Elastic N.V. announced the general availability of version 6.6 of the Elastic Stack. This release delivers powerful features that bring powerful operational efficiencies across several use cases, such as, logging, metrics, and APM. Index lifecycle management and frozen indices simplify how users operationalize, automate, and organize their data as it comes in and as they want to make more data available for analyses. Elasticsearch 6.6 also introduces geoshapes backed by the Bkd tree storage format, which brings higher storage densities and faster query speeds to geodata. Optimize Operational Efficiencies with Index Lifecycle Management: Elasticsearch users have always enjoyed a lot of control on how their data is indexed and stored to strike the right balance between performance and cost tradeoffs for their use case. Version 6.6 introduces foundational features into Elasticsearch that help users operationalize those choices over the lifecycle of their data. Index lifecycle management separates the lifecycle of an index into four phases - hot, warm, cold, and delete - andlets the user define and automate policies to control how long an index should live any phase, and the set of actions (for example, move data from hot node to cold node) to be taken on the index during each phase. Index lifecycle management is available as a free, Basic subscription feature. Frozen Indices Provide New, Long-Term Data Retention Capabilities: Elasticsearch 6.6 also introduces frozen indices that dramatically reduce memory requirements (and by extension hardware specs), and support more cost-effective sizing recommendations for long-term data retention needs. Frozen indices can be queried just like open indices, but trade off query speeds for a lower memory footprint. Users are always looking for new dimensions and techniques to manage hardware spend, and frozen indices give these users one more tool in the toolbox to reduce their memory footprint and hardware costs. Frozen indices is available as a free, Basic subscription feature. Faster Indexing and Query Speeds for Geo Data with Bkd-backed Geoshapes: Continuing in the storage and performance theme, Elasticsearch 6.6 introduces Bkd-backed geoshapes, resulting in significant storage and performance improvement when querying geoshape data. This feature brings the benefits of the more efficient BKD tree based storage format to more data types, and by extension to additional use cases. Bkd-backed geoshapes is available as an Elastic Stack open source feature. Elasticsearch SQL improvements: New functionality, such as, the ability to query IP address fields, native support for date histograms, and support for geo querying are great for all users of Elasticsearch SQL. These improvements, available through the Basic subscription, will make it easier to build time-series charts in Kibana Canvas. Elastic APM Gains Additional Deployment Options: Elastic has always provided users with a choice on how they consume Elastic technology, and recent releases extend that choice to Elastic APM. Elastic users can now add Elastic APM to their deployments running in Elasticsearch Service or Elastic Cloud Enterprise. Distributed tracing was introduced as a beta feature in Elastic APM version 6.5 and is now also generally available as a free, Basic subscription feature. Additionally, Elastic APM is now OpenTracing compatible. Other significant developments include: Preconfigured machine learning jobs for Auditbeat data to detect unusual events in audit data, especially security-related anomalies. Elastic Cloud Enterprise 2.1 launches with support for cross-cluster search, IP filtering, and other 6.6 goodies.