Finology 大数据金融

通过大数据以量化金融

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想让自己的博客被百度搜索引擎尽快收录，并在搜索时排在前面一些，那就需要及时提交博客的URL。

主要有三种提交方法，大家最好三种都用，这也是官方推荐的，不会有任何冲突。

主动推送

主动推送是实时的，能让百度在第一时间知道你的原创内容。

首先要安装hexo-baidu-url-submit插件。

在博客根目录下执行如下命令：

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sudo npm install hexo-baidu-url-submit --save
+ hexo-baidu-url-submit@0.0.6
added 85 packages from 61 contributors, removed 71 packages and updated 11 packages in 14.783s


   ╭────────────────────────────────────────────────────────────────╮
   │                                                                │
   │      New minor version of npm available! 6.10.0 → 6.13.7       │
   │   Changelog: https://github.com/npm/cli/releases/tag/v6.13.7   │
   │               Run npm install -g npm to update!                │
   │                                                                │
   ╰────────────────────────────────────────────────────────────────╯

(base)

然后在根目录中的_config.yml文件内容最后，添加如下内容：

count为提交Url的数量。

host为博客的地址。

token这也可以在百度网站上找到。

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# Baibu url submit
baidu_url_submit:
  count: 500
  host: https://finolo.gy
  token: ## 填下图位置里面token参数的值
  path: baidu_urls.txt

最后在Deploy标签下加入buidu_url_submitter

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deploy:
  - type: baidu_url_submitter

在hexo generate时，会产生.deploy_git/baidu_urls.txt文件。

hexo deploy时，会从上述文件中读取urls，提交到百度。

成功以后，一般会返回类似这样的信息。remain为今天剩余可推送urls数量，success为成功推送的urls数量。

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{"remain":99602,"success":149}
INFO  Deploy done: baidu_url_submitter

自动推送

在themes/<your_theme>/_config.yaml中，把baidu_push标签的值设置为true。

这时，系统会调用到themes/<your_theme>/layout/_third-party/seo/baidu-push.swig文件。

Sitemap

安装插件

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npm install hexo-generator-sitemap --save     
npm install hexo-generator-baidu-sitemap --save

然后把http://<domain>/baidusitemap.xml和http://<domain>/sitemap.xml提交到百度sitemap页面即可。

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官网对kubernetes_sd_config的详细说明文档

https://prometheus.io/docs/prometheus/latest/configuration/configuration/#kubernetes_sd_config

kubernetes_sd_config用于配置自动发现的。关于服务自动发现，还可以参考这篇实战：Prometheus kubernetes-cadvisor服务自动发现

Kubernetes SD configurations allow retrieving scrape targets from Kubernetes’ REST API and always staying synchronized with the cluster state.

role的类型有以下几种：node, service, pod, endpoints和ingress。

当role的值为endpoints时，官网说明：

The endpoints role discovers targets from listed endpoints of a service. For each endpoint address one target is discovered per port. If the endpoint is backed by a pod, all additional container ports of the pod, not bound to an endpoint port, are discovered as targets as well.

然后prometheus-additional.yaml的容是：

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- job_name: 'kubernetes-service-endpoints'
  kubernetes_sd_configs:
  - role: endpoints
  relabel_configs:
  - source_labels: [__meta_kubernetes_service_annotation_prometheus_io_scrape]
    action: keep
    regex: true
  - source_labels: [__meta_kubernetes_service_annotation_prometheus_io_scheme]
    action: replace
    target_label: __scheme__
    regex: (https?)
  - source_labels: [__meta_kubernetes_service_annotation_prometheus_io_path]
    action: replace
    target_label: __metrics_path__
    regex: (.+)
  - source_labels: [__address__, __meta_kubernetes_service_annotation_prometheus_io_port]
    action: replace
    target_label: __address__
    regex: ([^:]+)(?::\d+)?;(\d+)
    replacement: $1:$2
  - action: labelmap
    regex: __meta_kubernetes_service_label_(.+)
  - source_labels: [__meta_kubernetes_namespace]
    action: replace
    target_label: kubernetes_namespace
  - source_labels: [__meta_kubernetes_service_name]
    action: replace
    target_label: kubernetes_name

