Today, Amazon OpenSearch Service introduces a new engine purpose-built for log analytics workloads, delivering up to 4x better price-performance on internal benchmarks. It combines this efficiency with the full-text search capabilities that OpenSearch is known for, so users can still run the ad hoc queries that incident investigation depends on. As log volumes grow with cloud-native architectures, AI workloads, and expanding compliance needs, teams spend more of their time on aggregations and trend analysis to uncover broader patterns — while incident investigations still call for precise text
The increasing volume of log data from cloud-native architectures and AI workloads is driving demand for more efficient log analytics solutions.
This development offers significant price-performance improvements for organizations grappling with large-scale log data, enhancing operational efficiency and incident response.
Organizations can now process and analyze log data more cost-effectively, reducing operational expenditures and potentially improving the speed and depth of incident investigations.
- · AWS
- · Amazon OpenSearch Service users
- · Cloud-native companies
- · AI-driven enterprises
- · Less efficient log analytics solutions
- · Organizations slow to adopt optimized log processing
Companies reduce operational costs associated with log management and analysis.
Improved log analytics capabilities lead to faster incident resolution and better system observability.
The enhanced efficiency in log processing could enable more sophisticated AI-driven analysis of operational data, leading to new insights and automation opportunities.
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Read at AWS What's New