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LAS VEGAS--(TECHNO GADGET)--AWS RE:INVENT—New Relic, the Intelligent Observability company, announced a suite of integrations with Amazon Web Services (AWS) that deliver New Relic’s AI capabilities and observability insights directly to AWS AI services. The integrations meet AWS developers, DevOps engineers, SREs and tier 1 and tier 2 incident responders where they work so businesses can securely accelerate AI and agentic workflows, optimize operations and reduce mean time to resolution (MTTR).

“As organizations increasingly adopt AI and agentic workforces, leaders realize that observability isn’t optional — it’s a prerequisite for running AI in production,” said New Relic Chief Product Officer Brian Emerson. “Our integrations with AWS harness the power of agentic AI to predict issues so businesses can go beyond the black box with full-stack AI observability to speed up trouble-shooting and decision making. This fosters business growth and agentic AI in production at scale.”

Overall global AI spending is forecasted to top $2 trillion in 2026, according to Gartner. However, engineering and IT teams using agentic AI face fragmented workflows and lack context that slow release velocity and increase the risk of costly incidents. New Relic has extended its unified Intelligent Observability Platform and its MCP Server to help address these challenges for AWS customers.

Key features and use cases include:

- Auto instrumentation: New Relic agents come equipped with all AIM capabilities, including full AI stack visibility, response tracing, model comparison, and more for quick and easy setup.

- Full AI stack visibility: Holistic view across the application, infrastructure, and the AI layer, including AI metrics like response quality and tokens alongside APM golden signals.

- Deep trace insights for every LLM response: Trace the lifecycle of complex LLM responses built with tools like LangChain to fix performance issues and quality problems such as bias, toxicity, and hallucination.

- Compare performance and costs: Track usage, performance, quality, and cost across all models in a single view; optimize use with insights on frequently asked prompts, chain of thought, and prompt templates and caches.

- Enable responsible use of AI: Ensure safe and responsible AI use by verifying that responses are appropriately tagged to indicate AI-generated and are free from bias, toxicity, and hallucinations using response trace insights.

"Data and knowledge can end up in silos, making it hard to understand what your tools are telling you and when to escalate problems. Together, New Relic and AWS are helping enterprises improve their business workflows and outcomes with AI. Bringing observability directly into the business application workflow is a game changer for gaining fast insights and intelligent recommendations on complex data so you can troubleshoot in real-time."

The integration leverages natural language processing to facilitate interaction, enabling users regardless of their technical skills to ask questions and receive troubleshooting guidance.

By feeding real-time production data such as errors, performance traces, and vulnerabilities into the Amazon Q Business platform, the platform reduces the need for switching between multiple tools, enabling seamless workflow management.

New Relic and Microsoft said the integrations are intended to support organisations adopting AI at scale by reducing operational friction and ensuring teams can maintain service reliability as application complexity continues to grow.

 By - Aaradhay Sharma