Elastic (NYSE: ESTC) has announced a new integration with Azure AI Foundry, marking a major step toward improving observability and performance monitoring for agentic AI applications and large language models (LLMs). The partnership aims to help developers and site reliability engineers (SREs) build, monitor, and optimize intelligent agents more efficiently while ensuring system reliability and compliance.

Real-Time Visibility for Agentic AI

As enterprises race to deploy AI-driven agents across mission-critical environments, operational blind spots are emerging. Many face challenges like uncontrolled token usage, latency bottlenecks, and compliance risks that limit scalability. Elastic’s integration directly tackles these issues through pre-built dashboards that provide unified, real-time insights into model performance, costs, and content filtering.

With Elastic’s observability tools layered into Azure AI Foundry, developers can visualize performance metrics, identify inefficiencies, and apply cost controls—all without switching platforms.

Guardrails and Performance Insights

“Agentic AI is only as strong as the models and infrastructure that power it,” said Santosh Krishnan, General Manager of Observability & Security at Elastic. “With Elastic and Azure AI Foundry, developers and SREs gain clear visibility into how their agents perform, understand cost drivers, and fix performance bottlenecks in real time. That means they can scale AI applications faster without compromising reliability, compliance, or budget.”

The integration adds built-in safeguards that monitor token consumption, latency, and operational expenses, helping teams maintain control over production environments.

Microsoft Strengthens Azure’s AI Ecosystem

The move also aligns with Microsoft’s push to make Azure AI Foundry a comprehensive hub for building and managing AI workloads. “This integration with Elastic delivers real-time visibility into token usage, latency, and costs, with built-in safeguards for any model hosted in Azure AI Foundry,” said Amanda Silver, Corporate Vice President at Microsoft Azure CoreAI. “Developers can now build and scale agents on Azure AI Foundry with the operational clarity and control they need to succeed in production.”

Why It Matters

The integration underscores a growing trend in the AI infrastructure landscape—where visibility, governance, and efficiency are becoming just as critical as model innovation. As agentic AI expands beyond experimental phases into production-grade systems, observability will play a defining role in maintaining trust and performance across workloads.

Elastic’s observability suite, combined with Azure’s compute and model hosting capabilities, positions the partnership as a significant advantage for enterprises investing in large-scale AI transformation.

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