虚拟机： VMware ESXi
操作系统：CentOS Linux release 7.5
# 固定静态IP
[root@JMS ~]# cat /etc/sysconfig/network-scripts/ifcfg-ens33
TYPE="Ethernet"
PROXY_METHOD="none"
BROWSER_ONLY="no"
BOOTPROTO="static"
DEFROUTE="yes"
IPV4_FAILURE_FATAL="no"
IPV6INIT="yes"
IPV6_AUTOCONF="yes"
IPV6_DEFROUTE="yes"
IPV6_FAILURE_FATAL="no"
IPV6_ADDR_GEN_MODE="stable-privacy"
NAME="ens33"
UUID="2a047fc4-4910-4773-8f50-e9211cd158f0"
DEVICE="ens33"
ONBOOT="yes"
IPADDR=192.168.xx.xx
NETMASK=255.255.255.0
GATEWAY=192.168.2.1
DNS1=223.5.5.5
DNS2=8.8.8.8
# 重启network服务
service network restart
hostnamectl set-hostname k8s-master
hostnamectl set-hostname k8s-slave1
hostnamectl set-hostname k8s-slave2
cat >> /etc/hosts << EOF
192.168.2.161 k8s-master
192.168.2.162 k8s-slave1
192.168.2.163 k8s-slave2
EOF
配置master1到node1无密码登陆
在master上操作
ssh-keygen -t rsa
#一直回车就可以
cd /root && ssh-copy-id -i .ssh/id_rsa.pub root@k8s-slave1
cd /root && ssh-copy-id -i .ssh/id_rsa.pub root@k8s-slave2
#上面需要输入yes之后，输入密码，输入node1物理机密码即可
#安装基础软件包，各个节点操作
yum -y install wget net-tools nfs-utils lrzsz gcc gcc-c++make cmake libxml2-devel openssl-devel curl curl-devel unzip sudo ntplibaio-devel wget vim ncurses-devel autoconf automake zlib-devel python-devel epel-release openssh-serversocat ipvsadm conntrack ntpdate
systemctl stop firewalld && systemctl disable firewalld
yum install iptables-services -y
service iptables stop && systemctl disable iptables
# 时间同步
ntpdate cn.pool.ntp.org
1）crontab -e
* */1 * * * /usr/sbin/ntpdate cn.pool.ntp.org
2）重启crond服务：
service crond restart
# 设置永久关闭selinux，各个节点操作
sed -i 's/SELINUX=enforcing/SELINUX=disabled/' /etc/sysconfig/selinux
sed -i 's/SELINUX=enforcing/SELINUX=disabled/g' /etc/selinux/config
# 永久禁用，打开/etc/fstab注释掉swap那一行。
swapoff -a
sed -i 's/.*swap.*/#&/' /etc/fstab
# 修改内核参数，各个节点操作
cat <<EOF > /etc/sysctl.d/k8s.conf
net.bridge.bridge-nf-call-ip6tables = 1
net.bridge.bridge-nf-call-iptables = 1
EOF
sysctl --system
reboot -f
设置网桥包经IPTables，core文件生成路径，配置永久生效
echo 1 > /proc/sys/net/bridge/bridge-nf-call-iptables
echo 1 >/proc/sys/net/bridge/bridge-nf-call-ip6tables
echo """
vm.swappiness = 0
net.bridge.bridge-nf-call-iptables = 1
net.ipv4.ip_forward = 1
net.bridge.bridge-nf-call-ip6tables = 1
""" > /etc/sysctl.conf
sysctl -p
开启ipvs，不开启ipvs将会使用iptables，但是效率低，所以官网推荐需要开通ipvs内核
cat > /etc/sysconfig/modules/ipvs.modules <<EOF
#!/bin/bash
ipvs_modules="ip_vs ip_vs_lc ip_vs_wlc ip_vs_rrip_vs_wrr ip_vs_lblc ip_vs_lblcr ip_vs_dh ip_vs_sh ip_vs_fo ip_vs_nq ip_vs_sedip_vs_ftp nf_conntrack"
for kernel_module in \${ipvs_modules}; do
/sbin/modinfo -Ffilename \${kernel_module} > /dev/null 2>&1
if [ $? -eq 0 ];then
/sbin/modprobe\${kernel_module}
fi
done
EOF
chmod 755 /etc/sysconfig/modules/ipvs.modules &&bash /etc/sysconfig/modules/ipvs.modules && lsmod | grep ip_vs
===========================================安装docker===============================================
sudo yum update
官方脚本安装：curl -sSL https://get.docker.com/ | sh 或者：sudo yum -y install docker-ce-19.03.13 或者
docker run hello-world
docker version
# 修改成如下内容
vim /usr/lib/systemd/system/docker.service
ExecStart=/usr/bin/dockerd --exec-opt native.cgroupdriver=systemd
# 新增docker源加速
cat /etc/docker/daemon.json
{
"storage-driver": "overlay2",
"insecure-registries": ["registry.access.redhat.com","quay.io","192.168.2.110:5000"],
"registry-mirrors": ["https://registry.docker-cn.com","http://hub-mirror.c.163.com","https://0qswmwvl.mirror.aliyuncs.com"]
}
systemctl daemon-reload && systemctl restart docker && systemctl status docker
=======================================安装kubernetes=====================================================
cat > /etc/yum.repos.d/kubernetes.repo << EOF
[kubernetes]
name=Kubernetes
baseurl=https://mirrors.aliyun.com/kubernetes/yum/repos/kubernetes-el7-x86_64
enabled=1
gpgcheck=1
repo_gpgcheck=1
gpgkey=https://mirrors.aliyun.com/kubernetes/yum/doc/yum-key.gpg
https://mirrors.aliyun.com/kubernetes/yum/doc/rpm-package-key.gpg
EOF
yum install -y kubelet kubeadm kubectl
# 跳过密钥安装如下
yum install kubectl-1.18.2-0.x86_64 --nogpgcheck
yum install kubelet-1.18.2-0.x86_64 --nogpgcheck
yum install kubeadm-1.18.2-0.x86_64 --nogpgcheck
systemctl enable kubelet
kubelet --version
docker load -i 1-18-kube-apiserver.tar.gz &&
docker load -i 1-18-kube-scheduler.tar.gz &&
docker load -i 1-18-kube-controller-manager.tar.gz &&
docker load -i 1-18-pause.tar.gz &&
docker load -i 1-18-cordns.tar.gz &&
docker load -i 1-18-etcd.tar.gz &&
docker load -i 1-18-kube-proxy.tar.gz &&
docker load -i cni.tar.gz &&
docker load -i calico-node.tar.gz &&
docker load -i traefik_1_7_9.tar.gz &&
docker load -i dashboard_2_0_0.tar.gz &&
docker load -i metrics-scrapter-1-0-1.tar.gz &&
