New Relic’s Intelligent Observability Platform Is Ambitious

New Relic has released what could be its most ambitious observability platform to date.

Announced during the New Relic Now+ 2025 user’s conference in February, the company describes its New Relic Intelligent Observability Platform as an all-comprehensive observability solution that significantly lowers the threshold of adoption and use by nonoperations teams.

As such, it is designed to improve accessibility and usability for all users within an organization — and, according to the company, it provides easier integration for operations teams when setting up panels, for example.

The platform offers a very wide range of services that are largely tied to database analysis and, of course, AI-generated assistance. Its simplicity is largely attributed to the fact that all the data, which was traditionally managed in house, can now be sent to New Relic, which takes care of the rest. This would otherwise represent a significant project to manage internally.

For the platform release, New Relic takes on the massive tasks of data analysis, insight generation and integration. The platform’s “intelligent recommendations” integrate retrieval-augmented generation (RAG) from New Relic’s platform with user organization-defined data and third-party sources so you can take immediate action. According to the company, all of this data is managed within the platform for the user.

When will you be able to play video games all day as AI-assisted observability finds and fixes bugs and outages? Maybe never, but CEO Ashan Willy says @Newrelic‘s platform can already communicate with “other systems of action” to automatically resolve issues. pic.twitter.com/TOPepfRSpE

— BC Gain (@bcamerongain) February 27, 2025

What such a platform should offer was one of the topics of New Relic CEO Ashan Willy’s keynote given during New Relic Now+ 2025. “What happens today in observability is that we provide you with a ton of data, including opinionated data and views, and ask you to solve the problems,” Willy said. “Intelligent observability, on the other hand, means that the platform does the work for you, and for the first time, we have that ability.”

As he described it, the platform must draw conclusions for the user and solve problems. “These problems can be addressed interactively, providing you with a set of information so you can resolve them more quickly,” he said. “Alternatively, the platform can solve them automatically. It can communicate with other systems of action to help automatically resolve issues, significantly reducing your mean time to detect and mean time to repair.”

While New Relic’s platform is designed to meet these goals, how well it will work in practice remains to be seen. Touting Context Connector, using retrieval-augmented generation (RAG) for observability, as an “industry’s first,” said Manav Khurana, chief product officer for New Relic, during a presentation at New Relic Now+.

“You can now feed New Relic AI your prior incident retros, and New Relic AI will perform pattern analysis to determine if there’s a match, providing hints to help you solve problems faster,” Khurana said. “The second is the new Change Intelligence agent in New Relic AI, which identifies whether a change caused a problem. Changes are the leading contributors to incidents, and this agent helps determine what to do and how to fix the issue.”

What the Platform Can Do

The features the platform offers that the company shared include:

• Agentic integrations: Enables integrations between AI agents to bring New Relic’s critical observability data and intelligent recommendations across the organization’s entire infrastructure and cloud environments. Google Gemini will build upon New Relic’s expanding AI integration ecosystem that includes GitHub Copilot and Amazon Q Business.
• Response intelligence: Contextualizes all metrics, changes and services — including external sources like ITSMs — to accelerate incident resolution. Unifies telemetry data and correlates it in a single view, providing AI-strengthened impact analysis and mitigation recommendations based on past incidents.
• Predictions: The Predictions engine uses machine learning algorithms to analyze historical data, quickly identify patterns and forecast time-series metrics within a singular interface. The idea is to anticipate performance issues and bugs before they occur.
• Cloud-cost intelligence:  Delivers detailed views into multicloud cost trends, drivers and impacts for business teams’ current and future cloud investments.
• Pipeline control: Designed to improve the quality and value of telemetry data to control data, manage costs, ensure security and compliance, and understand ROI. A pipeline rules engine manages data, allowing users to route, filter and tweak all telemetry data that is ingested.
• Service architecture intelligence: Simplifies service, infrastructure, incident and quality management by consolidating critical knowledge on these aspects into customizable catalogs, scorecards, teams and maps.
• Video streaming: For streaming media, video and ad experiences across devices and regions are managed.
• Engagement intelligence: Automates data collection and uses intelligent element attribution to capture every interaction, eliminating manual instrumentation and accelerating how organizations analyze and improve digital user interactions. The platform correlates user behavior beyond the frontend application to the underlying services and infrastructure so insights are made accessible to any engineer supporting digital experiences.

“Enterprises that adopt Intelligence have a competitive edge, as they turn to AI for enhanced business decisions based on insights from large data sets, increased productivity, improved customer experiences, faster innovation and cost reduction,” said Stephen Elliot, IDC group vice president, in a press statement.

“Observability provides the lens on digital business, and as such, the ideal place for these intelligent capabilities to live. All businesses will demand observability.”

How Does the Platform Work?

A simple request but notorioulsy complex to get right: @newrelic‘s Jemiah Sius showed during New Relic Now+ 2025 conference how to apply AI to search the entire relevant history of an issue and automate a fix. @heyjemiah pic.twitter.com/vGzsIqXcX4

— BC Gain (@bcamerongain) February 27, 2025

It is hard to find any developer or operations person who does not seek answers with AI with Cursor, Copilot or other ways. New Relic’s observability platform makes use of AI in concrete ways, as New Relic’s Jemiah Sius, senior director of developer relations, showed during a demo at the conference. He demonstrated how New Relic AI can be used to, as he put it, “do all that analysis for me and provide me with this AI summary.”

During the demo, Sius received a page alerting him of an order-transaction issue, where a rewards portal wasn’t working as expected. He showed how — without New Relic Alerts — the user would have to parse through each issue separately when attempting to gain an understanding of the root cause of the problem.

“I take a glance at the chart, dive into the tags, and try to make sure that I understand the scope of impact, praying that I know which part of this environment it affects and figuring out which team I may need to pull in with me,” Sius said. “I would have to do this for every single issue, spending minutes on each one, which leads to a ton of time lost. Now, with Response Intelligence, I don’t have to do any of that.”

During Sius’s demo, New Relic AI helped to provide an analysis and summary of a critical issue affecting users and how it was fixed in a couple of minutes. “I can also see what has happened previously — this has occurred before in October of  2024 — while letting me know ‘Hey, this is a recurring problem,’” Sius said. “So, what would have normally taken me 10 to 15 minutes, I have now been able to do in two minutes.”

How well New Relic’s platform lives up to its ambitious claims remains to be seen, of course, but New Relic — as a legacy observability player already in this emerging sector — has shown more than solid results with its past solutions.

“It’s not enough to capture some telemetry, put it in a database, be able to dashboard it and alert on it because that is just contributing to information overload for users,” Nic Benders, chief technical strategist at New Relic, told The New Stack. “What you have to do is be able to say, ‘I can pull end-to-end: an intelligent data capture that gets the data that you want and does it efficiently.’

“An intelligent data platform pulls everything together, lets you ask questions that you didn’t know that you had before you sat down, gives you powerful query capabilities and an intelligent action platform that says you probably don’t actually know the questions that you need to ask.”