Introducing memory retention for agentic memory in OpenSearch
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…
Back to all articles
Category
Technical
35 articles · Page 2 of 3
Windows Monitoring with Zabbix
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 real cost of your observability stack
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…
Scaling Kubernetes Workloads with the OpenSearch KEDA Scaler
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…
Retrieve vectors 5x faster with docvalue_fields in OpenSearch
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 …
Single pane of glass for all your telemetry: The OpenSearch Observability Stack
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 …
No more zero results with vector query relaxing in OpenSearch
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…
Bringing intelligence to OpenSearch: Introducing the OpenSearch agent server
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.…
Asymmetric model support: Optimizing semantic search for queries and documents
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…
Agentic SDLC: How OpenSearch accelerates engineering with its own engine
The OpenSearch team has developed four AI agents—Atlas, Ralph, Nitro, and Sentinel—to automate repetitive tasks throughout the software development lifecycle, ranging from knowledg…
Personalizing your contact center agent using OpenSearch agentic memory
OpenSearch agentic memory addresses the lack of conversational context in AI contact center agents by providing persistent, personalized memory across multiple interactions. By uti…
Introducing the OpenSearch Hadoop connector 2.0: Spark 4 support, OpenSearch Serverless, and more
The OpenSearch Hadoop connector 2.0 has been released, introducing support for Apache Spark 3.5 and 4, as well as official compatibility for OpenSearch 3.x. The update also adds su…