Reducing long-term logging expenses by 4,800% with Amazon OpenSearch Service

This article discusses ways to reduce long-term logging expenses by up to 4,800% using Amazon OpenSearch Service. It examines the trade-offs between cost, latency, throughput, data durability and availability, retention, and data access.

Specifically, the article covers:

• Examining your requirements for latency, durability, availability, cost, retention, and data access
• Understanding the OpenSearch Service cost model for data nodes, UltraWarm nodes, and Amazon S3 storage
• An example use case of a company storing 3TB of log data daily and reducing costs from $14 million to $288,000 annually
• Using ephemeral storage deployments with replicas for high availability and durability
• Using Amazon S3 backed storage like UltraWarm and UltraWarm cold storage to reduce costs
• Using OpenSearch Service zero-ETL integration with Amazon S3 for infrequently queried data
• Additional techniques like data sampling and compression to further reduce data size and costs