How-To: Set up Fluentd, Elastic search and Kibana in Kubernetes

How to install Fluentd, Elastic Search, and Kibana to search control plane logs in Kubernetes


Install Elastic search and Kibana

  1. Create a Kubernetes namespace for monitoring tools

    kubectl create namespace radius-monitoring
  2. Add the helm repo for Elastic Search

    helm repo add elastic
    helm repo update
  3. Install Elastic Search using Helm

    By default, the chart creates three replicas which must be on different nodes. If your cluster has fewer than 3 nodes, specify a smaller number of replicas with the --set replicas=1 flag:

    helm install elasticsearch elastic/elasticsearch --version 7.17.3 -n radius-monitoring --set replicas=1

    If you are using minikube or simply want to disable persistent volumes for development purposes, you can do so with --set persistence.enabled=false:

    helm install elasticsearch elastic/elasticsearch --version 7.17.3 -n radius-monitoring --set persistence.enabled=false,replicas=1
  4. Install Kibana

    helm install kibana elastic/kibana --version 7.17.3 -n radius-monitoring
  5. Ensure that Elastic Search and Kibana are running in your Kubernetes cluster

    kubectl get pods -n radius-monitoring

    You should see:

    NAME                            READY   STATUS    RESTARTS   AGE
    elasticsearch-master-0          1/1     Running   0          6m58s
    kibana-kibana-95bc54b89-zqdrk   1/1     Running   0          4m21s

Install Fluentd

  1. Install config map and Fluentd as a daemonset

    Download these config files:

    Note: If you already have Fluentd running in your cluster, enable the nested json parser so that it can parse JSON-formatted logs from radius.

    Apply the configurations to your cluster:

    kubectl apply -f ./fluentd-config-map.yaml
    kubectl apply -f ./fluentd-radius-with-rbac.yaml
  2. Ensure that Fluentd is running as a daemonset. The number of Fluentd instances should be the same as the number of cluster nodes. In the example below, there is only one node in the cluster:

    kubectl get pods -n kube-system -w

    You should see:

    NAME                          READY   STATUS    RESTARTS   AGE
    coredns-6955765f44-cxjxk      1/1     Running   0          4m41s
    coredns-6955765f44-jlskv      1/1     Running   0          4m41s
    etcd-m01                      1/1     Running   0          4m48s
    fluentd-sdrld                 1/1     Running   0          14s

Install Radius control plane

Visit the Kubernetes docs to learn how to install the Radius control plane. By default, Radius has JSON logging enabled.

For Kubernetes, you can install with the rad CLI:

rad install kubernetes

Search logs

Once the Radius control plane is installed, you can search the logs using Kibana.

Note: There is a small delay for Elastic Search to index the logs that Fluentd sends. You may need to wait a minute and refresh to see your logs.

  1. Port-forward from localhost to svc/kibana-kibana

    kubectl port-forward svc/kibana-kibana 5601 -n radius-monitoring

    You should see:

    Forwarding from -> 5601
    Forwarding from [::1]:5601 -> 5601
    Handling connection for 5601
    Handling connection for 5601
  2. Browse to http://localhost:5601

  3. Expand the drop-down menu and click Management → Stack Management

    Stack Management item under Kibana Management menu options

  4. On the Stack Management page, select Data → Index Management and wait until radius-* is indexed.

    Index Management view on Kibana Stack Management page

  5. Once radius-* is indexed, click on Kibana → Index Patterns and then the Create index pattern button.

    Kibana create index pattern button

  6. Define a new index pattern by typing radius* into the Index Pattern name field, then click the Next step button to continue.

    Kibana define an index pattern page

  7. Configure the primary time field to use with the new index pattern by selecting the @timestamp option from the Time field drop-down. Click the Create index pattern button to complete creation of the index pattern.

    Kibana configure settings page for creating an index pattern

  8. The newly created index pattern should be shown. Confirm that the fields of interest such as scope, type, app_id, level, etc. are being indexed by using the search box in the Fields tab.

    Note: If you cannot find the indexed field, please wait. The time it takes to search across all indexed fields depends on the volume of data and size of the resource that the elastic search is running on.

    View of created Kibana index pattern

  9. To explore the indexed data, expand the drop-down menu and click Analytics → Discover.

    Discover item under Kibana Analytics menu options

  10. In the search box, type in a query string such as scope:* and click the Refresh button to view the results.

    Note: This can take a long time. The time it takes to return all results depends on the volume of data and size of the resource that the elastic search is running on.

    Using the search box in the Kibana Analytics Discover page