New Relic has
introduced new agentic AI integrations with Microsoft Azure designed to bring observability data directly into the tools that developers and reliability teams already rely on. The updates link New Relic’s Model Context Protocol (MCP) Server with Azure Monitor, the Azure SRE Agent, and Microsoft Foundry. The goal is to reduce context-switching, speed up incident response, and give engineering teams clearer visibility into how AI-driven applications behave in production.
Camden Swita, Head of AI, New Relic, told ChannelE2E, “Agentic integrations between New Relic and Azure fundamentally transform how DevOps and SRE teams resolve incidents by bringing critical telemetry data, intelligent observability insights, and actionable recommendations directly into Azure product workflows where they can use it to make informed decisions faster and take decisive action.”
Cloud and AI adoption continue to rise, but the operational roadblocks remain familiar. Teams still burn time piecing together context from multiple tools, whether they’re verifying an alert or tracing the impact of a recent deployment. New Relic’s MCP Server is meant to compress those tasks into a single workflow, giving Azure’s AI agents immediate access to the observability data they need.
Bringing Observability Into the Azure SRE Agent
A core part of the announcement is the integration between the Azure SRE Agent and the New Relic MCP Server. When an alert fires or a deployment rolls out, the SRE Agent can call New Relic for a real-time snapshot of what’s happening across services, applications, and infrastructure. This helps teams get from detection to diagnosis faster and reduces the back-and-forth typically required during an incident.
Swita explains what this unlocks for customers: “With New Relic’s MCP Server integrated into Azure services such as the Azure SRE Agent, teams can now triage incidents, analyze root causes, and orchestrate remediation using natural language within their existing Azure workflows, without context-switching or losing visibility. This unified real-time view correlates infrastructure changes, telemetry, and configuration data to eliminate blind spots, accelerate diagnosis, and strengthen collaboration between teams.”
According to Swita, this shift has a direct impact: “Because workflows that once took hours can now be completed in minutes, customers can expect significant reductions in MTTR by automating incident triage, root cause analysis, and remediation across hybrid cloud environments.”
Expanding Support for AI App Development in Microsoft Foundry
The announcement also includes new capabilities for Microsoft Foundry, where developers build and manage AI applications across GitHub, Visual Studio, Copilot Studio, and Microsoft Fabric. With New Relic supplying logs and metrics directly into Foundry workflows, teams get a clearer understanding of how their AI apps and agents behave throughout the development lifecycle.
Swita highlights the MCP-specific advantage: “New Relic’s approach is differentiated because it leverages the gold standard for agentic context gathering and analysis: Model Context Protocol (MCP). As the Azure SRE Agent evolves and Microsoft builds new agents - or Azure Foundry customers build their own - they can continue leveraging the same New Relic MCP Server without manual configuration required by other integrations.”
This allows observability to stay tied to the workflow rather than the tool, keeping teams focused on building and tuning their applications.
Closing Visibility Gaps Across Azure Infrastructure
Platform engineering teams often face fragmented visibility across their environments. New Relic’s Azure Autodiscovery feature aims to reduce those gaps by surfacing unmonitored resources and mapping dependencies across services. Engineers can overlay configuration changes directly onto performance graphs to see where issues originate and how they spread.
This matters even more as AI agents take on a larger share of remediation tasks. Swita notes: “New Relic ensures accuracy and safety of its AI-driven insights by grounding all analysis in concrete telemetry data and deterministic features. AI agents on other platforms often operate with limited access to the production data required to make reliable decisions, but New Relic eliminates this risk by delivering complete, context-rich observability directly into AI workflows.”
He adds that the design keeps humans in control: “Teams maintain full visibility and control, ensuring automated actions are informed by accurate telemetry, workflows remain transparent and auditable, and remediation aligns to the operational safeguards DevOps and SRE teams already use.”
New Relic also noted that monitoring for SAP Solutions is now available on Microsoft Marketplace. The tool provides predictive visibility into SAP and connected systems without relying on agents inside SAP itself. For Azure customers that run business-critical SAP workloads, this creates a clearer operational picture and reduces the risk of disruptions. Swita underscored one of the differentiators here: “New Relic offers a native connector to SAP systems, while competitors are forced to use third-party tools to connect with SAP on the cloud.”
