Maximize your Elasticsearch performance and cost efficiency. Our guide covers indexing, querying, resource management, and cost optimization for your deployments.

Quesma

A practical guide to improving Elasticsearch performance and reducing costs across five areas: indexing strategy (bulk API, shard sizing, mapping management), efficient querying (filters and caching), resource management (cluster health monitoring, JVM tuning), cost optimization via Index Lifecycle Management (ILM hot/warm/cold/delete phases), and horizontal scalability planning. Key tips include targeting 20–40 GB shard sizes, using keyword and match_only_text types instead of text where possible, setting JVM heap to 50% of RAM, and automating index lifecycle policies to move data to cheaper storage tiers.

Maximizing Elasticsearch's performance and cost efficiency