Optimizing Elasticsearch Performance with ILM: Seeking Guidance

Hey Folks,

I'm reaching out for some guidance on grasping the ins and outs of ILM (Index Lifecycle Management).

Currently, my ELK setup for production consists of a three-node Elasticsearch cluster, with dedicated servers for Kibana and Logstash. Additionally, there are no specified nodes for data, master, or ml purposes.

Now, I'm keen to integrate ILM Policies to efficiently manage indices and enhance the overall performance of the cluster in our production environment. However, I'm grappling with a question: given the absence of node definitions for the Elasticsearch nodes, how will implementing ILM Policies for high-volume time-series indices, along with configuring hot, warm, and cold phases, benefit us?