The OpenSearch Project recently concluded its first hackathon, awarding prizes to three "agentic skills" designed to automate log analysis, GDPR compliance, and query performance t…
OpenSearch Query Insights now features built-in dashboards that provide real-time and historical monitoring of query performance through interactive visualizations. These tools all…
The AOSC (Automatic Online Schema Change) plugin for OpenSearch enables live index migrations with different mappings, settings, or shard counts within a single cluster. It automat…
OpenSearch 3.8 introduces an experimental memory retention feature for agentic memory containers, allowing users to set age-based or count-based limits to automatically delete stal…
This article provides a technical guide on using Zabbix agents to monitor both operating system metrics and various applications within Windows environments. It details deployment …
The massive volume of telemetry produced by AI agents makes traditional per-GB observability pricing unsustainable and leads to costly, fragmented tool sprawl. The OpenSearch Obser…
The new OpenSearch KEDA scaler, introduced in KEDA 2.20, allows Kubernetes workloads to scale directly based on any arbitrary query result from OpenSearch, such as error rates or l…
OpenSearch 3.7 introduces the ability to retrieve vectors via `docvaluefields` rather than the traditional `source` path, allowing for direct reading from the columnar store. This …
The OpenSearch Observability Stack is an OpenTelemetry-native platform that unifies metrics, traces, and logs into a single correlated store to streamline root cause analysis. The …
This article discusses how vector search in OpenSearch acts as a semantic safety net to prevent zero-result pages when traditional lexical search strategies fail to match user inte…
The OpenSearch agent server is an experimental multi-agent orchestration platform that enables users to build and deploy specialized AI agents for specific tasks within OpenSearch.…
OpenSearch 3.5 introduces support for asymmetric embedding models, which enhance semantic search relevance by applying distinct encoding strategies to short queries and long, infor…