Install Elasticsearch on Kubernetes Using Helm Chart

The ELK Stack natively integrates with Kubernetes, where it serves as a monitoring stack – it collects, stores, and analyzes k8 telemetry data. There are several methods for setting up and deploying the ELK stack on Kubernetes, and using helm charts is the most straightforward one.

In this tutorial, you will learn how to utilize a helm chart to install Elasticsearch, the main component of the ELK stack, as well as Kibana and Metricbeat (in place of Logstash), on your Kubernetes cluster.

• A Kubernetes cluster (you can create it with minikube)
• kubectl command-line tool installed
• Helm package manager installed

1. First, start Minikube. A multi-node cluster for Elasticsearch requires significant system resources, so make sure you allocate enough CPUs and memory using the --cpus and --memory options:

minikube start --cpus 4 --memory 8192

2. Check if your cluster is functioning properly by typing:

kubectl cluster-info

The output confirms that the Kubernetes control plane and KubeDNS are running:

1. To start installing Elasticsearch, add the elastic repository in Helm:

helm repo add elastic https://helm.elastic.co

2. Now, use the curl command to download the values.yaml file containing configuration information:

curl -O https://raw.githubusercontent.com/elastic/helm-charts/master/elasticsearch/examples/minikube/values.yaml

3. Use the helm install command and the values.yaml file to install the Elasticsearch helm chart:

helm install elasticsearch elastic/elasticsearch -f ./values.yaml

The -f option allows specifying the yaml file with the template. If you wish to install Elasticsearch in a specific namespace, add the -n option followed by the name of the namespace.

helm install elasticsearch elastic/elasticsearch -n [namespace] -f ./values.yaml

The output confirms the status of the app as deployed and offers additional options to test the installation:

4. The first option is to use the get pods command to check if the cluster members are up:

kubectl get pods --namespace=default -l app=elasticsearch-master -w

Once the READY column in the output is entirely populated with 1/1 entries, all the cluster members are up:

The other option is to use the helm test command to examine the cluster’s health:

helm test elasticsearch

5. Once you successfully installed Elasticsearch, use the kubectl port-forward command to forward it to port 9200:

kubectl port-forward svc/elasticsearch-master 9200

1. To install Kibana on top of Elasticsearch, type the following command:

helm install kibana elastic/kibana

The output confirms the deployment of Kibana:

2. Check if all the pods are ready:

kubectl get pods

Kibana pod appears underneath the Elasticsearch pods:

3. Forward Kibana to port 5601 using kubectl:

kubectl port-forward deployment/kibana-kibana 5601

4. After you set up port-forwarding, access Elasticsearch, and the Kibana GUI by typing http://localhost:5601 in your browser:

Installing Metricbeat follows the same pattern as installing Kibana.

1. Use Helm to issue the install command:

helm install metricbeat elastic/metricbeat

2. Confirm that the Metricbeat pods are up and running:

kubectl get pods

3. To see Elasticsearch metric indexing, use the curl command:

curl localhost:9200/_cat/indices

4. Visit Kibana. You will now be able to create an index pattern. Navigate to Stack Management > Index patterns:

5. Click the Create Index Pattern button to start working with Kibana.

After following this tutorial, you should know how to install Elasticsearch, Kibana, and Metricbeat in Kubernetes using the helm chart.

The ELK stack can also be deployed outside of Kubernetes. If you want to know more about this topic, read how to install ELK stack on Ubuntu.