docker load -i metrics-server-amd64_0_3_1.tar.gz &&
docker load -i addon.tar.gz
echo "export KUBECONFIG=/etc/kubernetes/admin.conf" >> ~/.bash_profile
source ~/.bash_profile
初始化
kubeadm init \
--apiserver-advertise-address=192.168.2.161 \
--image-repository registry.aliyuncs.com/google_containers \
--kubernetes-version v1.18.2 \
--service-cidr=10.1.0.0/16 \
--pod-network-cidr=10.244.0.0/16
mkdir -p $HOME/.kube
sudo cp -i /etc/kubernetes/admin.conf $HOME/.kube/config
sudo chown $(id -u):$(id -g) $HOME/.kube/config ###注释：这个目录可以拷贝到其它节点然后它们也可以使用kubectl命令
kubectl get nodes
kubectl apply -f calico.yaml #只需要在master创建一次即可
kubectl get nodes
复制到node1 node2 节点执行：
kubeadm join 192.168.2.161:6443 --token 574y6z.9235pj93va9o8ed3 \
--discovery-token-ca-cert-hash sha256:93205aa49e2b587c429f9d11e2b7d546000072abcd943d98e1eff32df505a988
生成traefik证书，在master1上操作
mkdir ~/ikube/tls/ -p
echo """
[req]
distinguished_name = req_distinguished_name
prompt = yes
[ req_distinguished_name ]
countryName = Country Name (2 letter code)
countryName_value = CN
stateOrProvinceName = State orProvince Name (full name)
stateOrProvinceName_value = Beijing
localityName = Locality Name (eg, city)
localityName_value =Haidian
organizationName =Organization Name (eg, company)
organizationName_value = Channelsoft
organizationalUnitName = OrganizationalUnit Name (eg, section)
organizationalUnitName_value = R & D Department
commonName = Common Name (eg, your name or your server\'s hostname)
commonName_value =*.multi.io
emailAddress = Email Address
emailAddress_value =lentil1016@gmail.com
""" > ~/ikube/tls/openssl.cnf
openssl req -newkey rsa:4096 -nodes -config ~/ikube/tls/openssl.cnf -days3650 -x509 -out ~/ikube/tls/tls.crt -keyout ~/ikube/tls/tls.key
kubectl create -n kube-system secret tls ssl --cert ~/ikube/tls/tls.crt--key ~/ikube/tls/tls.key
kubectl apply -f traefik.yaml #只需要在master创建一次即可
kubectl get pods -n kube-system
kubectl apply -f kubernetes-dashboard.yaml #只需要在master创建一次即可
kubectl get pods -n kubernetes-dashboard
kubectl get svc -n kubernetes-dashboard
修改service type类型变成NodePort：
kubectl edit svc kubernetes-dashboard -n kubernetes-dashboard
把type: ClusterIP变成 type: NodePort，保存退出即可。
# 查看端口 我的是30471
kubectl get svc -n kubernetes-dashboard
kubectl get secret -n kubernetes-dashboard
# 查看token 值 复制登录
kubectl describe secret kubernetes-dashboard-token-5mwhr -n kubernetes-dashboard
# 创建admin管理员权限
kubectl create clusterrolebinding dashboard-cluster-admin --clusterrole=cluster-admin --serviceaccount=kubernetes-dashboard:kubernetes-dashboard
kubectl apply -f metrics.yaml
# 登录浏览器
https://192.168.2.161:30471/#/overview?namespace=_all
=======================================Prometheus+Grafana+Alertmanager==========================================
k8s集群中部署prometheus
1.创建namespace、sa账号，在k8s集群的master节点操作
创建一个monitor-sa的名称空间
kubectl create ns monitor-sa
创建一个sa账号
[root@k8s-master ~]# kubectl create serviceaccount monitor -n monitor-sa
serviceaccount/monitor created
把sa账号monitor通过clusterrolebing绑定到clusterrole上
[root@k8s-master ~]# kubectl create clusterrolebinding monitor-clusterrolebinding -n monitor-sa --clusterrole=cluster-admin --serviceaccount=monitor-sa:monitor
clusterrolebinding.rbac.authorization.k8s.io/monitor-clusterrolebinding created
2.创建数据目录
在k8s集群的任何一个node节点操作，这里我选择在k8s-node1上操作如下命令：
[root@k8s-node1 ~]# mkdir /data
[root@k8s-node1 ~]# chmod 777 /data/
3.安装prometheus，以下步骤均在在k8s集群的k8s-master1节点操作
1）创建一个configmap存储卷，用来存放prometheus配置信息
cat >prometheus-cfg.yaml <<EOF
---
kind: ConfigMap
apiVersion: v1
metadata:
labels:
app: prometheus
name: prometheus-config
namespace: monitor-sa
data:
prometheus.yml: |
global:
scrape_interval: 15s
scrape_timeout: 10s
evaluation_interval: 1m
scrape_configs:
- job_name: 'kubernetes-node'
kubernetes_sd_configs:
- role: node
relabel_configs:
- source_labels: [__address__]
regex: '(.*):10250'
replacement: '${1}:9100'
target_label: __address__
action: replace
- action: labelmap
regex: __meta_kubernetes_node_label_(.+)
- job_name: 'kubernetes-node-cadvisor'
kubernetes_sd_configs:
- role: node
scheme: https
tls_config:
ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
bearer_token_file: /var/run/s ecrets/kubernetes.io/serviceaccount/token
relabel_configs:
- action: labelmap
regex: __meta_kubernetes_node_label_(.+)
- target_label: __address__
replacement: kubernetes.default.svc:443
- source_labels: [__meta_kubernetes_node_name]
regex: (.+)
target_label: __metrics_path__
replacement: /api/v1/nodes/${1}/proxy/metrics/cadvisor
- job_name: 'kubernetes-apiserver'
kubernetes_sd_configs:
- role: endpoints
scheme: https
tls_config:
ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token
relabel_configs:
- source_labels: [__meta_kubernetes_namespace, __meta_kubernetes_service_name, __meta_kubernetes_endpoint_port_name]
action: keep
regex: default;kubernetes;https
- 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
EOF
注意：通过上面命令生成的promtheus-cfg.yaml文件会有一些问题，$1和$2这种变量在文件里没有，需要在k8s的k8s-master1节点打开promtheus-cfg.yaml文件，手动把$1和$2这种变量写进文件里，promtheus-cfg.yaml文件需要手动修改部分如下：
22行的replacement: ':9100'变成replacement: '${1}:9100'
42行的replacement: /api/v1/nodes//proxy/metrics/cadvisor变成
replacement: /api/v1/nodes/${1}/proxy/metrics/cadvisor
73行的replacement: 变成replacement: $1:$2
通过kubectl apply更新configmap
kubectl apply -f prometheus-cfg.yaml
2）通过deployment部署prometheus
cat >prometheus-deploy.yaml <<EOF
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: prometheus-server
namespace: monitor-sa
labels:
app: prometheus
spec:
replicas: 1
selector:
matchLabels:
app: prometheus
component: server
#matchExpressions:
#- {key: app, operator: In, values: [prometheus]}
#- {key: component, operator: In, values: [server]}
template:
metadata:
labels:
app: prometheus
component: server
annotations:
prometheus.io/scrape: 'false'
spec:
nodeName: k8s-node1
serviceAccountName: monitor
containers:
- name: prometheus
image: prom/prometheus:v2.2.1
imagePullPolicy: IfNotPresent
command:
- prometheus
- --config.file=/etc/prometheus/prometheus.yml
- --storage.tsdb.path=/prometheus
- --storage.tsdb.retention=720h
ports:
- containerPort: 9090
protocol: TCP
volumeMounts:
- mountPath: /etc/prometheus/prometheus.yml
name: prometheus-config
subPath: prometheus.yml
- mountPath: /prometheus/
name: prometheus-storage-volume
volumes:
- name: prometheus-config
configMap:
name: prometheus-config
items:
- key: prometheus.yml
path: prometheus.yml
mode: 0644
- name: prometheus-storage-volume
hostPath:
path: /data
type: Directory
EOF
注意：在上面的prometheus-deploy.yaml文件有个nodeName字段，这个就是用来指定创建的这个prometheus的pod调度到哪个节点上，根据我们实际的节点名字来修改，我的节点名字为：k8s-node1，所以我们这里让nodeName=k8s-node1，也即是让pod调度到k8s-node1节点上，因为k8s-node1节点我们创建了数据目录/data，所以大家记住：你在k8s集群的哪个节点创建/data，就让pod调度到哪个节点。
通过kubectl apply更新prometheus
kubectl apply -f prometheus-deploy.yaml
查看prometheus是否部署成功
kubectl get pods -n monitor-sa
显示如下，可看到pod状态是running，说明prometheus部署成功
kubectl get pods -n monitor-sa
3.给prometheus pod创建一个service
cat > prometheus-svc.yaml << EOF
---
apiVersion: v1
kind: Service
metadata:
name: prometheus
namespace: monitor-sa
labels:
app: prometheus
spec:
type: NodePort
ports:
- port: 9090
targetPort: 9090
protocol: TCP
selector:
app: prometheus
component: server
EOF
通过kubectl apply更新service
kubectl apply -f prometheus-svc.yaml
查看service在物理机映射的端口
kubectl get svc -n monitor-sa
显示如下：
通过上面可以看到service在宿主机上映射的端口是32639，这样我们访问k8s集群的k8s-master1节点的ip:32639，就可以访问到prometheus的WebUI界面了
访问Prometheus WebUI界面
浏览器输入如下k8s-master的地址：http://192.168.2.161:31285/ 可看到如下页面：
prometheus热更新
为了每次修改配置文件可以热加载prometheus，也就是不停止prometheus
就可以使配置生效，如修改prometheus-cfg.yaml，想要使配置生效可用如下热加载命令：
[root@k8s-master ~]# curl -X POST http://10.244.1.70:9090/-/reload
Lifecycle APIs are not enabled[
10.244.1.70是prometheus的pod的IP地址
如何查看prometheus的pod的IP，可用如下命令：
kubectl get pods -n monitor-sa -o wide | grep prometheus
显示如下，10.244.1.5就是prometheus的ip
热加载速度比较慢，可以暴力重启prometheus，如修改上面的prometheus-cfg.yaml文件之后，可执行如下强制删除：
kubectl delete -f prometheus-cfg.yaml
kubectl delete -f prometheus-deploy.yaml
然后再通过apply更新：
kubectl apply -f prometheus-cfg.yaml
kubectl apply -f prometheus-deploy.yaml
注意：线上最好热加载，暴力删除可能造成监控数据的丢失
Grafana安装和配置
上传包镜像到k8s的各个master节点和k8s的各个node节点
这里采用将包传到k8s-master节点，然后通过脚本传到各节点并导入镜像
vim /root/scp_heapster-grafana_load_image.sh
scp heapster-grafana-amd64_v5_0_4.tar.gz k8s-node1:/root
scp heapster-grafana-amd64_v5_0_4.tar.gz k8s-node2:/root
docker load -i heapster-grafana-amd64_v5_0_4.tar.gz
ssh k8s-node1 docker load -i heapster-grafana-amd64_v5_0_4.tar.gz
ssh k8s-node2 docker load -i heapster-grafana-amd64_v5_0_4.tar.gz
赋值脚本权限并执行
chmod +x /root/scp_heapster-grafana_load_image.sh && sh /root/scp_heapster-grafana_load_image.sh
在k8s的k8s-master节点创建grafana.yaml
cat >grafana.yaml << EOF
apiVersion: apps/v1
kind: Deployment
metadata:
name: monitoring-grafana
namespace: kube-system
spec:
replicas: 1
selector:
matchLabels:
task: monitoring
k8s-app: grafana
template:
metadata:
labels:
task: monitoring
k8s-app: grafana
spec:
containers:
- name: grafana
image: k8s.gcr.io/heapster-grafana-amd64:v5.0.4
ports:
- containerPort: 3000
protocol: TCP
volumeMounts:
- mountPath: /etc/ssl/certs
name: ca-certificates
readOnly: true
- mountPath: /var
name: grafana-storage
env:
- name: INFLUXDB_HOST
value: monitoring-influxdb
- name: GF_SERVER_HTTP_PORT
value: "3000"
