使用 Fluentd 记录日志
此任务将展示如何配置 Istio 创建自定义日志条目并且发送给 Fluentd 守护进程。Fluentd 是一个开源的日志收集器,
支持多种数据输出并且有一个可插拔架构。
Elasticsearch是一个流行的后端日志记录程序,
Kibana 用于查看。在任务结束后,
一个新的日志流将被加载发送日志到示例 Fluentd/Elasticsearch/Kibana 栈。
在任务中,将使用 BookInfo 示例应用程序作为示例应用程序。
在开始之前
- 安装 Istio 到您的集群并且部署一个应用程序。这个任务假定 Mixer 是
以默认配置设置的(--configDefaultNamespace=istio-system
)。
如果您使用不同的值,则更新此任务中的配置和命令以匹配对应的值。
安装 Fluentd
在您的群集中,您可能已经有一个 Fluentd DaemonSet 运行,
就像 add-on 中这里
和这里的描述,
或者特定于您的集群提供者的东西。这可能配置为将日志发送到 Elasticsearch 系统或其它日志记录提供程序。
您可以使用这些 Fluentd 守护进程或您已经设置的任何其他Fluentd守护进程,只要Fluentd守护进程正在侦听转发的日志, 并且
Istio 的 Mixer 可以连接Fluentd守护进程。为了让 Mixer 连接到正在运行的 Fluentd 守护进程, 您可能需要为 Fluentd 添加
service.
监听转发日志的 Fluentd 配置是:
<source>
type forward
</source>
将 Mixer 连接到所有可能 Fluentd 配置的完整细节超出了此任务的范围。
Fluentd, Elasticsearch, Kibana 栈示例
为了这个任务的准备,您可以部署提供的示例栈。
该栈包括 Fluentd,Elasticsearch 和 Kibana 在一个非生产集合 Services 和 Deployments
在一个新的叫做logging
的
Namespace 中.
将下面的内容保存为 logging-stack.yaml
.
# Logging Namespace. All below are a part of this namespace.
apiVersion: v1
kind: Namespace
metadata:
name: logging
---
# Elasticsearch Service
apiVersion: v1
kind: Service
metadata:
name: elasticsearch
namespace: logging
labels:
app: elasticsearch
spec:
ports:
- port: 9200
protocol: TCP
targetPort: db
selector:
app: elasticsearch
---
# Elasticsearch Deployment
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
name: elasticsearch
namespace: logging
labels:
app: elasticsearch
annotations:
sidecar.istio.io/inject: "false"
spec:
template:
metadata:
labels:
app: elasticsearch
spec:
containers:
- image: docker.elastic.co/elasticsearch/elasticsearch-oss:6.1.1
name: elasticsearch
resources:
# need more cpu upon initialization, therefore burstable class
limits:
cpu: 1000m
requests:
cpu: 100m
env:
- name: discovery.type
value: single-node
ports:
- containerPort: 9200
name: db
protocol: TCP
- containerPort: 9300
name: transport
protocol: TCP
volumeMounts:
- name: elasticsearch
mountPath: /data
volumes:
- name: elasticsearch
emptyDir: {}
---
# Fluentd Service
apiVersion: v1
kind: Service
metadata:
name: fluentd-es
namespace: logging
labels:
app: fluentd-es
spec:
ports:
- name: fluentd-tcp
port: 24224
protocol: TCP
targetPort: 24224
- name: fluentd-udp
port: 24224
protocol: UDP
targetPort: 24224
selector:
app: fluentd-es
---
# Fluentd Deployment
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
name: fluentd-es
namespace: logging
labels:
app: fluentd-es
annotations:
sidecar.istio.io/inject: "false"
spec:
template:
metadata:
labels:
app: fluentd-es
spec:
containers:
- name: fluentd-es
image: gcr.io/google-containers/fluentd-elasticsearch:v2.0.1
env:
- name: FLUENTD_ARGS
value: --no-supervisor -q
resources:
limits:
memory: 500Mi
requests:
cpu: 100m
memory: 200Mi
volumeMounts:
- name: config-volume
mountPath: /etc/fluent/config.d
terminationGracePeriodSeconds: 30
volumes:
- name: config-volume
configMap:
name: fluentd-es-config
---
# Fluentd ConfigMap, contains config files.
kind: ConfigMap
apiVersion: v1
data:
