72-0d68-4e13-a3f3-c77e2d971899",
"@timestamp" => 2021-08-01T07:55:01.353Z,
"appkey" => "a62d54b6bxxxxxxxxxxxxxxxxxxx37",
"path" => "/var/log/test.log",
"responseTime" => 15,
"responseStatus" => 200,
"headers" => {
"x-forwarded-proto" => "http,http",
"x-product-code" => "xxxxx",
"x-ca-client-ip" => "10.244.2.0",
"authorization" => "bearer 0ed29xxxxxxxxxxxxxxxxxxxxxxxxx71899",
"x-ca-key" => "a62d5xxxxxxxxxxxxxxxxxxxxxxxxb1cff8637",
"x-forwarded-for" => "10.244.2.0",
"trace-id" => "edda5da8278xxxxxxxxxxxxxxxxxxx49cfa3387d48",
"x-forwarded-host" => "gatxxxxxxxxx.gm",
"x-forwarded-prefix" => "/xxxxxx",
"x-forwarded-port" => "80,80",
"x-tenant-id" => "123",
"x-ca-env-code" => "TEST",
"x-ca-api-id" => "1418470181321347075"
},
"host" => "logstash-debug-649dcb789c-n9866"
}
4.2.4 转换数据类型
嗯,已经满足了,接下来是最后一步,将某些字段的字符串转成整型
代码语言:txt复制filter {
grok {
match => {"message" => '%{TIMESTAMP_ISO8601:timeFlag} %{LOGLEVEL:logLevel} %{NUMBER:id} --- [(?<traceId>traceId=.*)] [ (?<Nio>.*)] (?<filter>[a-z0-9A-Z.] ) : (?<originBody>{".*"}$)'}
}
json {
source => "originBody"
}
split {
field => "headers"
}
mutate {
remove_field => ["message", "timeFlag", "logLevel", "id", "traceId", "Nio", "filter", "originBody"]
convert => {
"responseStatus" => "integer"
"responseTime" => "integer"
}
}
}
最终结果
代码语言:txt复制{
"appName" => "超级管理员",
"token" => "bearer 0ed29c72-0d68-4e13-a3f3-c77e2d971899",
"responseTime" => 15,
"path" => "/var/log/test.log",
"headers" => {
"x-forwarded-host" => "gatxxxxxxxxx.gm",
"trace-id" => "edda5da8278xxxxxxxxxxxxxxxxxxx49cfa3387d48",
"x-ca-key" => "a62d5xxxxxxxxxxxxxxxxxxxxxxxxb1cff8637",
"x-forwarded-prefix" => "/xxxxxx",
"x-ca-api-id" => "1418470181321347075",
"x-ca-client-ip" => "10.244.2.0",
"x-forwarded-for" => "10.244.2.0",
"x-forwarded-port" => "80,80",
"authorization" => "bearer 0ed29xxxxxxxxxxxxxxxxxxxxxxxxx71899",
"x-ca-env-code" => "TEST",
"x-forwarded-proto" => "http,http",
"x-tenant-id" => "123",
"x-product-code" => "xxxxx"
},
"appkey" => "a62d54b6bxxxxxxxxxxxxxxxxxxx37",
"time" => "2021-08-01 12:26:04.062",
"@version" => "1",
"responseStatus" => 200,
"serverName" => "test-server",
"url" => "/test/v4/orgs/123/list-children",
"@timestamp" => 2021-08-01T07:57:54.071Z,
"host" => "logstash-debug-649dcb789c-n9866"
}
到这里就大功告成了
5. 总结
这篇文章只说了logstash
的其中一种日志处理方式,用的是它自带的一些插件,基本上可以满足我们日常的一些需求,但是如果加入一些逻辑处理的话,我们也可以通过自定义ruby
代码段来进行处理,下一篇文章将介绍结合ruby
的日志处理。