kubernetes 1.9+node
首选须要建立一个apiservice(custom metrics AP)。nginx
adapter会根据配置的rules从Prometheus抓取并处理metrics,在处理(如重命名metrics等)完后将其发送到kubernetes的custom metrics API。后续HPA会经过该custom metrics API获取metrics的value进行扩缩容git
部署adapter前须要配置adapter的rule,默认配置为manifests/custom-metrics-config-map.yaml
。adapter的配置主要分为4个:github
Discovery:指定如何获取Prometheus的metrics数据,经过seriesQuery挑选须要处理的metrics集合,能够经过seriesFilters精确过滤metrics。正则表达式
seriesQuery能够根据标签进行查找(以下),也能够直接指定metric name查找shell
seriesQuery: '{__name__=~"^container_.*_total",container_name!="POD",namespace!="",pod_name!=""}' seriesFilters: - isNot: "^container_.*_seconds_total"
seriesFilters:json
is: <regex>, 匹配包含该正则表达式的metrics. isNot: <regex>, 匹配不包含该正则表达式的metrics.
Association:设置metric与kubernetes resources的映射关系,kubernetes resorces能够经过kubectl api-resources
命令查看。overrides会将Prometheus label与一个kubernetes resource(下例为deployment)关联。须要注意的是该label必须是一个真实的kubernetes resource,如metric的pod_name能够映射为kubernetes的pod resource,但不能将container_image映射为kubernetes的pod resource,映射错误可能会致使没法经过custom metrics API获取正确的值。这也表示metric中必须存在一个真实的resource 名称,将其转化为kubernetes resource。bootstrap
resources: overrides: microservice: {group: "apps", resource: "deployment"}
Naming:用于将prometheus metrics名称转化为custom metrics API所使用的metrics名称。若是不须要能够不执行这一步。api
# match turn any name <name>_total to <name>_per_second # e.g. http_requests_total becomes http_requests_per_second name: matches: "^(.*)_total$" as: "${1}_per_second"
如本例中HPA后续能够经过/apis/{APIService-name}/v1beta1/namespaces/{namespaces-name}/pods/*/http_requests_per_second
获取metricsbash
Querying:处理调用custom metrics API获取到的metrics的value
# convert cumulative cAdvisor metrics into rates calculated over 2 minutes metricsQuery: "sum(rate(<<.Series>>{<<.LabelMatchers>>,container_name!="POD"}[2m])) by (<<.GroupBy>>)"
metricsQuery
字段使用Go template将URL请求转变为Prometheus的请求,它会提取custom metrics APIq请求中的字段,并将其划分为metric name,group-resource,以及group-resource中的一个或多个objects,对应以下字段:
Series
: metric名称LabelMatchers
: 以逗号分割的objects,当前表示特定group-resource加上命名空间的label(若是该group-resource 是namespaced的)GroupBy
:以逗号分割的label的集合,当前表示LabelMatchers中的group-resource label假设metrics http_requests_per_second
以下
http_requests_per_second{pod="pod1",service="nginx1",namespace="somens"} http_requests_per_second{pod="pod2",service="nginx2",namespace="somens"}
当调用kubectl get --raw "/apis/{APIService-name}/v1beta1/namespaces/somens/pods/*/http_request_per_second"
时,metricsQuery
字段的模板的实际内容以下:
Series: "http_requests_total"
LabelMatchers: "pod=~\"pod1|pod2",namespace="somens"
GroupBy:pod
github下载k8s-prometheus-adapter
参照官方文档部署
pull镜像:directxman12/k8s-prometheus-adapter:latest,修改镜像tag并push到本地镜像仓库
运行gencerts.sh生成cm-adapter-serving-certs.yaml,并将其拷贝到manifests/
目录下
#!/usr/bin/env bash # exit immediately when a command fails set -e # only exit with zero if all commands of the pipeline exit successfully set -o pipefail # error on unset variables set -u # Detect if we are on mac or should use GNU base64 options case $(uname) in Darwin) b64_opts='-b=0' ;; *) b64_opts='--wrap=0' esac go get -v -u github.com/cloudflare/cfssl/cmd/... export PURPOSE=metrics openssl req -x509 -sha256 -new -nodes -days 365 -newkey rsa:2048 -keyout ${PURPOSE}-ca.key -out ${PURPOSE}-ca.crt -subj "/CN=ca" echo '{"signing":{"default":{"expiry":"43800h","usages":["signing","key encipherment","'${PURPOSE}'"]}}}' > "${PURPOSE}-ca-config.json" export SERVICE_NAME=custom-metrics-apiserver export ALT_NAMES='"custom-metrics-apiserver.monitoring","custom-metrics-apiserver.monitoring.svc"' echo "{\"CN\":\"${SERVICE_NAME}\", \"hosts\": [${ALT_NAMES}], \"key\": {\"algo\": \"rsa\",\"size\": 2048}}" | \ cfssl gencert -ca=metrics-ca.crt -ca-key=metrics-ca.key -config=metrics-ca-config.json - | cfssljson -bare apiserver cat <<-EOF > cm-adapter-serving-certs.yaml apiVersion: v1 kind: Secret metadata: name: cm-adapter-serving-certs data: serving.crt: $(base64 ${b64_opts} < apiserver.pem) serving.key: $(base64 ${b64_opts} < apiserver-key.pem) EOF