forward.input.conf: |-
# Takes the messages sent over TCP
<source>
type forward
</source>
output.conf: |-
<match **>
type elasticsearch
log_level info
include_tag_key true
host elasticsearch
port 9200
logstash_format true
# Set the chunk limits.
buffer_chunk_limit 2M
buffer_queue_limit 8
flush_interval 5s
# Never wait longer than 5 minutes between retries.
max_retry_wait 30
# Disable the limit on the number of retries (retry forever).
disable_retry_limit
# Use multiple threads for processing.
num_threads 2
</match>
metadata:
name: fluentd-es-config
namespace: logging
---
# Kibana Service
apiVersion: v1
kind: Service
metadata:
name: kibana
namespace: logging
labels:
app: kibana
spec:
ports:
- port: 5601
protocol: TCP
targetPort: ui
selector:
app: kibana
---
# Kibana Deployment
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
name: kibana
namespace: logging
labels:
app: kibana
annotations:
sidecar.istio.io/inject: "false"
spec:
template:
metadata:
labels:
app: kibana
spec:
containers:
- name: kibana
image: docker.elastic.co/kibana/kibana-oss:6.1.1
resources:
# need more cpu upon initialization, therefore burstable class
limits:
cpu: 1000m
requests:
cpu: 100m
env:
- name: ELASTICSEARCH_URL
value: http://elasticsearch:9200
ports:
- containerPort: 5601
name: ui
protocol: TCP
---
创建资源:
kubectl apply -f logging-stack.yaml
你应该看到以下内容:
namespace "logging" created
service "elasticsearch" created
deployment "elasticsearch" created
service "fluentd-es" created
deployment "fluentd-es" created
configmap "fluentd-es-config" created
service "kibana" created
deployment "kibana" created
配置 Istio
现在有一个正在运行的 Fluentd 守护进程,请使用新的日志类型配置 Istio,
并将这些日志发送到监听守护进程。
创建一个新的 YAML 文件来保存日志流的配置,Istio 将自动生成并收集。
将下面的内容保存为 fluentd-istio.yaml
:
# Configuration for logentry instances
apiVersion: "config.istio.io/v1alpha2"
kind: logentry
metadata:
name: newlog
namespace: istio-system
spec:
severity: '"info"'
timestamp: request.time
variables:
source: source.labels["app"] | source.service | "unknown"
user: source.user | "unknown"
destination: destination.labels["app"] | destination.service | "unknown"
responseCode: response.code | 0
responseSize: response.size | 0
latency: response.duration | "0ms"
monitored_resource_type: '"UNSPECIFIED"'
---
# Configuration for a fluentd handler
apiVersion: "config.istio.io/v1alpha2"
kind: fluentd
metadata:
name: handler
namespace: istio-system
spec:
address: "fluentd-es.logging:24224"
---
# Rule to send logentry instances to the fluentd handler
apiVersion: "config.istio.io/v1alpha2"
kind: rule
metadata:
name: newlogtofluentd
namespace: istio-system
spec:
match: "true" # match for all requests
actions:
- handler: handler.fluentd
instances:
- newlog.logentry
---
创建资源:
istioctl create -f fluentd-istio.yaml
预期的输出类似于:
Created config logentry/istio-system/newlog at revision 22374
Created config fluentd/istio-system/handler at revision 22375
Created config rule/istio-system/newlogtofluentd at revision 22376
请注意在处理程序配置中 address: "fluentd-es.logging:24224"
行指向我们设置的Fluentd守护进程示例栈。
查看新的日志
将流量发送到示例应用程序。
对于 BookInfo
示例, 在浏览器中访问http://$GATEWAY_URL/productpage
或发送以下命令:curl http://$GATEWAY_URL/productpage
在 Kubernetes 环境中, 通过以下命令为 Kibana 建立端口转发:
kubectl -n logging port-forward $(kubectl -n logging get pod -l app=kibana -o jsonpath='{.items[0].metadata.name}') 5601:5601
退出运行命令。完成访问 Kibana UI 时输入 Ctrl-C 退出。
导航到 Kibana UI 并点击 右上角的 “Set up index patterns”。
使用
*
作为索引模式, 并单击 “Next step.”。选择
@timestamp
作为时间筛选字段名称,然后单击 “Create index pattern”。现在在左侧的菜单上点击 “Discover”,并开始检索生成的日志。
清理
删除新的遥测配置:
istioctl delete -f fluentd-istio.yaml
删除 Fluentd, Elasticsearch, Kibana 示例栈:
kubectl delete -f logging-stack.yaml
如果您不打算探索任何后续任务, 参考
BookInfo cleanup 关闭应用程序的说明。