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.
Table of contents
1. Optimized indexing strategy2. Efficient querying techniques3. Resource management4. Cost optimization5. Scalability planningBest practices for adding nodesSort: