Install the Analyzer on Google Kubernetes Engine
- Having a GCP account with permissions to create and administer Kubernetes Clusters.
- A GCP Project with Kubernetes API active.
- Having a machine with
Install the necessary tools
On the machine or VM you will use to administer the cluster:
kubectl, follow the official Kubernetes documentation.
gcloud, follow the GCP documentation.
helm, follow the official Helm documentation.
Download the Helm charts
You can download the helm charts with:
Create a cluster
- Once the Kubernetes API is activated and you have the necessary permissions to create and administer a Cluster, we will create one.
- On your Project page, click on Kubernetes Engine.
- Once in the Clusters tab, click on Create and select the Standard Cluster.
- In the Cluster basics section, name your analyzer.
- Click on default pool and change the number of nodes from 3 to 1, check the Enable cluster autoscaler box.
- Lower down the page, set the Minimum number of nodes at 1 and Maximum number of nodes at 2.
- Click on the Nodes tab on the left and change the image type from Container-Optimized OS with containerd to Ubuntu with containerd.
- In the Machine configuration section, set the machine type to fit the requirements to host the analyzer as described in docs.latence.ca.
- Set the boot disk size at 20GB as requested for the analyzer to run properly.
- If your application can handle a less stable environment, select Enable nodes on spot VMs, since this is a demo/test environment, we can check the box. This will also reduce the cost of the cluster.
- In the Automation tab on the left, select Enable vertical Pod autoscaling.
- Finally you can hit Create, and wait for your cluster to be set up.
Install the Analyzer
You can remotely connect to your cluster using this command in your terminal:
gcloud container clusters get-credentials <cluster-name> --zone <cluster-zone> --project <project-name>
- You can see the running components of your cluster by entering:
kubectl get all
- Take note of the Cluster-IP.
We will need to modify three parameters in our
1) The Latencetech License.
2) The IP address the Kafka pod will use.
3) The IP address zookeeper will use.
Set your license.
- Set the IP address Kafka will use in the IP range of the Cluster-IP we saw above.
- Set the IP address Zookeeper will use in the IP range of the Cluster-IP we saw above.
- Set that same IP address as zookeeperEndpoint in the Kafka section
- Once the IP addresses are set, we can install the analyzer running this command:
helm install analyzer k8s-analyzer/
- Wait 60 seconds for all the services and pods to be deployed.
- You can check the status of deployment by running:
kubectl get all
- Once done, you can get the External IP address your analyzer was deployed at running this command:
kubectl get svc