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Kubernetes based microservice monitoring solution on Azure platform.

This ARM template will deploy a controller VM of Linux Ubuntu 16.04 with default size Standard_A1 in Azure China.

The controller VM will access and manage the Kubernetes cluster you provided, by installing helm charts for monitoring, and acting as proxy of the cluster for accessing.

Two monitoring stacks will be installed:

  • Heapster + Influxdb + Grafana
  • Beats + Logstash + Elasticsearch + Kibana (ELK)

The first one is for cluster resource monitoring (e.g. CPU and memory of Node and Pod), and the second one is for container/app monitoring (e.g. logs of container and heartbeat of the service).

Prerequisite

  • Azure China Cloud subscription
  • Existing Kubernetes cluster

A. Deploy a controller VM for installing monitoring stacks

  1. Click the "Deply to Azure" button
  2. Enter the deployment parameters
Parameter Descrption Default Value
vmDnsName DNS name of the controller VM
vmAdminUsername Administrator user name for the controller VM azureuser
vmAdminPassword Administrator password to login controller VM
vmUbuntuOSVersion The Ubuntu version for the controller VM 16.04.0-LTS
vmSize The size of the Virtual Machine as controller Standard_A1
k8sMasterNodeHostname Kubernetes cluster master node hostname
k8sMasterNodeUsername Kubernetes cluster master node username
k8sMasterNodeIdentityFileBase64 Kubernetes cluster master node identity file in base64 encoded string
monitorClusterNamespace Monitoring cluster namespace in Kubernetes
azureCloudEnvironment Azure cloud environment 'AzureCloud' or 'AzureChinaCloud' AzureChinaCloud
enableElkStack Feature flag to enable ELK monitoring stack or not enabled
enableHigStack Feature flag to enable Heapster-InfluxDB-Grafana monitoring stack or not enabled

B. Connect to the controller VM

  1. Once the deployment completed, get the Public IP address and DNS of the controller VM
  2. SSH into the VM, with the admin username and password provided in deployment parameters
  3. Run the kubectl command below to check if the VM accesses Kubernetes correctly
Kubectl cluster-info
  1. Open a brower, and go to http://< DNS or Public IP address of controller VM >/ui, with the admin username and password provided in deployment parameters, to check if the Kubernetes UI shows correctly

C. View the monitoring stacks

  1. In kubernetes UI, browse the namespace in which the monitoring stacks are deployed
  2. In Services, Grafana and Kibana are exposed as a services with Public IP address
  3. Go to Grafana and Kibana portal with those Public IP address, to check if data is collected and shows correctly

D. Customize the config for data collection

Beats are the data shipper which ships kinds of data to ELK stack. Currently we install Filebeat for shipping container logs, and Heartbeat for service health check.

You can config the Beats per your request, following the official documentation. Here we take Heartbeat as an example to show how to customize the config.

  1. SSH into the controller VM, switch to root account (sudo -i)
  2. Go to /tmp/install/msref, this is where the repo file downloaded
  3. Go to monitoring/k8s/helm-charts/configs/heartbeat-config, edit heartbeat.yml (reference Heartbeat Configuration Options)
  4. Go back to monitoring/k8s/helm-charts, run the commands below
yes | cp -rf configs/heartbeat-config/heartbeat.yml heartbeat/config
helm upgrade -f configs/heartbeat.yaml heartbeat heartbeat/

Reference GitHub projects

elk-acs-kubernetes (MIT License)

This repo contains tools that enable user to deploy ELK stack in Kubernetes cluster hosted in Azure Container Service.

charts (Apach-2.0 License)

Use this repository to submit official Charts for Kubernetes Helm. Charts are curated application definitions for Kubernetes Helm. For more information about installing and using Helm, see its README.md. To get a quick introduction to Charts see this chart document.