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Elasticsearch & Full Text Search Systems · Lesson

Production Deployment Strategies

Review best practices for deploying Elasticsearch in production, including hardware sizing, backup/restore, and disaster recovery plans.

Production Deployment Intro

Deploying Elasticsearch in production requires careful planning. Unlike development setups, production environments demand high availability, performance, and robust data integrity.

This lesson covers essential strategies for hardware sizing, data backup, and disaster recovery to ensure your Elasticsearch cluster is ready for prime time.

Hardware Sizing: CPU & RAM

Proper hardware sizing is foundational for a stable and performant cluster. For CPU, aim for a balance: too few cores limit processing, too many can increase licensing costs unnecessarily.

  • CPU: More cores generally mean better performance for indexing and complex queries.
  • RAM: Allocate about half of the physical RAM to the JVM heap (e.g., 30-32GB max). The remaining RAM is crucial for the operating system's filesystem cache, which Elasticsearch heavily relies on.

All lessons in this course

  1. Geospatial Search Capabilities
  2. Time-Series Data Management
  3. Production Deployment Strategies
  4. Index Lifecycle Management
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