建立命名空间:kubectl create namespace custom-metrics
openshift的kube-system下面可能没有role extension-apiserver-authentication-reader
,若是不存在,则须要建立
apiVersion: rbac.authorization.k8s.io/v1 kind: Role metadata: annotations: rbac.authorization.kubernetes.io/autoupdate: "true" labels: kubernetes.io/bootstrapping: rbac-defaults name: extension-apiserver-authentication-reader namespace: kube-system rules: - apiGroups: - "" resourceNames: - extension-apiserver-authentication resources: - configmaps verbs: - get
修改custom-metrics-apiserver-deployment.yaml的--prometheus-url
字段,指向正确的prometheus
建立其余组件:kubectl create -f manifests/
,
HPA支持的metrics类型有4种(下述为v2beta2的格式):
resource:目前仅支持cpu
和memory
。target能够指定数值(targetAverageValue
)和比例(targetAverageUtilization
)进行扩缩容
pods:custom metrics,这类metrics描述了pod,target仅支持按指定数值(targetAverageValue
)进行扩缩容。targetAverageValue
用于计算全部相关pods上的metrics的平均值
type: Pods pods: metric: name: packets-per-second target: type: AverageValue averageValue: 1k
object:custom metrics,这类metrics描述了相同命名空间下的(非pod)对象。target支持经过value
和AverageValue
进行扩缩容,前者直接将metric与target比较进行扩缩容,后者经过metric/相关的pod数目
与target比较进行扩缩容
type: Object object: metric: name: requests-per-second describedObject: apiVersion: extensions/v1beta1 kind: Ingress name: main-route target: type: Value value: 2k
external:kubernetes 1.10+。这类metrics与kubernetes集群无关。与object相似,target支持经过value
和AverageValue
进行扩缩容。因为external能够尝试匹配全部metrics,所以实际中不建议使用该类型。
- type: External external: metric: name: queue_messages_ready selector: "queue=worker_tasks" target: type: AverageValue averageValue: 30
1.6版本支持多metrics的扩缩容,当其中一个metrics达到扩容标准时就会建立pod副本(当前副本<maxReplicas)
注:target的value的一个单位能够划分为1000份,每一份以m
为单位,如500m表示1/2
个单位。参见Quantity
假设注册的APIService为custom.metrics.k8s.io/v1beta1,在注册好APIService后HorizontalPodAutoscaler controller会从以/apis/custom.metrics.k8s.io/v1beta1
为根API的路径上抓取metrics。metrics的API path能够分为namespaced
和non-namespaced
类型的。经过以下方式校验HPA是否能够获取到metrics:
kubectl get --raw "/apis/custom.metrics.k8s.io/v1beta1/namespaces/{namespace-name}/{object-type}/{object-name}/{metric-name...}"
如获取monitor
命名空间下名为grafana
的pod的start_time_seconds
metric
kubectl get --raw "/apis/custom.metrics.k8s.io/v1beta1/namespaces/monitor/pods/grafana/start_time_seconds"
kubectl get --raw "/apis/custom.metrics.k8s.io/v1beta1/namespaces/{namespace-name}/pods/*/{metric-name...}"
如获取monitor
命名空间下名为全部pod的start_time_seconds
metric
kubectl get --raw "/apis/custom.metrics.k8s.io/v1beta1/namespaces/monitor/pods/*/start_time_seconds"
kubectl get --raw "/apis/custom.metrics.k8s.io/v1beta1/namespaces/{namespace-name}/{object-type}/{object-name}/{metric-name...}?labelSelector={label-name}"
kubectl get --raw "/apis/custom.metrics.k8s.io/v1beta1/namespaces/{namespace-name}/pods/*/{metric-name...}?labelSelector={label-name}"
non-namespaced和namespaced的相似,主要有node,namespace,PersistentVolume等。non-namespaced访问有些与custom metrics API描述不一致。
kubectl get --raw "/apis/custom.metrics.k8s.io/v1beta1/namespaces/{namespace-name}/metrics/{metric-name...}"
kubectl get --raw "/apis/custom.metrics.k8s.io/v1beta1/namespaces/*/metrics/{metric-name...}"
kubectl get --raw "/apis/custom.metrics.k8s.io/v1beta1/nodes/{node-name}/{metric-name...}"
使用以下方式查看注册的APIService发现的全部rules
kubectl get --raw /apis/custom.metrics.k8s.io/v1beta1
若是获取失败,能够看下使用oc get apiservice v1beta1.custom.metrics.k8s.io -oyaml
查看status
和message
的相关信息
经过以下方式查看完整的请求过程(--v=8)
kubectl get --raw “/apis/custom.metrics.k8s.io/v1beta1/namespaces/{namespace-name}/pods/*/{metric-name...}" --v=8
--metrics-relist-interval
设置值大于Prometheus的参数scrape_interval
rules
的seriesQuery
规则能够抓取到Prometheus的数据rules
的metricsQuery
规则能够抓取到计算出数据,此处须要注意的是,若是使用到了计算某段时间的数据,若是时间设置太短,可能致使没有数据生成pod
和`namespace label,不然在官方默认配置下没法采集到metrics。遗留问题:
HPA是如何感知注册的apiservice的?
apiservice的工做模型