# The following env variables are required to make Grafana accessible via
# the kubernetes api-server proxy. On production clusters, we recommend
# removing these env variables, setup auth for grafana, and expose the grafana
# service using a LoadBalancer or a public IP.
- name: GF_AUTH_BASIC_ENABLED
value: "false"
- name: GF_AUTH_ANONYMOUS_ENABLED
value: "true"
- name: GF_AUTH_ANONYMOUS_ORG_ROLE
value: Admin
- name: GF_SERVER_ROOT_URL
# If you're only using the API Server proxy, set this value instead:
# value: /api/v1/namespaces/kube-system/services/monitoring-grafana/proxy
value: /
volumes:
- name: ca-certificates
hostPath:
path: /etc/ssl/certs
- name: grafana-storage
emptyDir: {}
---
apiVersion: v1
kind: Service
metadata:
labels:
# For use as a Cluster add-on (https://github.com/kubernetes/kubernetes/tree/master/cluster/addons)
# If you are NOT using this as an addon, you should comment out this line.
kubernetes.io/cluster-service: 'true'
kubernetes.io/name: monitoring-grafana
name: monitoring-grafana
namespace: kube-system
spec:
# In a production setup, we recommend accessing Grafana through an external Loadbalancer
# or through a public IP.
# type: LoadBalancer
# You could also use NodePort to expose the service at a randomly-generated port
# type: NodePort
ports:
- port: 80
targetPort: 3000
selector:
k8s-app: grafana
type: NodePort
EOF
通过kubectl apply更新grafana
[root@k8s-master ~]# kubectl apply -f grafana.yaml
deployment.apps/monitoring-grafana created
service/monitoring-grafana created
查看grafana是否部署成功
[root@k8s-master ~]# kubectl get pods -n kube-system
显示如下，说明部署成功
monitoring-grafana-7d7f6cf5c6-nmkd7 1/1 Running 0 110s
查看grafana的service
[root@k8s-master ~]# kubectl get svc -n kube-system
显示如下：
monitoring-grafana NodePort 10.100.202.134 <none> 80:30234/TCP 6m39s
上面可以看到grafana暴露的宿主机端口是30234
我们访问k8s集群的master节点ip:30234即可访问到grafana的web界面
Grafan界面接入prometheus数据源
1）登录grafana，在浏览器访问
Name: Prometheus
Type: Prometheus
HTTP处的URL写如下：
http://prometheus.monitor-sa.svc:9090
导入监控模板
模板文件导入后 下拉框 选择Name: Prometheus
安装配置kube-state-metrics组件
kube-state-metrics是什么？
kube-state-metrics通过监听API Server生成有关资源对象的状态指标，比如Deployment、Node、Pod，需要注意的是kube-state-metrics只是简单的提供一个metrics数据，并不会存储这些指标数据，所以我们可以使用Prometheus来抓取这些数据然后存储，主要关注的是业务相关的一些元数据，比如Deployment、Pod、副本状态等；调度了多少个replicas？现在可用的有几个？多少个Pod是running/stopped/terminated状态？Pod重启了多少次？我有多少job在运行中。
安装kube-state-metrics组件
1）创建sa，并对sa授权
在k8s的k8s-master节点生成一个kube-state-metrics-rbac.yaml文件
cat > kube-state-metrics-rbac.yaml <<EOF
---
apiVersion: v1
kind: ServiceAccount
metadata:
name: kube-state-metrics
namespace: kube-system
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
name: kube-state-metrics
rules:
- apiGroups: [""]
resources: ["nodes", "pods", "services", "resourcequotas", "replicationcontrollers", "limitranges", "persistentvolumeclaims", "persistentvolumes", "namespaces", "endpoints"]
verbs: ["list", "watch"]
- apiGroups: ["extensions"]
resources: ["daemonsets", "deployments", "replicasets"]
verbs: ["list", "watch"]
- apiGroups: ["apps"]
resources: ["statefulsets"]
verbs: ["list", "watch"]
- apiGroups: ["batch"]
resources: ["cronjobs", "jobs"]
verbs: ["list", "watch"]
- apiGroups: ["autoscaling"]
resources: ["horizontalpodautoscalers"]
verbs: ["list", "watch"]
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
name: kube-state-metrics
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: ClusterRole
name: kube-state-metrics
subjects:
- kind: ServiceAccount
name: kube-state-metrics
namespace: kube-system
EOF
通过kubectl apply更新yaml文件
kubectl apply -f kube-state-metrics-rbac.yaml
2)安装kube-state-metrics组件
在k8s的k8s-master节点生成一个kube-state-metrics-deploy.yaml文件
cat > kube-state-metrics-deploy.yaml <<EOF
apiVersion: apps/v1
kind: Deployment
metadata:
name: kube-state-metrics
namespace: kube-system
spec:
replicas: 1
selector:
matchLabels:
app: kube-state-metrics
template:
metadata:
labels:
app: kube-state-metrics
spec:
serviceAccountName: kube-state-metrics
containers:
- name: kube-state-metrics
# image: gcr.io/google_containers/kube-state-metrics-amd64:v1.3.1
image: quay.io/coreos/kube-state-metrics:v1.9.0
ports:
- containerPort: 8080
EOF
通过kubectl apply更新yaml文件
kubectl apply -f kube-state-metrics-deploy.yaml
查看kube-state-metrics是否部署成功
kubectl get pods -n kube-system
显示如下，看到pod处于running状态，说明部署成功
kube-state-metrics-79c9686b96-lgbfz 1/1 Running 0 3m11s
3）创建service在k8s的k8s-master节点生成一个kube-state-metrics-svc.yaml文件
cat >kube-state-metrics-svc.yaml <<EOF
apiVersion: v1
kind: Service
metadata:
annotations:
prometheus.io/scrape: 'true'
name: kube-state-metrics
namespace: kube-system
labels:
app: kube-state-metrics
spec:
ports:
- name: kube-state-metrics
port: 8080
protocol: TCP
selector:
app: kube-state-metrics
EOF
通过kubectl apply更新yaml
kubectl apply -f kube-state-metrics-svc.yaml
查看service是否创建成功
kubectl get svc -n kube-system | grep kube-state-metrics
显示如下，说明创建成功
kube-state-metrics ClusterIP 10.109.205.230 <none> 8080/TCP 4s
安装和配置Alertmanager-发送报警到qq邮箱
