All Articles
LLM Observability with Elastic’s Azure AI Foundry Integration
Gain comprehensive visibility into your generative AI workloads on Azure AI Foundry. Monitor token usage, latency, and cost, while leveraging built-in content filters to ensure safe and compliant application behavior—all with out-of-the-box observability powered by Elastic.
Elastic MongoDB Atlas Integration: Complete Database Monitoring and Observability
Comprehensive MongoDB Atlas monitoring with Elastic's integration - track performance, security, and operations through real-time alerts, audit logs, and actionable insights.
Monitoring Proxmox VE deployments with Elastic Observability
Monitoring Proxmox VE deployments, VMs, and Linux Containers with Elastic Observability.
The next evolution of observability: unifying data with OpenTelemetry and generative AI
Generative AI and machine learning are revolutionizing observability, but siloed data hinders their true potential. This article explores how to break down data silos by unifying logs, metrics, and traces with OpenTelemetry, unlocking the full power of GenAI for natural language investigations, automated root cause analysis, and proactive issue resolution.
Debugging Azure Networking for Elastic Cloud Serverless
Learn how Elastic SREs uncovered and resolved unexpected packet loss in Azure Kubernetes Service (AKS), impacting Elastic Cloud Serverless performance.
Pivoting Elastic's Data Ingestion to OpenTelemetry
Elastic has fully embraced OpenTelemetry as the backbone of its data ingestion strategy, aligning with the open-source community and contributing to make it the best data collection platform for a broad user base. This move benefits users by providing enhanced flexibility, efficiency, and control over telemetry data.
Connecting the Dots: ES|QL Joins for Richer Observability Insights
Now in tech preview, ES|QL LOOKUP JOIN lets you enrich logs, metrics, and traces at query time no need to denormalize at ingest. Add deployment, infra, or business context dynamically, reduce storage, and accelerate root cause analysis in Elastic Obervability.
Optimizing Spend and Content Moderation on Azure OpenAI with Elastic
We have added further capabilities to the Azure OpenAI GA package, which now offer content filter monitoring and enhancements to the billing insights!
Transforming Industries and the Critical Role of LLM Observability: How to use Elastic's LLM integrations in real-world scenarios
This blog explores four industry specific use cases that use Large Language Models (LLMs) and highlights how Elastic's LLM observability integrations provide insights into the cost, performance, reliability and the prompts and response exchange with the LLM.
Observability for Amazon MQ with Elastic: Demystifying Messaging Flows with Real-Time Insights
RabbitMQ, managed by Amazon MQ, enables asynchronous communication in distributed architectures but introduces operational risks such as retries, processing delays, and queue backlogs. Elastic’s Amazon MQ integration for RabbitMQ delivers deep observability into broker health, queue performance, message flow, and resource usage through Amazon CloudWatch metrics and logs. This blog outlines key operational risks associated with RabbitMQ and explains how Elastic observability helps maintain system reliability and optimize message delivery at scale.
LLM Observability for Google Cloud’s Vertex AI platform - understand performance, cost and reliability
Enhance LLM observability with Elastic's GCP Vertex AI Integration — gain actionable insights into model performance, resource efficiency, and operational reliability.
Elastic Distributions of OpenTelemetry (EDOT) Now GA: Open-Source, Production-Ready OTel
Elastic is proud to introduce General Availability of Elastic Distributions of OpenTelemetry (EDOT), which contains Elastic’s versions of the OpenTelemetry Collector and several language SDKs like Python, Java, .NET, and NodeJS. These help provide enhanced features and enterprise-grade support for EDOT.