Blog
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Open Distro for Elasticsearch 1.4.0 with K-nearest neighbor (k-NN) search support is now available
We are happy to announce the release of Open Distro for Elasticsearch 1.4.0. Version 1.4.0 includes the upstream open source versions of Elasticsearch 7.4.2, Kibana 7.4.2 and the latest updates for the alerting, SQL, security, performance analyzer and Kibana plugins. We are also pleased to announce the general availability of Open Distro for Elasticsearch k-NN plugin, and installer for Windows...
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Real Time Root Cause Analysis in Open Distro for Elasticsearch
The Open Distro for Elasticsearch Performance Analyzer captures Elasticsearch and JVM activity, as well as lower-level resource usage (e.g. disk, network, CPU and memory) of these activities. Based on this instrumentation, Performance Analyzer computes and exposes diagnostic metrics, with the goal of enabling Elasticsearch users and administrators to measure and understand bottlenecks in their Elasticsearch clusters. The Open Distro for...
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Announcing Open Distro for Elasticsearch 1.3.0, Helm chart for Kubernetes and Windows support
We are pleased to announce the release of Open Distro for Elasticsearch 1.3.0. Version 1.3.0 includes the upstream open source versions of Elasticsearch 7.3.2, Kibana 7.3.2 and the latest updates for the alerting, SQL, security, performance analyzer and Kibana plugins. We are excited to announce the general availability of Open Distro for Elasticsearch Index Management, installer for Windows deployments, Helm...
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Real Time Anomaly Detection in Open Distro for Elasticsearch
Today, we released Anomaly Detection (preview) on Open Distro for Elasticsearch. We are excited to continue our work on anomaly detection as a part of Open Distro for Elasticsearch in the coming months, and invite developers in the larger search community to join in and co-develop some parts. The feature includes a nice mix of machine learning algorithms, statistics methods,...
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Random Cut Forests
We plan to publish a series of blogs discussing the science and math behind Random Cut Forests (RCF). In this first post we begin with a brief overview of Random Forests as a class of Machine Learning model. Next, we introduce RCFs and highlight their relevance to streaming data. Finally, we close with a look to the future, giving ideas...
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