我理解的逻辑是：

  1. 首先查找ep,svc两个同时存在的
  2. 然后查找svc的annotations标签__meta_kubernetes_service_annotation_prometheus_io_scrape的值为true的。
  3. 最后看到ep里面有两个Addresses，所以显示两个Targets。

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kubectl get serviceMonitor -n monitoring kubelet -o yaml
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apiVersion: monitoring.coreos.com/v1
kind: ServiceMonitor
metadata:
  annotations:
    kubectl.kubernetes.io/last-applied-configuration: |
      {"apiVersion":"monitoring.coreos.com/v1","kind":"ServiceMonitor","metadata":{"annotations":{},"labels":{"k8s-app":"kubelet"},"name":"kubelet","namespace":"monitoring"},"spec":{"endpoints":[{"bearerTokenFile":"/var/run/secrets/kubernetes.io/serviceaccount/token","honorLabels":true,"interval":"30s","port":"https-metrics","scheme":"https","tlsConfig":{"insecureSkipVerify":true}},{"bearerTokenFile":"/var/run/secrets/kubernetes.io/serviceaccount/token","honorLabels":true,"interval":"30s","metricRelabelings":[{"action":"drop","regex":"container_(network_tcp_usage_total|network_udp_usage_total|tasks_state|cpu_load_average_10s)","sourceLabels":["__name__"]}],"path":"/metrics/cadvisor","port":"https-metrics","scheme":"https","tlsConfig":{"insecureSkipVerify":true}}],"jobLabel":"k8s-app","namespaceSelector":{"matchNames":["kube-system"]},"selector":{"matchLabels":{"k8s-app":"kubelet"}}}}
  creationTimestamp: "2019-12-29T06:40:27Z"
  generation: 1
  labels:
    k8s-app: kubelet
  name: kubelet
  namespace: monitoring
  resourceVersion: "2602"
  selfLink: /apis/monitoring.coreos.com/v1/namespaces/monitoring/servicemonitors/kubelet
  uid: 327bae9c-d09c-4d00-b293-354870b19f91
spec:
  endpoints:
  - bearerTokenFile: /var/run/secrets/kubernetes.io/serviceaccount/token
    honorLabels: true
    interval: 30s
    port: https-metrics
    scheme: https
    tlsConfig:
      insecureSkipVerify: true
  - bearerTokenFile: /var/run/secrets/kubernetes.io/serviceaccount/token
    honorLabels: true
    interval: 30s
    metricRelabelings:
    - action: drop
      regex: container_(network_tcp_usage_total|network_udp_usage_total|tasks_state|cpu_load_average_10s)
      sourceLabels:
      - __name__
    path: /metrics/cadvisor
    port: https-metrics
    scheme: https
    tlsConfig:
      insecureSkipVerify: true
  jobLabel: k8s-app
  namespaceSelector:
    matchNames:
    - kube-system
  selector:
    matchLabels:
      k8s-app: kubelet

根据上面的namespaceSelector和selector

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kubectl get ep -n kube-system -l k8s-app=kubelet -o yaml
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apiVersion: v1
items:
- apiVersion: v1
  kind: Endpoints
  metadata:
    creationTimestamp: "2019-12-29T06:40:06Z"
    labels:
      k8s-app: kubelet
    name: kubelet
    namespace: kube-system
    resourceVersion: "2371"
    selfLink: /api/v1/namespaces/kube-system/endpoints/kubelet
    uid: 326583cc-3379-4883-8426-5a856c29c77e
  subsets:
  - addresses:
    - ip: 172.16.64.232
      targetRef:
        kind: Node
        name: k8s-node1
        uid: 09ffae8e-e3f1-456b-a398-7891487712da
    - ip: 172.16.64.233
      targetRef:
        kind: Node
        name: k8s-master
        uid: 774ddb3e-2c3c-4af8-8e1c-15b0c2c3b8c1
    - ip: 172.16.64.235
      targetRef:
        kind: Node
        name: k8s-node2
        uid: 7c1cc5f0-2b71-462a-907e-191b0d3ee819
    ports:
    - name: http-metrics
      port: 10255
      protocol: TCP
    - name: cadvisor
      port: 4194
      protocol: TCP
    - name: https-metrics
      port: 10250
      protocol: TCP
kind: List
metadata:
  resourceVersion: ""
  selfLink: ""