在k8s的k8s-master节点创建alertmanager-cm.yaml文件
cat >alertmanager-cm.yaml <<EOF
kind: ConfigMap
apiVersion: v1
metadata:
name: alertmanager
namespace: monitor-sa
data:
alertmanager.yml: |-
global:
resolve_timeout: 1m
smtp_smarthost: 'smtp.163.com:25'
smtp_from: '123456789@163.com'
smtp_auth_username: '123456789'
smtp_auth_password: 'XXXXXX'
smtp_require_tls: false
route:
group_by: [alertname]
group_wait: 10s
group_interval: 10s
repeat_interval: 10m
receiver: default-receiver
receivers:
- name: 'default-receiver'
email_configs:
- to: '123456789@qq.com'
send_resolved: true
EOF
通过kubectl apply更新文件
kubectl apply -f alertmanager-cm.yaml
alertmanager配置文件解释说明：
#用于发送邮件的邮箱的SMTP服务器地址+端口
smtp_smarthost: 'smtp.163.com:25'
smtp_smarthost: 'smtp.qq.com:465'
#这是指定从哪个邮箱发送报警
smtp_from: '1228848273@qq.com'
#这是发送邮箱的认证用户，不是邮箱名
smtp_auth_username: '1228848273'
#这是发送邮箱的授权码而不是登录密码
smtp_auth_password: 'rpxxxxxxxjcib'
#to后面指定发送到哪个邮箱，我发送到我的qq邮箱，大家需要写自己的邮箱地址，不应该跟smtp_from的邮箱名字重复
email_configs:
- to: '2413117757@qq.com'
在k8s的k8s-master节点重新生成一个prometheus-cfg.yaml文件
cat prometheus-cfg.yaml
kind: ConfigMap
apiVersion: v1
metadata:
labels:
app: prometheus
name: prometheus-config
namespace: monitor-sa
data:
prometheus.yml: |-
rule_files:
- /etc/prometheus/rules.yml
alerting:
alertmanagers:
- static_configs:
- targets: ["localhost:9093"]
global:
scrape_interval: 15s
scrape_timeout: 10s
evaluation_interval: 1m
scrape_configs:
- job_name: 'kubernetes-node'
kubernetes_sd_configs:
- role: node
relabel_configs:
- source_labels: [__address__]
regex: '(.*):10250'
replacement: '${1}:9100'
target_label: __address__
action: replace
- action: labelmap
regex: __meta_kubernetes_node_label_(.+)
- job_name: 'kubernetes-node-cadvisor'
kubernetes_sd_configs:
- role: node
scheme: https
tls_config:
ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token
relabel_configs:
- action: labelmap
regex: __meta_kubernetes_node_label_(.+)
- target_label: __address__
replacement: kubernetes.default.svc:443
- source_labels: [__meta_kubernetes_node_name]
regex: (.+)
target_label: __metrics_path__
replacement: /api/v1/nodes/${1}/proxy/metrics/cadvisor
- job_name: 'kubernetes-apiserver'
kubernetes_sd_configs:
- role: endpoints
scheme: https
tls_config:
ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token
relabel_configs:
- source_labels: [__meta_kubernetes_namespace, __meta_kubernetes_service_name, __meta_kubernetes_endpoint_port_name]
action: keep
regex: default;kubernetes;https
- 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
- job_name: kubernetes-pods
kubernetes_sd_configs:
- role: pod
relabel_configs:
- action: keep
regex: true
source_labels:
- __meta_kubernetes_pod_annotation_prometheus_io_scrape
- action: replace
regex: (.+)
source_labels:
- __meta_kubernetes_pod_annotation_prometheus_io_path
target_label: __metrics_path__
- action: replace
regex: ([^:]+)(?::\d+)?;(\d+)
replacement: $1:$2
source_labels:
- __address__
- __meta_kubernetes_pod_annotation_prometheus_io_port
target_label: __address__
- action: labelmap
regex: __meta_kubernetes_pod_label_(.+)
- action: replace
source_labels:
- __meta_kubernetes_namespace
target_label: kubernetes_namespace
- action: replace
source_labels:
- __meta_kubernetes_pod_name
target_label: kubernetes_pod_name
- job_name: 'kubernetes-schedule'
scrape_interval: 5s
static_configs:
- targets: ['192.168.2.161:10251']
- job_name: 'kubernetes-controller-manager'
scrape_interval: 5s
static_configs:
- targets: ['192.168.2.161:10252']
- job_name: 'kubernetes-kube-proxy'
scrape_interval: 5s
static_configs:
- targets: ['192.168.2.161:10249','192.168.2.114:10249','192.168.2.115:10249']
- job_name: 'kubernetes-etcd'
scheme: https
tls_config:
ca_file: /var/run/secrets/kubernetes.io/k8s-certs/etcd/ca.crt
cert_file: /var/run/secrets/kubernetes.io/k8s-certs/etcd/server.crt
key_file: /var/run/secrets/kubernetes.io/k8s-certs/etcd/server.key
scrape_interval: 5s
static_configs:
- targets: ['192.168.2.161:2379']
rules.yml: |
groups:
- name: example
rules:
- alert: kube-proxy的cpu使用率大于80%
expr: rate(process_cpu_seconds_total{job=~"kubernetes-kube-proxy"}[1m]) * 100 > 80
for: 2s
labels:
severity: warnning
annotations:
description: "{{$labels.instance}}的{{$labels.job}}组件的cpu使用率超过80%"
- alert: kube-proxy的cpu使用率大于90%
expr: rate(process_cpu_seconds_total{job=~"kubernetes-kube-proxy"}[1m]) * 100 > 90
for: 2s
labels:
severity: critical
annotations:
description: "{{$labels.instance}}的{{$labels.job}}组件的cpu使用率超过90%"
- alert: scheduler的cpu使用率大于80%
expr: rate(process_cpu_seconds_total{job=~"kubernetes-schedule"}[1m]) * 100 > 80
for: 2s
labels:
severity: warnning
annotations:
description: "{{$labels.instance}}的{{$labels.job}}组件的cpu使用率超过80%"
- alert: scheduler的cpu使用率大于90%
expr: rate(process_cpu_seconds_total{job=~"kubernetes-schedule"}[1m]) * 100 > 90
for: 2s
labels:
severity: critical
annotations:
description: "{{$labels.instance}}的{{$labels.job}}组件的cpu使用率超过90%"
- alert: controller-manager的cpu使用率大于80%
expr: rate(process_cpu_seconds_total{job=~"kubernetes-controller-manager"}[1m]) * 100 > 80
