Recently, Elastic announced the AI Assistant for Observability is now generally available for all Elastic users. The AI Assistant enables a new tool for Elastic Observability providing large language model (LLM) connected chat and contextual insights to explain errors and suggest remediation.

Adopting OpenTelemetry native standards for instrumenting and observing applications If you develop applications, you may have heard about OpenTelemetry. At Elastic®, we are enthusiastic about OpenTelemetry as the future of standardized application instrumentation and observability.

Observability goes beyond monitoring; it's about truly understanding your system. To achieve this comprehensive view, practitioners need a unified observability solution that natively combines insights from metrics, logs, traces, and crucially, continuous profiling. While metrics, logs, and traces offer valuable insights, they can't answer the all-important "why." Continuous profiling signals act as a magnifying glass, providing granular code visibility into the system's hidden complexities.

Search powered AI and developer tools built for speed and scale Daily breakthroughs in large language models (LLMs) and generative AI have put developers at the forefront of the movement, influencing its direction and possibilities. In this blog, I’ll share how Elastic's search customers are using Elastic's vector database and open platform for search powered AI and developer tools to accelerate and scale generative AI experiences, giving them new avenues for growth.

Elastic Search 8.13 extends the capabilities that enable developers to use artificial intelligence and machine learning models to create fast and elevated search experiences. Integrated with Apache Lucene 9.10, measured vector search performance has exceeded 2x in benchmarks, extending the sophistication of searches that can be performed in near real time.

Today, we are pleased to announce the general availability of Elastic 8.13.