Once the upgrade is complete, the monitoring data is now available in Kibana. The monitoring  dashboards present a wealth of information about the Elasticsearch cluster, including  valuable information about how much log data is running through it. Navigate to the  Monitoring  Elasticsearch (cluster) >  Nodes  section. All the nodes  that make up the current Elasticsearch cluster are displayed, along with extremely useful data  about JVM memory consumption and CPU usage per node. Assuming that the workload in  the current cluster is realistic, it’s more clear to see if the current resource allocation for the  management node CPU cores, or the JVM heap, is enough to handle the current workload  plus additional spikes. Currently, in the above cluster, JVM memory usage for the data nodes is around 60% which is  suitable for the current environment, plus a 40% overhead to handle temporary excess log  data. If this value was around 80% or 90% consistently, it would be beneficial to double the  allocated resources in the  logging-elk-data  StatefulSet. The current data nodes’ CPU usage  is around 30% and the maximum value the nodes have hit is around 60%, so for the current  workload, the CPU cores assigned to the management nodes are sufficient. In all cases,  these values should be monitored for changes and adjusted as required to keep the logging  services in a stable state. High CPU usage is an indicator that there is memory pressure in  the data nodes due to garbage collection processes. Figure 5-6 Kibana monitoring Figure 5-7 Monitoring dashboard for Elasticsearch nodes 166  IBM Cloud Private System Administrator’s Guide