Managing data automation through hot, warm, cold, and frozen tiers — No coding needed!

Joshua Quek's article provides a comprehensive guide on managing data automation in Elasticsearch using Kibana's "Stack Management" feature to efficiently move data through hot, warm, cold, and frozen tiers without coding. It introduces core concepts like high availability, redundancy, and data partitioning, explaining how data can be distributed across different datacenters or "Availability Zones" to ensure reliability and accessibility. The article uses an Excel spreadsheet analogy to illustrate data sharding and rollovers, emphasizing how partitioned data can enhance search efficiency. Quek outlines a step-by-step process to set up and manage data using Elastic "Data Streams," "Index Templates," and "Index Lifecycle Policies" within Kibana, demonstrating how these tools help control index sizes and facilitate the movement of indices through various data tiers. The guide encourages readers to explore Kibana and Elasticsearch, highlighting their capabilities in handling large datasets effectively.

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