Elasticsearch is a memory-intensive application. The default logging subsystem installation deploys 16G of memory for both memory requests and memory limits. The initial set of Red Hat OpenShift Service on AWS nodes might not be large enough to support the Elasticsearch cluster. You must add additional nodes to the Red Hat OpenShift Service on AWS cluster to run with the recommended or higher memory. Each Elasticsearch node can operate with a lower memory setting, though this is not recommended for production environments.
A persistent volume is required for each Elasticsearch deployment configuration. On Red Hat OpenShift Service on AWS this is achieved using persistent volume claims.
If you use a local volume for persistent storage, do not use a raw block volume, which is described with
The OpenShift Elasticsearch Operator names the PVCs using the Elasticsearch resource name.
Fluentd ships any logs from systemd journal and /var/log/containers/ to Elasticsearch.
Elasticsearch requires sufficient memory to perform large merge operations. If it does not have enough memory, it becomes unresponsive. To avoid this problem, evaluate how much application log data you need, and allocate approximately double that amount of free storage capacity.
By default, when storage capacity is 85% full, Elasticsearch stops allocating new data to the node. At 90%, Elasticsearch attempts to relocate existing shards from that node to other nodes if possible. But if no nodes have a free capacity below 85%, Elasticsearch effectively rejects creating new indices and becomes RED.
These low and high watermark values are Elasticsearch defaults in the current release. You can modify these default values. Although the alerts use the same default values, you cannot change these values in the alerts.