New Relic is expanding beyond traditional monitoring with the launch of a new AI agent platform and enhanced OpenTelemetry integration, a move aimed squarely at enterprises struggling to manage increasingly complex AI-powered systems.
The company said the new platform allows customers to build and manage AI agents directly within New Relic, while also improving how OpenTelemetry (OTel) data is ingested and analyzed. The release marks one of New Relic’s most significant pushes yet into AI infrastructure, as enterprises move from AI experimentation to production deployments and demand clearer visibility into how those systems perform.
As companies deploy AI agents that make decisions, call APIs and interact with users, observability has become more complicated. Traditional monitoring tools were designed for predictable application workloads. AI agents, by contrast, can behave in less deterministic ways, making it harder for teams to track performance, reliability and downstream impact. New Relic is positioning its new tools as a way to close that gap by combining agent creation and monitoring in a single environment.
Instead of requiring enterprises to build agents with one framework and monitor them with another, the company is offering an integrated approach. IT teams can create agents within the platform and observe their behavior using the same data model and interface they already use for application performance monitoring. For existing New Relic customers, that continuity could reduce the need to add yet another standalone AI observability tool to the stack.
The OpenTelemetry enhancements are a key piece of the strategy. OTel has emerged as a widely adopted open standard for collecting telemetry data across distributed systems. New Relic said its expanded integration makes it easier for enterprises to pipe OTel data into the platform and correlate it with AI agent metrics. That unified view is increasingly important as organizations juggle containerized workloads, microservices and AI-driven components across cloud environments.
The move also sharpens competition with other observability vendors. Datadog and Dynatrace have both rolled out AI-focused monitoring features in recent months. New Relic’s approach differs in that it is not just observing AI systems built elsewhere; it is offering tools to build and manage agents within its own platform.
The broader bet is that observability must be embedded into AI workflows from the outset, not added after agents are already in production. As enterprises scale AI deployments, they are looking for ways to track performance and reliability without multiplying tools. By tying AI agent development to its core observability platform and doubling down on open standards like OpenTelemetry, New Relic is aiming to position itself at the center of that shift.
Whether enterprises are ready to treat their observability vendor as an AI development platform remains to be seen. But as AI workloads grow more distributed and harder to monitor, vendors that can offer both visibility and control are likely to play a larger role in how companies manage their next generation of infrastructure.
This analysis is based on reporting from techbuzz.
Image courtesy of New Relic.
This article was generated with AI assistance and reviewed for accuracy and quality.
