Elastic Universal Profiling™ agent is now open source! The industry’s most advanced fleetwide continuous profiling solution empowers users to identify performance bottlenecks, reduce cloud spend, and minimize their carbon footprint. This post explores the history of the agent, its move to open source, and its future integration with OpenTelemetry.

As AI continues to grow and solve problems across countless industries, a key part of that tech is the ability to seamlessly bridge the gap between human language and machine understanding. This is where natural language processing (NLP) and large language models (LLMs) come in. They provide distinct and specialized approaches for connecting the power of human communication with software and machines. Or in simpler terms, NLP and LLMs enable us to have human-like conversations with software.

Site reliability engineers (SREs) and security analysts — despite having very different roles — share a lot of the same goals. They both employ proactive monitoring and incident response strategies to identify and address potential issues before they become service impacting. They also both prioritize organizational stability and resilience, aiming to minimize downtime and disruptions.

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.

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.

Manage and correlate signals and alerts in Elastic Observability As organizations embrace increasingly complex and interconnected IT systems, the sheer volume of alerts generated by diverse monitoring tools has given rise to a critical challenge — how do we efficiently sift through the noise to identify and respond to the most crucial issues? Event management and correlation are two indispensable pillars in the realm of IT service management.

The term “data mesh” isn’t especially new, but the definition of what it is and does is perhaps not widely agreed upon, so let’s explore it a bit.