Azure Kubernetes Metrics

You are going to need an instance of Kube State Metrics running in your cluster so that we can access different metrics that aren't accessible using just Metricbeat. Kube-state-metrics is a simple service that listens to the Kubernetes API server and generates metrics about the state of the objects.

In the Azure cloud shell run the following command to download the kube-state-metrics.

go get k8s.io/kube-state-metrics

Now change into the newly downloaded directory:

cd go/src/k8s.io/kube-state-metrics/

Then to deploy this project to your cluster you simply run:

kubectl apply -f examples/standard

Read more about what configuration and options are available for Kube State Metrics There are different settings and configurations you can use specifically for your cluster but for this example the default settings are being used.

Download the metricbeat kubernetes deployment manifest using the link below:

Click to download metricbeatbeat-kubernetes-7.10.0.yaml

Now you have the manifest you're going to want to add your Stack details. Open the file in a text editor.

Locate the environment variables controlling the logging destination and enter your Stacks Logstash input information.

We need to change the environment variables on both lines 142 & 270.

No input available! Your Stack is missing the required input for this data source Talk to support to add the input

Now your Metricbeat deployment manifest is updated with your Stack details, you can deploy it using the following command in Azure Cloud Shell:

kubectl apply -f metricbeat-kubernetes-7.10.0.yaml

Confirm that your pod has successfully been deployed using one or all of the following commands in Azure Cloud Shell:

kubectl get po -A

kubectl --namespace=kube-system get ds/metricbeat

kubectl --namespace=kube-system get pods

You should see a pod for each Kubernetes node with a name similar to metricbeat-abcde listed.

Now you should view your data:

Launch Dashboard

If you don't see logs take a look at How to diagnose no data in Stack below for how to diagnose common issues.

You should now start to see logs arriving in Kibana from your Kubernetes cluster, similar to the example below.