Geo Roadmap for Elasticsearch and Kibana: Layers, GeoJSON, Vega

The blog post introduces the roadmap for geo features in Elasticsearch and Kibana, highlighting enhancements that allow users to create multi-layered maps with advanced geospatial data analysis capabilities. Users will be able to choose base layers from the Elastic Maps Service, add multiple data layers, and customize them through stylesheets and shape layers, with no limits on the number of layers. The integration of GeoJSON directly into the Kibana UI will automatically create indices in Elasticsearch, facilitating seamless use across different maps. Additional features in development include support for Vega visualizations, custom map layers, on-premises map deployment, and region maps, all aimed at expanding the geospatial analytical power of the Elastic Stack. The post is part of a series from the Elastic{ON} 2018 conference, which also covered various other topics related to Elasticsearch, such as machine learning forecasting, security analytics, and operational data analysis.

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