for: 2s
labels:
severity: warnning
annotations:
description: "{{$labels.instance}}的{{$labels.job}}组件的cpu使用率超过80%"
- alert: controller-manager的cpu使用率大于90%
expr: rate(process_cpu_seconds_total{job=~"kubernetes-controller-manager"}[1m]) * 100 > 0
for: 2s
labels:
severity: critical
annotations:
description: "{{$labels.instance}}的{{$labels.job}}组件的cpu使用率超过90%"
- alert: apiserver的cpu使用率大于80%
expr: rate(process_cpu_seconds_total{job=~"kubernetes-apiserver"}[1m]) * 100 > 80
for: 2s
labels:
severity: warnning
annotations:
description: "{{$labels.instance}}的{{$labels.job}}组件的cpu使用率超过80%"
- alert: apiserver的cpu使用率大于90%
expr: rate(process_cpu_seconds_total{job=~"kubernetes-apiserver"}[1m]) * 100 > 90
for: 2s
labels:
severity: critical
annotations:
description: "{{$labels.instance}}的{{$labels.job}}组件的cpu使用率超过90%"
- alert: etcd的cpu使用率大于80%
expr: rate(process_cpu_seconds_total{job=~"kubernetes-etcd"}[1m]) * 100 > 80
for: 2s
labels:
severity: warnning
annotations:
description: "{{$labels.instance}}的{{$labels.job}}组件的cpu使用率超过80%"
- alert: etcd的cpu使用率大于90%
expr: rate(process_cpu_seconds_total{job=~"kubernetes-etcd"}[1m]) * 100 > 90
for: 2s
labels:
severity: critical
annotations:
description: "{{$labels.instance}}的{{$labels.job}}组件的cpu使用率超过90%"
- alert: kube-state-metrics的cpu使用率大于80%
expr: rate(process_cpu_seconds_total{k8s_app=~"kube-state-metrics"}[1m]) * 100 > 80
for: 2s
labels:
severity: warnning
annotations:
description: "{{$labels.instance}}的{{$labels.k8s_app}}组件的cpu使用率超过80%"
value: "{{ $value }}%"
threshold: "80%"
- alert: kube-state-metrics的cpu使用率大于90%
expr: rate(process_cpu_seconds_total{k8s_app=~"kube-state-metrics"}[1m]) * 100 > 0
for: 2s
labels:
severity: critical
annotations:
description: "{{$labels.instance}}的{{$labels.k8s_app}}组件的cpu使用率超过90%"
value: "{{ $value }}%"
threshold: "90%"
- alert: coredns的cpu使用率大于80%
expr: rate(process_cpu_seconds_total{k8s_app=~"kube-dns"}[1m]) * 100 > 80
for: 2s
labels:
severity: warnning
annotations:
description: "{{$labels.instance}}的{{$labels.k8s_app}}组件的cpu使用率超过80%"
value: "{{ $value }}%"
threshold: "80%"
- alert: coredns的cpu使用率大于90%
expr: rate(process_cpu_seconds_total{k8s_app=~"kube-dns"}[1m]) * 100 > 90
for: 2s
labels:
severity: critical
annotations:
description: "{{$labels.instance}}的{{$labels.k8s_app}}组件的cpu使用率超过90%"
value: "{{ $value }}%"
threshold: "90%"
- alert: kube-proxy打开句柄数>600
expr: process_open_fds{job=~"kubernetes-kube-proxy"} > 600
for: 2s
labels:
severity: warnning
annotations:
description: "{{$labels.instance}}的{{$labels.job}}打开句柄数>600"
value: "{{ $value }}"
- alert: kube-proxy打开句柄数>1000
expr: process_open_fds{job=~"kubernetes-kube-proxy"} > 1000
for: 2s
labels:
severity: critical
annotations:
description: "{{$labels.instance}}的{{$labels.job}}打开句柄数>1000"
value: "{{ $value }}"
- alert: kubernetes-schedule打开句柄数>600
expr: process_open_fds{job=~"kubernetes-schedule"} > 600
for: 2s
labels:
severity: warnning
annotations:
description: "{{$labels.instance}}的{{$labels.job}}打开句柄数>600"
value: "{{ $value }}"
- alert: kubernetes-schedule打开句柄数>1000
expr: process_open_fds{job=~"kubernetes-schedule"} > 1000
for: 2s
labels:
severity: critical
annotations:
description: "{{$labels.instance}}的{{$labels.job}}打开句柄数>1000"
value: "{{ $value }}"
- alert: kubernetes-controller-manager打开句柄数>600
expr: process_open_fds{job=~"kubernetes-controller-manager"} > 600
for: 2s
labels:
severity: warnning
annotations:
description: "{{$labels.instance}}的{{$labels.job}}打开句柄数>600"
value: "{{ $value }}"
- alert: kubernetes-controller-manager打开句柄数>1000
expr: process_open_fds{job=~"kubernetes-controller-manager"} > 1000
for: 2s
labels:
severity: critical
annotations:
description: "{{$labels.instance}}的{{$labels.job}}打开句柄数>1000"
value: "{{ $value }}"
- alert: kubernetes-apiserver打开句柄数>600
expr: process_open_fds{job=~"kubernetes-apiserver"} > 600
for: 2s
labels:
severity: warnning
annotations:
description: "{{$labels.instance}}的{{$labels.job}}打开句柄数>600"
value: "{{ $value }}"
- alert: kubernetes-apiserver打开句柄数>1000
expr: process_open_fds{job=~"kubernetes-apiserver"} > 1000
for: 2s
labels:
severity: critical
annotations:
description: "{{$labels.instance}}的{{$labels.job}}打开句柄数>1000"
value: "{{ $value }}"
- alert: kubernetes-etcd打开句柄数>600
expr: process_open_fds{job=~"kubernetes-etcd"} > 600
for: 2s
labels:
severity: warnning
annotations:
description: "{{$labels.instance}}的{{$labels.job}}打开句柄数>600"
value: "{{ $value }}"
- alert: kubernetes-etcd打开句柄数>1000
expr: process_open_fds{job=~"kubernetes-etcd"} > 1000
for: 2s
labels:
severity: critical
annotations:
description: "{{$labels.instance}}的{{$labels.job}}打开句柄数>1000"
value: "{{ $value }}"
- alert: coredns
expr: process_open_fds{k8s_app=~"kube-dns"} > 600
for: 2s
labels:
severity: warnning
annotations:
description: "插件{{$labels.k8s_app}}({{$labels.instance}}): 打开句柄数超过600"
value: "{{ $value }}"
- alert: coredns
expr: process_open_fds{k8s_app=~"kube-dns"} > 1000
for: 2s
labels:
severity: critical
annotations:
