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.

Elasticsearch and Kibana 8.13 deliver simplified kNN, improved query parallelization plus improvements to ES|QL, anomaly detection, and new improved health indicators. Also announcing the Elastic Integration Filter and GA of Kafka for Elastic Agent.

Simplify configuring cross-cluster search, execute vector search faster, detect data drifts and log rate dips, stream Elastic Agent to Kafka, and authenticate Webhook connector using third-party security certificates with Elastic Stack 8.10.

Elastic Learned Sparse Encoder is an AI model for high relevance semantic search across domains. As a sparse vector model, it expands the query with terms that don't exist in the query itself, delivering superior relevance without domain adaptation.

In Elastic 8.0, Elastic Stack security is on by default for self-managed clusters. To get started, simply spin up Elasticsearch and Kibana, connect them using the new web UI, and they work together securely, out of the box.

Alerting in the Elastic Stack is generally available with the 7.11 release and adds better ways to manage alerts as well as a new integration with Microsoft Teams.

7.9 introduces a new architecture for Kibana, delivering instant page loads for faster navigation. Also in this release, Elastic Enterprise Search integration, a new security layer in Elastic Maps, and model snapshot management for machine learning.

We’re excited to announce a new alerting framework that delivers a first-class alerting experience natively within the SIEM, Uptime, APM, and Metrics applications as part of the Kibana 7.7 release.