Elastic announced the general availability of Elastic 8.0 with enhancements across the Elastic Search Platform and its Enterprise Search, Observability, and Security solutions.
Updates include native vector search, native support for modern natural language processing models, increasingly simplified data onboarding, and a streamlined security experience.
Native support for natural language processing (NLP), now generally available, enables the use of custom or third-party PyTorch machine learning models directly in Elasticsearch. The addition of native NLP support with vector search enables users to perform inference within Elasticsearch, resulting in faster and more relevant search results.
In addition, customers can now leverage enhanced vector search capabilities, including the general availability of native support for approximate nearest neighbor (ANN) search, to quickly and efficiently perform queries on enormous data sets such as documents, images, audio files, and more.
Elastic native vector search extends technology commonly associated with searching for image and text content into the world of business data. For example, organizations can use vector search with NLP support to deliver faster, more relevant customer support information, improve customer shopping experiences with unique product alternatives, and enhance search accessibility by providing unique audio and visual search results.
Additionally, expanded security features across the Elastic Search Platform include new default security settings to secure data, network, and user information in self-managed clusters. Auto-generated tokens and certificates, streamline and simplify security to help users save time and effort.
A more simplified Elastic Cloud on AWS onboarding experience includes new integrations to speed data ingestion, including the new Elastic Serverless Forwarder. Designed as an AWS Lambda application and published in the AWS Serverless Application Repository, the Elastic Serverless Forwarder enables users to simplify their architectures and streamline data ingestion without the overhead of provisioning virtual machines or installing data shippers.
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