Elastic, publicly traded on the New York Stock Exchange under the symbol ESTC and known as the Search AI Company, has expanded its collaboration with Microsoft by introducing a new integration that brings advanced observability to Azure AI Foundry. The companies are working together to give developers and site reliability engineers a deeper lens into the behavior and performance of agentic AI systems and large language models as they scale into production environments. This integration is focused on ensuring that intelligent agents operate efficiently and securely while organizations continue adopting artificial intelligence for essential business tasks.
As demand increases for AI that can make decisions and take actions, enterprises are facing mounting concerns tied to real time performance monitoring and governance. Agentic systems can experience runaway token consumption, slow response times, and compliance issues if left unchecked. Elastic’s new capabilities aim to directly confront these challenges. Through a set of prebuilt dashboards and analytical tools, teams can monitor usage patterns, inspect model activity, and track operational costs without switching between multiple monitoring solutions. The insights are presented in a single cohesive interface that highlights reliability risks and exposes areas where optimization is needed.
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Santosh Krishnan, general manager of Observability and Security at Elastic, emphasized the importance of visibility and proactive control as more artificial intelligence is deployed to support business critical functions. “Agentic AI is only as strong as the models and infrastructure that power it,” he said. “With Elastic and Azure AI Foundry, developers and SREs gain clear visibility into how their agents are performing, understand the drivers of cost, and fix performance bottlenecks in real time. That means they can scale AI applications faster without compromising reliability, compliance, or budget.”
Microsoft sees the collaboration as a step toward helping organizations adopt AI with confidence. Amanda Silver, corporate vice president at Microsoft Azure CoreAI, noted that better observability gives teams the clarity needed to push AI solutions from experimentation into full scale deployment. “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,” she said. “Developers can now build and scale agents on Azure AI Foundry with the operational clarity and control they need to succeed in production.”
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By enhancing performance monitoring for models running inside Azure AI Foundry, Elastic is positioning itself as a central layer of intelligence that supports the shift to agent driven digital experiences. The company believes that observability, cost transparency, and automated safeguards are essential pillars as enterprises continue to move beyond generative AI experimentation and into strategic, long term adoption.
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