Elasticsearch, a widely used log storage solution, requires careful configuration to prevent common issues and optimize performance, especially in production environments. Key configurations involve setting appropriate cluster and node names, ensuring data is stored in safe locations, and managing network settings to facilitate smooth communication between nodes. Critical to successful Elasticsearch operation is understanding and configuring the Java Virtual Machine (JVM) heap space appropriately, as well as defining clear data mappings to avoid schema-related errors. Additionally, common mistakes such as failing bootstrap checks, oversized templating, inadequate capacity provisioning, and improper shard management can hinder cluster performance. Addressing these issues involves familiarity with Elasticsearch's configuration options, such as dynamic templates for mappings, collection modes for combinable data, and settings to prevent search timeouts and shard failures. Properly configuring these elements ensures a stable and efficient Elasticsearch deployment capable of handling the demands of a production environment.