All news with #opensearch tag

Amazon OpenSearch Service Adds Automatic Semantic Enrichment

🔍 Amazon OpenSearch Service now provides automatic semantic enrichment for managed domains, extending an earlier capability from OpenSearch Serverless to managed clusters and enabling semantic search with minimal configuration. The feature performs semantic processing automatically so customers do not need to manage ML models. It supports English-only and multilingual variants across 15 languages (including Arabic, French, Hindi, Japanese, and Korean) and is billed based on ingestion usage as OpenSearch Compute Unit (OCU) - Semantic Search. The capability requires OpenSearch 2.19 or later and is currently available for non‑VPC domains in selected AWS Regions; see the OpenSearch Service documentation for setup and configuration details.

Amazon OpenSearch: GPU-Accelerated Auto-Optimized Vectors

🚀Amazon OpenSearch Service now offers GPU-accelerated, auto-optimized vector indexes that let teams build billion-scale vector databases in under an hour. Serverless GPU acceleration can speed index builds up to 10X while reducing indexing cost to roughly a quarter of previous expenses. Auto-optimize jobs evaluate k-NN algorithms, quantization, and engine settings against specified latency and recall targets to produce configuration recommendations without manual tuning. These capabilities support vector collections and OpenSearch 2.17+/3.1+ domains across multiple regions.

OpenSearch Service Introduces Agentic Search for NLP Queries

🔎 Amazon Web Services has introduced Agentic Search for OpenSearch Service, an agent-driven layer that interprets natural-language intent, orchestrates search tools, and generates OpenSearch DSL queries while providing transparent summaries of its decision process. The built-in QueryPlanningTool uses LLMs to plan and emit DSL, removing the need for manual query syntax. Two agent types are available: conversational agents with memory and flow agents optimized for throughput. Administrators can configure agents via APIs or OpenSearch Dashboards, and Agentic Search is supported on OpenSearch Service version 3.3+ across AWS Commercial and GovCloud regions.

AWS OpenSearch Service adds PPL and natural language

🔍 Amazon OpenSearch Service now makes Piped Processing Language (PPL) and natural language the default experience in the OpenSearch UI Observability workspace. The release introduces 35+ new commands for deep analysis, faceted exploration, and natural-language querying, and integrates OpenTelemetry ingestion pipelines to simplify onboarding. Users can run enterprise-grade queries, correlate events, and move directly from query to visualization to reduce mean time to detect and resolve issues.

Amazon OpenSearch Service: OpenSearch 3.3 Now Available

📢 Amazon OpenSearch Service now supports OpenSearch 3.3, introducing search performance, observability, and agentic AI integration improvements. Vector search enhancements include agentic search for natural-language queries without complex DSLs, batch processing for the semantic highlighter to lower latency and improve GPU utilization, and optimizations in the Neural Search plugin. The release also makes Apache Calcite the default query engine for PPL, adds a broader PPL command library, and improves the approximation framework for more responsive pagination and dashboards. A new workload management plugin enables grouping of search traffic and tenant-level network isolation to prevent resource overuse.

Amazon OpenSearch Adds OR2 and OM2 Instances in Regions

🚀 Amazon Web Services has expanded OR2 and OM2 OpenSearch Optimized instances into additional global regions, delivering higher indexing throughput and S3-based managed storage for indexing-heavy workloads. In AWS internal benchmarks OR2 showed up to 26% higher indexing throughput vs OR1 (70% vs R7g) and OM2 up to 15% vs OR1 (66% vs M7g). Both families include local instance caching, S3-managed storage, pay-as-you-go and reserved pricing, and a range of sizes to fit different compute and memory needs.

Amazon OpenSearch Service Adds Cluster Insights Dashboard

🔍 Amazon OpenSearch Service now includes Cluster Insights, a unified monitoring dashboard that consolidates logs and metrics to give operators comprehensive operational visibility across nodes, indices, and shards. The feature automates correlation of critical data, highlights performance metrics and top‑N query analysis, and surfaces targeted remediation steps to speed troubleshooting. Built into the OpenSearch UI, Cluster Insights retains monitoring resilience during cluster unavailability and provides account‑level summaries for managing multiple deployments. It is available at no additional cost for OpenSearch 2.17 or later in regions where the OpenSearch UI is offered.

OpenSearch Service Adds Graviton4 EC2 Instance Support

🚀 Amazon OpenSearch Service now supports Graviton4-based EC2 instance families — compute-optimized C8g, general-purpose M8g, and memory-optimized R8g/R8gd — across multiple regions. Graviton4 processors deliver up to 30% better performance compared with Graviton3 and are supported on all OpenSearch versions as well as Elasticsearch 7.9 and 7.10. The change is intended to improve price-performance for compute-, general-, and memory-intensive search and analytics workloads.

OpenSearch Star-Tree Index Speeds Aggregations for Analytics

⚡ OpenSearch introduces the Star-Tree Index, an opt-in index type that pre-aggregates data at ingestion to enable sub-second responses for frequent high-cardinality and multi-dimensional aggregations such as terms, histogram, and range. The feature is designed for real-time analytics and requires no query syntax changes; OpenSearch automatically routes supported queries to the optimized path. Early benchmarks indicate markedly faster aggregation performance on large datasets with minimal impact to ingestion throughput. Available in regions that support OpenSearch 3.1 and enabled at index creation via composite index settings.

OpenSearch Adds Derived Source Feature to Reduce Storage

🔧 Amazon OpenSearch Service announced support for Derived Source, an opt-in feature that lets you omit persisting the document _source and reconstruct it dynamically when needed. The capability, available with OpenSearch 3.1, reduces domain storage by skipping stored _source fields while still supporting search, get, mget, reindex, and update operations. Enable Derived Source at index creation using composite index settings.

Amazon OpenSearch Service Adds AI-Powered Forecasting

📈 Amazon now lets customers generate AI-powered forecasts and visualizations from time-series data indexed into Amazon OpenSearch Service domains. Forecasts can enhance insights into infrastructure utilization, application and business metrics, website traffic, and system performance to help anticipate upcoming changes. You can set up forecasts directly from OpenSearch dashboards or the OpenSearch UI, and no data science or AI expertise is required. The feature is available in all regions that support OpenSearch 3.1+ domains.

Amazon OpenSearch Service adds OpenSearch 3.1 for vectors

🚀 Amazon OpenSearch Service now supports OpenSearch 3.1, bringing targeted improvements for vector-driven and traditional search workloads. The release bundles Lucene 10 for optimized vector field indexing, faster indexing times, reduced index sizes, sparse indexing, and vector quantization to lower memory usage. It also improves range query and high-cardinality aggregation latency and introduces a new Search Relevance Workbench for iterative quality testing. Additional vector search enhancements include Z-score normalization for more reliable hybrid search and memory-optimized Faiss support; OpenSearch 3.1 is available in all AWS Regions.