Monitoring Azure Kubernetes Service (AKS) with Azure Monitor & Log Analytics

Part of running Kubernetes is being able to monitoring the cluster, the nodes, and the workloads running in it. Running production workloads regardless of PaaS, VM’s, or containers requires a solid level of reliability. Azure Kubernetes Service comes with monitoring provided from Azure bundled with the semi-managed service. Kubernetes also has built in monitoring that can also be utilized.

It is important to note that AKS is a free service and Microsoft aims to achieve at least 99.5% availability for the Kubernetes API server on the master node side.

But due to AKS being a free service Microsoft does not carry an SLA on the Kubernetes cluster service itself. Microsoft does provide an SLA for the availability of the underlying nodes in the cluster via the Azure Virtual Machines SLA. Without an official SLA for the Kubernetes cluster service it becomes even more critical to understand your deployment and have the right monitoring tooling and plan in place so when an issue arises the DevOps or CloudOps team can address, investigate, and resolve any issues with the cluster.

The monitoring service included with AKS gives you monitoring from two perspectives including the first one being directly from an AKS cluster and the second one being all AKS clusters in a subscription. The monitoring looks at two key areas “Health status” and “Performance charts” and consists of:

Insights – Monitoring for the Kubernetes cluster and containers.

Metrics – Metric based cluster and pod charts.

Log Analytics – K8s and Container logs viewing and search.

Azure Monitor

Azure Monitor has a containers section. Here is where you will find a health summary across all clusters in a subscription including ACS. You also will see how many nodes and system/user pods a cluster has and if there are any health issues with the a node or pod. If you click on a cluster from here it will bring you to the Insights section on the AKS cluster itself.

If you click on an AKS cluster you will be brought to the Insights section of AKS monitoring on the actual AKS cluster. From here you can access the Metrics section and the Logs section as well as shown in the following screenshot.

Insights

Insights is where you will find the bulk of useful data when it comes to monitoring AKS. Within Insights you have these 4 areas Cluster, Nodes, Controllers, and Containers. Let’s take a deeper look into each of the 4 areas.

Cluster

The cluster page contains charts with key performance metrics for your AKS clusters health. It has performance charts for your node count with status, pod count with status, along with aggregated node memory and CPU utilization across the cluster. In here you can change the date range and add filters to scope down to specific information you want to see.

Nodes

After clicking on the nodes tab you will see the nodes running in your AKS cluster along with uptime, amount of pods on the node, CPU usage, memory working set, and memory RSS. You can click on the arrow next to a node to expand it displaying the pods that are running on it.

What you will notice is that when you click on a node, or pod a property pane will be shown on the right hand side with the properties of the selected object. An example of a node is shown in the following screenshot.

Controllers

Click on the Controllers tab to see the health of the clusters controllers. Again here you will see CPU usage, memory working set, and memory RSS of each controller and what is running a controller. As an example shown in the following screenshot you can see the kubernetes dashboard pod running on the kubernetes-dashboard controller.

The properties of the kubernetes dashboard pod as shown in the following screenshot gives you information like the pod name, pod status, Uid, label and more.

You can drill in to see the container the pod was deployed using.

Containers

On the Containers tab is where all the containers in the AKS cluster are displayed. An as with the other tabs you can see CPU usage, memory working set, and memory RSS. You also will see status, the pod it is part of, the node its running on, its uptime and if it has had any restarts. In the following screenshot the CPU usage metric filter is used and I am showing a containers that has restarted 71 times indicating an issue with that container.

 In the following screenshot the memory working set metric filter is shown.

You can also filter the containers that will be shown through using the searching by name filter.

You also can see a containers logs in the containers tab. To do this select a container to show its properties. Within the properties you can click on View container live logs (preview) as shown in the following screenshot or View container logs. Container log data is collected every three minutes. STDOUT and STDERR is the log output from each Docker container that is sent to Log Analytics.

Kube-system is not currently collected and sent to Log Analytics. If you are not familiar with Docker logs more information on STDOUT and STDERR can be found on this Docker logging article here:  https://docs.docker.com/config/containers/logging.

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Deploy MySQL and WordPress on Azure Kubernetes Service (AKS)

In this blog post I am going to walk through the steps for deploying WordPress to Azure Kubernetes Service (AKS) using MySQL and WordPress Docker images. Note that using the way I will show you is one way. Another way to deploy WordPress to AKS would be using a Helm Chart. Here is a link to the WordPress Helm Chart by Bitnami https://bitnami.com/stack/wordpress/helm. Here are the images we will use in this blog post:

MySQL WordPress
apiVersion: v1
kind: Service
metadata:
name: wordpress-mysql
labels:
app: wordpress
spec:
ports:
– port: 3306
selector:
app: wordpress
tier: mysql
clusterIP: None

apiVersion: v1
kind: PersistentVolumeClaim
metadata:
name: mysql-pv-claim
labels:
app: wordpress
spec:
accessModes:
– ReadWriteOnce
resources:
requests:
storage: 20Gi

apiVersion: apps/v1 # for versions before 1.9.0 use apps/v1beta2
kind: Deployment
metadata:
name: wordpress-mysql
labels:
app: wordpress
spec:
selector:
matchLabels:
app: wordpress
tier: mysql
strategy:
type: Recreate
template:
metadata:
labels:
app: wordpress
tier: mysql
spec:
containers:
– image: mysql:5.6
name: mysql
env:
– name: MYSQL_ROOT_PASSWORD
valueFrom:
secretKeyRef:
name: mysql-pass
key: password
ports:
– containerPort: 3306
name: mysql
volumeMounts:
– name: mysql-persistent-storage
mountPath: /var/lib/mysql
volumes:
– name: mysql-persistent-storage
persistentVolumeClaim:
claimName: mysql-pv-claim
apiVersion: v1
kind: Service
metadata:
name: wordpress
labels:
app: wordpress
spec:
ports:
– port: 80
selector:
app: wordpress
tier: frontend
type: LoadBalancer

apiVersion: v1
kind: PersistentVolumeClaim
metadata:
name: wp-pv-claim
labels:
app: wordpress
spec:
accessModes:
– ReadWriteOnce
resources:
requests:
storage: 20Gi

apiVersion: apps/v1 # for versions before 1.9.0 use apps/v1beta2
kind: Deployment
metadata:
name: wordpress
labels:
app: wordpress
spec:
selector:
matchLabels:
app: wordpress
tier: frontend
strategy:
type: Recreate
template:
metadata:
labels:
app: wordpress
tier: frontend
spec:
containers:
– image: wordpress:4.8-apache
name: wordpress
env:
– name: WORDPRESS_DB_HOST
value: wordpress-mysql
– name: WORDPRESS_DB_PASSWORD
valueFrom:
secretKeyRef:
name: mysql-pass
key: password
ports:
– containerPort: 80
name: wordpress
volumeMounts:
– name: wordpress-persistent-storage
mountPath: /var/www/html
volumes:
– name: wordpress-persistent-storage
persistentVolumeClaim:
claimName: wp-pv-claim

The first thing we need to do is save these files as mysql-deployment.yaml and wordpress-deployment.yaml respectively.

Next, we need to setup a password for our MySQL DB. We will do this by creating a secret on our K8s cluster. To do this launch the bash or PowerShell in Azure cloud shell like in the following screenshot and run the following syntax:

kubectl create secret generic mysql-pass –from-literal=password=YOURPASSWORDHERE

Note: Replace “PASSWORDHERE” in the syntax with your own password.

The secret is now created. To ensure it was created you can run the following syntax to list the secrets:

kubectl get secrets

You also can see the secret in the Kubernetes dashboard as shown in the following screenshot.

Next the mysql-deployment.yaml and wordpress-deployment.yaml files from the beginning of this post need to be uploaded to Azure cloudrive storage.

You can also do this in the Cloudshell as shown in the following screenshot.

Run ls in the shell to make sure the files are on your clouddrive.

You will need your home drive. Mine was. /home/steve. To see this, click on Download. It will show you what yours is.

Next create the MySQL Pod and service by running the following syntax.

kubectl apply -f /home/steve/mysql-deployment.yaml

NOTE: You could use kubectl create /home/steve/mysql-deployment.yaml instead of apply to create the MySQL pod and service. I use apply because I typically use the declarative object configuration approach. kubectl apply essentially equals kubectl create + kubectl replace. In order to update an object after it has been created using kubectl create you would need to run kubectl replace.

There are pros and cons to using each and it is more of a preference for example when using the declarative approach there is no audit trail associated with changes. For more information on the multiple Kubernetes Object Management approaches go here: https://kubernetes.io/docs/concepts/overview/object-management-kubectl/overview.

Note that in the mysql yaml file it has syntax to create a persistent volume. This is needed so that the database stays in tact even if the pod fails, is moved etc. You can check to ensure the persistent volume was created by running the following syntax:

kubectl get pvc

Also, you can run the following syntax to verify the mysql pod is running:

kubectl get pods

Deploying the WordPress Pod and service is the same process. Use the following syntax to create the WordPress pod and service:

kubectl apply -f /home/steve/wordpress-deployment.yaml

Again, check to ensure the persistent volume was created. Use the following syntax:

kubectl get pvc

NOTE: When checking right after you created the persistent volume it may be in a pending status for a while like shown in the following screenshot:

You can also check the persistent volume using the K8s dashboard as shown in the following screenshot:

With the deployment of MySQL and WordPress we created 2 services. The MySQL service has a clusterip that can only be accessed internally. The WordPress service has an external IP that is also attached to an Azure Load Balancer for external access. I am not going to expand on what Kubernetes services are in this blog post but know that they are typically used as an abstracted layer in K8s used for access to Pods on the backend and follow the Pods regardless of the node they are running on. For more information about Kubernetes services visit this link: https://kubernetes.io/docs/concepts/services-networking/service.

In order to see that the services are running properly and find out the external IP you can run the following syntax:

kubectl get services (to see all services)

or

kubectl get services wordpress (to see just the WordPress service)

You also can view the services in the K8s dashboard as shown in the following screenshot:

Well now that we have verified the pods and the services are running let’s check out our new WordPress instance by going to the external IP in a web browser.

Thanks for checking out this blog post. I hope this was an easy to use guide to get WordPress up and running on your Azure Kubernetes Service cluster. Check back soon for more Azure and Kubernetes/Container content.

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