description: "插件{{$labels.k8s_app}}({{$labels.instance}}): 打开句柄数超过1000"
value: "{{ $value }}"
- alert: kube-proxy
expr: process_virtual_memory_bytes{job=~"kubernetes-kube-proxy"} > 2000000000
for: 2s
labels:
severity: warnning
annotations:
description: "组件{{$labels.job}}({{$labels.instance}}): 使用虚拟内存超过2G"
value: "{{ $value }}"
- alert: scheduler
expr: process_virtual_memory_bytes{job=~"kubernetes-schedule"} > 2000000000
for: 2s
labels:
severity: warnning
annotations:
description: "组件{{$labels.job}}({{$labels.instance}}): 使用虚拟内存超过2G"
value: "{{ $value }}"
- alert: kubernetes-controller-manager
expr: process_virtual_memory_bytes{job=~"kubernetes-controller-manager"} > 2000000000
for: 2s
labels:
severity: warnning
annotations:
description: "组件{{$labels.job}}({{$labels.instance}}): 使用虚拟内存超过2G"
value: "{{ $value }}"
- alert: kubernetes-apiserver
expr: process_virtual_memory_bytes{job=~"kubernetes-apiserver"} > 2000000000
for: 2s
labels:
severity: warnning
annotations:
description: "组件{{$labels.job}}({{$labels.instance}}): 使用虚拟内存超过2G"
value: "{{ $value }}"
- alert: kubernetes-etcd
expr: process_virtual_memory_bytes{job=~"kubernetes-etcd"} > 2000000000
for: 2s
labels:
severity: warnning
annotations:
description: "组件{{$labels.job}}({{$labels.instance}}): 使用虚拟内存超过2G"
value: "{{ $value }}"
- alert: kube-dns
expr: process_virtual_memory_bytes{k8s_app=~"kube-dns"} > 2000000000
for: 2s
labels:
severity: warnning
annotations:
description: "插件{{$labels.k8s_app}}({{$labels.instance}}): 使用虚拟内存超过2G"
value: "{{ $value }}"
- alert: HttpRequestsAvg
expr: sum(rate(rest_client_requests_total{job=~"kubernetes-kube-proxy|kubernetes-kubelet|kubernetes-schedule|kubernetes-control-manager|kubernetes-apiservers"}[1m])) > 1000
for: 2s
labels:
team: admin
annotations:
description: "组件{{$labels.job}}({{$labels.instance}}): TPS超过1000"
value: "{{ $value }}"
threshold: "1000"
- alert: Pod_restarts
expr: kube_pod_container_status_restarts_total{namespace=~"kube-system|default|monitor-sa"} > 0
for: 2s
labels:
severity: warnning
annotations:
description: "在{{$labels.namespace}}名称空间下发现{{$labels.pod}}这个pod下的容器{{$labels.container}}被重启,这个监控指标是由{{$labels.instance}}采集的"
value: "{{ $value }}"
threshold: "0"
- alert: Pod_waiting
expr: kube_pod_container_status_waiting_reason{namespace=~"kube-system|default"} == 1
for: 2s
labels:
team: admin
annotations:
description: "空间{{$labels.namespace}}({{$labels.instance}}): 发现{{$labels.pod}}下的{{$labels.container}}启动异常等待中"
value: "{{ $value }}"
threshold: "1"
- alert: Pod_terminated
expr: kube_pod_container_status_terminated_reason{namespace=~"kube-system|default|monitor-sa"} == 1
for: 2s
labels:
team: admin
annotations:
description: "空间{{$labels.namespace}}({{$labels.instance}}): 发现{{$labels.pod}}下的{{$labels.container}}被删除"
value: "{{ $value }}"
threshold: "1"
- alert: Etcd_leader
expr: etcd_server_has_leader{job="kubernetes-etcd"} == 0
for: 2s
labels:
team: admin
annotations:
description: "组件{{$labels.job}}({{$labels.instance}}): 当前没有leader"
value: "{{ $value }}"
threshold: "0"
- alert: Etcd_leader_changes
expr: rate(etcd_server_leader_changes_seen_total{job="kubernetes-etcd"}[1m]) > 0
for: 2s
labels:
team: admin
annotations:
description: "组件{{$labels.job}}({{$labels.instance}}): 当前leader已发生改变"
value: "{{ $value }}"
threshold: "0"
- alert: Etcd_failed
expr: rate(etcd_server_proposals_failed_total{job="kubernetes-etcd"}[1m]) > 0
for: 2s
labels:
team: admin
annotations:
description: "组件{{$labels.job}}({{$labels.instance}}): 服务失败"
value: "{{ $value }}"
threshold: "0"
- alert: Etcd_db_total_size
expr: etcd_debugging_mvcc_db_total_size_in_bytes{job="kubernetes-etcd"} > 10000000000
for: 2s
labels:
team: admin
annotations:
description: "组件{{$labels.job}}({{$labels.instance}})：db空间超过10G"
value: "{{ $value }}"
threshold: "10G"
- alert: Endpoint_ready
expr: kube_endpoint_address_not_ready{namespace=~"kube-system|default"} == 1
for: 2s
labels:
team: admin
annotations:
description: "空间{{$labels.namespace}}({{$labels.instance}}): 发现{{$labels.endpoint}}不可用"
value: "{{ $value }}"
threshold: "1"
- name:物理节点状态-监控告警
rules:
- alert:物理节点cpu使用率
expr: 100-avg(irate(node_cpu_seconds_total{mode="idle"}[5m])) by(instance)*100 > 90
for: 2s
labels:
severity: ccritical
annotations:
summary: "{{ $labels.instance }}cpu使用率过高"
description: "{{ $labels.instance }}的cpu使用率超过90%,当前使用率[{{ $value }}],需要排查处理"
- alert:物理节点内存使用率
expr: (node_memory_MemTotal_bytes - (node_memory_MemFree_bytes + node_memory_Buffers_bytes + node_memory_Cached_bytes)) / node_memory_MemTotal_bytes * 100 > 90
for: 2s
labels:
severity: critical
annotations:
summary: "{{ $labels.instance }}内存使用率过高"
description: "{{ $labels.instance }}的内存使用率超过90%,当前使用率[{{ $value }}],需要排查处理"
- alert: InstanceDown
expr: up == 0
for: 2s
labels:
severity: critical
annotations:
summary: "{{ $labels.instance }}:服务器宕机"
description: "{{ $labels.instance }}:服务器延时超过2分钟"
- alert:物理节点磁盘的IO性能
expr: 100-(avg(irate(node_disk_io_time_seconds_total[1m])) by(instance)* 100) < 60
for: 2s
labels:
severity: critical
