Releases
Elastic 8.15 includes enhancements in semantic search, new OTel collector distribution, AI-driven SIEM data onboarding, LLM integrations, additions to cross-cluster search (CCS), and more functionality within the Elasticsearch Query Language (ES|QL).
Elastic Platform 8.15: Native vector database now supports bit vectors, SIMD acceleration, and simple config
Elasticsearch native vector database now supports bit vectors, SIMD acceleration, and int4 quantization. The new semantic_text field type makes generating embeddings simple. ES|QL has new query capabilities and an expanded UI in Kibana Discover.
NEW in Elastic Security 8.15: Automatic Import, Gemini models, and AI Assistant APIs
Elastic Security 8.15 introduces Automatic Import, support for Gemini 1.5 Pro/Flash Models, on-demand scanning for the Elastic Defend integration, a full set of APIs for the Elastic AI Assistant, and a redesigned context pivot in the details flyout.
Elastic Observability 8.15: AI Assistant, OTel, and log quality enhancements
Introducing Elastic Observability 8.15: Elastic Distribution for OTel Collector, native OTLP profiling, AI Assistant support for Google Vertex (Gemini 1.5 Pro model), LLM observability for Azure OpenAI, and logs data set quality improvements.
Releases
Elastic Platform 8.14: ES|QL GA, encryption at rest, and vector search optimizations
Elastic Platform 8.14 includes ES|QL GA, the use of AI for pattern recognition in logs, API key based security model for remote clusters, encryption at rest with KMS keys, retrievers, several vector optimizations, and vector quantization by default.
Elastic Search 8.14: Faster and more cost-effective vector search, improved relevance with retrievers and reranking, RAG and developer tooling
With Elastic Search 8.14, vector search is faster and more cost-effective. Key components for semantic and contextual searches are now seamlessly integrated into Elasticsearch APIs. We introduce more robust tooling enhancements.
