You can now run OpenSearch version 2.17 in Amazon OpenSearch Service. With OpenSearch 2.17, we have made several improvements in the areas of vector search, query performance and machine learning (ML) toolkit to help accelerate application development and enable generative AI workloads.
This launch introduces disk-optimized vector search, a new option for the vector engine that’s designed to run efficiently with less memory to deliver accurate, economical vector search at scale. In addition to this, OpenSearch’s FAISS engine now supports byte vectors lowering cost and latency by compressing k-NN indexes with minimal recall degradation. You can now encode numeric terms as a roaring bitmap that enables you to perform aggregations, filtering and more, with lower retrieval latency and reduced memory usage.
This launch also includes key features to help you build ML-powered applications. Firstly, with ML inference search processors you can now run model predictions while executing search queries. In addition to this, you can also perform high-volume ML tasks, such as generating embeddings for large datasets and ingesting them into k-NN indexes using asynchronous batch ingestion. Finally, this launch adds threat intelligence capabilities to Security Analytics solution. This enables you to use customized Structured Threat Information Expression (STIX)-compliant threat intelligence feeds to provide insights to support decision-making and remediation.
For information on upgrading to OpenSearch 2.17, please see the documentation. OpenSearch 2.17 is now available in all AWS Regions where Amazon OpenSearch Service is available.
Source:: Amazon AWS