New Relic Launches Open-Source Tool for AI Coding Observability
New Relic introduces AI Coding Observability, an open-source tool designed to monitor and manage the use of AI assistants in software development workflows.
New Relic has released AI Coding Observability, a new open-source tool aimed at bringing much-needed visibility into the rapidly expanding landscape of AI-assisted software development. As organizations increasingly adopt AI coding assistants to boost productivity, these tools often operate outside traditional observability systems, creating blind spots for IT and security teams. This new offering extends monitoring capabilities directly into the coding process, allowing companies to track, analyze, and audit how AI coding assistants are being utilized.
"You can’t manage what you can’t see," stated Brian Emerson, Chief Product Officer at New Relic. "AI coding assistants are having a measurable impact on businesses, but without real-time oversight into how they’re behaving, organizations are scaling risk as fast as they’re scaling output. New Relic AI Coding Observability will close this gap, removing barriers to quality innovation that succeeds in production."
Gartner predicts that by 2028, 90% of enterprise software engineers will leverage AI code assistants. However, the current reality is a fragmented ecosystem where developers use a variety of tools depending on the task. New Relic AI Coding Observability is designed to provide a unified, vendor-neutral platform that normalizes telemetry data from major AI coding assistants and correlates it with existing production infrastructure, future-proofing development strategies.
The tool offers several key benefits. Teams can gain comprehensive insights into AI coding tool behavior, moving beyond blind trust to understand actual usage patterns. It also addresses cost control by allowing organizations to track AI spend, eliminate "black box" invoices, and forecast expenses against budgets. Furthermore, it aims to enhance productivity metrics by replacing anecdotal evidence with hard data on efficiency and identifying hidden failure modes.
Security and compliance are also central to the design. A "local-only / zero-outbound" mode ensures that queries run entirely within a user's private network, guaranteeing data sovereignty, privacy, and regulatory compliance. The open-source nature of the code also provides strong code transparency, empowering engineering and security teams to independently verify data privacy protocols and AI reasoning.
To prevent vendor lock-in, the feature is built natively on the OpenTelemetry protocol and Model Context Protocol (MCP). This allows organizations to seamlessly port their telemetry data and AI workflows across different cloud ecosystems and language model providers. The tool is designed for broad coverage, with initial support for assistants including Claude Code, Cursor, GitHub Copilot, Windsurf, and Amazon Q.
New Relic AI Coding Observability will be available as an open-source feature starting June 23rd at no additional cost. This move democratizes access to essential monitoring capabilities for AI-assisted development, a critical step as AI integration becomes standard practice in software engineering.