annotations:
summary: "{{$labels.mountpoint}}流入磁盘IO使用率过高！"
description: "{{$labels.mountpoint }}流入磁盘IO大于60%(目前使用:{{$value}})"
- alert:入网流量带宽
expr: ((sum(rate (node_network_receive_bytes_total{device!~'tap.*|veth.*|br.*|docker.*|virbr*|lo*'}[5m])) by (instance)) / 100) > 102400
for: 2s
labels:
severity: critical
annotations:
summary: "{{$labels.mountpoint}}流入网络带宽过高！"
description: "{{$labels.mountpoint }}流入网络带宽持续5分钟高于100M. RX带宽使用率{{$value}}"
- alert:出网流量带宽
expr: ((sum(rate (node_network_transmit_bytes_total{device!~'tap.*|veth.*|br.*|docker.*|virbr*|lo*'}[5m])) by (instance)) / 100) > 102400
for: 2s
labels:
severity: critical
annotations:
summary: "{{$labels.mountpoint}}流出网络带宽过高！"
description: "{{$labels.mountpoint }}流出网络带宽持续5分钟高于100M. RX带宽使用率{{$value}}"
- alert: TCP会话
expr: node_netstat_Tcp_CurrEstab > 1000
for: 2s
labels:
severity: critical
annotations:
summary: "{{$labels.mountpoint}} TCP_ESTABLISHED过高！"
description: "{{$labels.mountpoint }} TCP_ESTABLISHED大于1000%(目前使用:{{$value}}%)"
- alert:磁盘容量
expr: 100-(node_filesystem_free_bytes{fstype=~"ext4|xfs"}/node_filesystem_size_bytes {fstype=~"ext4|xfs"}*100) > 80
for: 2s
labels:
severity: critical
annotations:
summary: "{{$labels.mountpoint}}磁盘分区使用率过高！"
description: "{{$labels.mountpoint }}磁盘分区使用大于80%(目前使用:{{$value}}%)"
注意：
通过上面命令生成的promtheus-cfg.yaml文件会有一些问题，$1和$2这种变量在文件里没有，需要在k8s的k8s-master节点打开promtheus-cfg.yaml文件，手动把$1和$2这种变量写进文件里，promtheus-cfg.yaml文件需要手动修改部分如下：
27行的replacement: ':9100'变成replacement: '${1}:9100'
47行的replacement: /api/v1/nodes//proxy/metrics/cadvisor变成
replacement: /api/v1/nodes/${1}/proxy/metrics/cadvisor
78行的replacement:变成replacement: $1:$2
102行的replacement:变成replacement: $1:$2
通过kubectl apply更新文件
kubectl apply -f prometheus-cfg.yaml
在k8s的k8s-master节点重新生成一个prometheus-deploy.yaml文件
cat >prometheus-deploy.yaml <<EOF
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: prometheus-server
namespace: monitor-sa
labels:
app: prometheus
spec:
replicas: 1
selector:
matchLabels:
app: prometheus
component: server
#matchExpressions:
#- {key: app, operator: In, values: [prometheus]}
#- {key: component, operator: In, values: [server]}
template:
metadata:
labels:
app: prometheus
component: server
annotations:
prometheus.io/scrape: 'false'
spec:
nodeName: k8s-node1
serviceAccountName: monitor
containers:
- name: prometheus
image: prom/prometheus:v2.2.1
imagePullPolicy: IfNotPresent
command:
- "/bin/prometheus"
args:
- "--config.file=/etc/prometheus/prometheus.yml"
- "--storage.tsdb.path=/prometheus"
- "--storage.tsdb.retention=24h"
- "--web.enable-lifecycle"
ports:
- containerPort: 9090
protocol: TCP
volumeMounts:
- mountPath: /etc/prometheus
name: prometheus-config
- mountPath: /prometheus/
name: prometheus-storage-volume
- name: k8s-certs
mountPath: /var/run/secrets/kubernetes.io/k8s-certs/etcd/
- name: alertmanager
image: prom/alertmanager:v0.14.0
imagePullPolicy: IfNotPresent
args:
- "--config.file=/etc/alertmanager/alertmanager.yml"
- "--log.level=debug"
ports:
- containerPort: 9093
protocol: TCP
name: alertmanager
volumeMounts:
- name: alertmanager-config
mountPath: /etc/alertmanager
- name: alertmanager-storage
mountPath: /alertmanager
- name: localtime
mountPath: /etc/localtime
volumes:
- name: prometheus-config
configMap:
name: prometheus-config
- name: prometheus-storage-volume
hostPath:
path: /data
type: Directory
- name: k8s-certs
secret:
secretName: etcd-certs
- name: alertmanager-config
configMap:
name: alertmanager
- name: alertmanager-storage
hostPath:
path: /data/alertmanager
type: DirectoryOrCreate
- name: localtime
hostPath:
path: /usr/share/zoneinfo/Asia/Shanghai
EOF
生成一个etcd-certs，这个在部署prometheus需要
kubectl -n monitor-sa create secret generic etcd-certs --from-file=/etc/kubernetes/pki/etcd/server.key --from-file=/etc/kubernetes/pki/etcd/server.crt --from-file=/etc/kubernetes/pki/etcd/ca.crt
通过kubectl apply更新yaml文件
kubectl apply -f prometheus-deploy.yaml
查看prometheus是否部署成功
kubectl get pods -n monitor-sa | grep prometheus
显示如下，可看到pod状态是running，说明prometheus部署成功
NAME READY STATUS RESTARTS AGE
prometheus-server-5465fb85df-jsqrq 2/2 Running 0 33s
在k8s的k8s-master节点重新生成一个alertmanager-svc.yaml文件
cat >alertmanager-svc.yaml <<EOF
---
apiVersion: v1
kind: Service
metadata:
labels:
name: prometheus
kubernetes.io/cluster-service: 'true'
name: alertmanager
namespace: monitor-sa
spec:
ports:
- name: alertmanager
nodePort: 30066
port: 9093
protocol: TCP
targetPort: 9093
selector:
app: prometheus
sessionAffinity: None
type: NodePort
EOF
通过kubectl apply更新yaml文件
kubectl apply -f prometheus-svc.yaml
查看service在物理机映射的端口
kubectl get svc -n monitor-sa
显示如下：
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
alertmanager NodePort 10.101.168.161 <none> 9093:30066/TCP 10s
prometheus NodePort 10.104.39.13 <none> 9090:32639/TCP 26h
注意：上面可以看到prometheus的service暴漏的端口是31043，alertmanager的service暴露的端口是30066
访问prometheus的web界面
点击status->targets，可看到如下
资源包分享路径：
k8s-tools-all.tar.gz
链接：https://pan.baidu.com/s/1w8YPnAksaxKCasa2j0he4g
提取码：xeo6
参考微信公众号如下：
网友评论