kubernetes heapster

Heapster is a container cluster monitoring and performance analysis tool that naturally supports kubernetes and CoreOS.Kubernetes has a well-known surveillance agent-cadvisor. The cadvisor is run on each kubernetes node, and it collects monitoring data (cpu,memory,filesystem,network,uptime) for both native and container.In the newer version, K8S has integrated th

First, IntroductionHeapster is a cluster-wide monitoring and event data aggregator. It natively supports kubernetes and can be run on all kubernetes settings. Heapster is run as a cluster in a group, similar to how any other kubernetes application runs. InfluxDB is an open source database written in go that i

Spec:Serviceaccountname:Heapster containers: -Name:Heapster image: k8s.GCR.io/Heapster-Amd64:v1.4.2Imagepullpolicy:Ifnotpresent command: - /heapster ---source=kubernetes:https://kubernetes.default ---sink=influxdb:http://150.109.39.33:31001 # Here fill in the address of the INFLUXDB server just recorded. --- Apiversion:v1 Kind:service metadata: Labels: task:monitoring # for use as a Cluster

1. First to the outside network to download the image to pour into the various nodes2. Download the Yaml file and create the appMKDIR-P ~/k8s/heapster cd ~/k8s/heapster wget https://raw.githubusercontent.com/kubernetes/heapster/master/deploy/kube-config/influxdb/ Grafana.yaml wget https:// Raw.githubusercontent.com/

=influxdb:http://monitoring-influxdb:8086 Note: modify ---source for your own master apiserver access address , Modify the image address (provided above) Heapster-service.yaml[[Email Protected]_master UI]#Cat Heapster-service.yamlapiVersion:v1kind:Servicemetadata:labels:task:monitoring#For use as a Cluster add-on (https://github.com/kubernetes/

Kubernetes Dashboard is a generic web-based UI for Kubernetes clusters. It allows users to manage and troubleshoot applications running in a cluster, and to manage the cluster itself.Deploying DashboardProject GitHub AddressOfficial documentation ReferenceGet Yaml filecurl -O https://raw.githubusercontent.com/kubernetes/dashboard/master/src/deploy/recommended/

Objective In the K8S resource audit and billing this piece, the container and the virtual machine have very big difference. The container is not easy to implement relative to the virtual machine.Resource metrics can be collected using Heapster or Prometheus. Before the article has introduced, Prometheus Storage bottleneck and query large data volume, easy to oom these two problems. So I chose the heapster.

Kubernetes Dashboard1.8.3 Deployment DescriptionPlease click images to download and use the image below. Installing Dashboard#下载yamlwget https://raw.githubusercontent.com/kubernetes/dashboard/master/src/deploy/recommended/kubernetes-dashboard.yaml#查看yaml中imageimage: k8s.gcr.io/kubernetes-dashboard-amd64:v1.8.3

Export kubeconfig=/etc/kubernetes/admin.conf echo "Export kubeconfig=/etc/kubernetes/admin.conf" >> ~/. Bash_profile 2.2 Installation Network addon To Docker can communicate with each other need to do some configuration, here with flannel to achieve Kubectl apply-f https://raw.githubusercontent.com/coreos/flannel/v0.9.1/Documentation/kube-flannel.yml After the installation is complete, check to see if

establish a secure communication mechanism with Apiserver, you must not use insecure port. Kubernetes Apiserver Secure port is also on by default and the port is 6443. At the same time, Apiserver opens the basic auth (–basic-auth-file=/srv/kubernetes/basic_auth_file). This way, dashboard will not be able to access apiserver secure port properly by passing the –apiserver-host parameter and pass basic auth.

).MetricsHere is official suggested solution as follows. For more informaton, please see Tools for monitoring Compute, Storage, and Network ResourcesGrafana + heapster/prometheus + cadvisor + InfluxDBHeapster As a Metircs aggregator and processorInfluxDB Time Series database for storageGrafana As a dashboarding and alerting solutionCadvisor Have been built in Kubelet, which collects host metrics like CPUs, disk space, and memory utilization, in additi

automatically added load balancing, and then delete the old version. To view application events: Application events primarily collect event information that is applied to the Kubernetes cluster. Monitoring, Alarm systemMonitoring alarms We have two major categories of PAAs platforms and business applications. The PAAs platform focuses on monitoring alarms for the various service components of the infrastructure and leengine (such as host CPU, mem

:v1.8.3 heapster-influxdb-amd64:v1.3.3 heapster-grafana-amd64:v4.4.3 heapster-amd64:v1.4.2 )for imageName in ${images[@]} ; dodocker pull registry.cn-shenzhen.aliyuncs.com/duyj/$imageNamedocker tag registry.cn-shenzhen.aliyuncs.com/duyj/$imageName k8s.gcr.io/$imageNamedocker rmi registry.cn-shenzhen.aliyuncs.com/duyj/$imageNamedonedocker pull quay.io/cor

From Mesos to KubernetesThe previous scheduling framework was based on Mesos self-research. The language used is Python. Run for about two years, and has been relatively stable. But as the business grows, the problems of the existing framework are gradually exposed. Scheduling speed encountered bottlenecks, affecting the deployment of large business speed. There is no good support for stateful services. There are two solutions to this problem, one for improved refactoring of ex

/services/monitoring-grafan/proxyTo open a connection:You can see the CPU, memory, load and other utilization graphs of each Nodes, Pods, if the utilization graph is not visible on dashboard, restart the dashboard pod using the following command: First deletekubectl scale deploy kubernetes-dashboard --replicas=0 -n kube-system And then create a newkubectl scale deploy kubernetes-dashboard --rep

1.14.5Registry.cn-shenzhen.aliyuncs.com/rancher_cn/k8s-dns-dnsmasq-nanny-amd64 1.14.5Registry.cn-shenzhen.aliyuncs.com/rancher_cn/heapster-influxdb-amd64 v1.3.3Registry.cn-shenzhen.aliyuncs.com/rancher_cn/heapster-grafana-amd64 v4.4.3Registry.cn-shenzhen.aliyuncs.com/rancher_cn/heapster-amd64 v1.4.0The contents of the Pause-amd64/3.0/dockerfile file in my privat

The Cluster Lifecycle layer adds self-hosted functionality to Kubeadm, which means that Kubernetes can be run on Kubernetes, which is bootstrap. Bootstrap is considered to be a system of "elegance" of a embodiment, in fact, Kubernetes in the early attempt to bootstrap, now Kubeadm directly add this feature, is undoubtedly a step closer. In addition, the KUBEADM c

management system that namespace/resourcequota/deployment/service/ The call of API such as endpoint realizes the partition of resource quota and management of application life cycle. The biggest challenge for the container cloud platform in terms of ease of use is the troubleshooting, the container cloud is ultimately delivered to the developer, and they don't know about kubernetes, which makes troubleshooting a challenging process. Now we just want

applications require the container to obtain the host's IP address, this block we made some changes to the kubernetes, You can dynamically inject the host name information such as the host IP into the container's environment variables. Q:ECP The positioning and resolution of the target compared with the current people in the traditional cloud platform solution in terms of? A:ECP product positioning is a complete container solution, from

The Kubernetes network model is made up of four parts from inside to outside: The network where the pod interior container resides The network where the pod resides Network for communication between pod and service Network of communication between outside and service It is recommended that you understand the network model of Docker before reading this article. Refer to the author's first two articles [