As software systems become more complex and the demand for quality and reliability increases, DevOps, SRE, and network operation center (NOC) teams can find themselves overwhelmed by a constant flood of information. Between noisy alerts, signals distributed among multiple tools, and thousands of “unknown unknowns,” it’s difficult to quickly determine and address the root cause of incidents, let alone detect and respond to issues proactively. Troubleshooting and incident resolution efforts are further complicated by an influx of alerts from multiple tools that can create distractions and response fatigue for your team.

We’ve seen these problems and know the struggle of maintaining complex, large-scale systems. That’s why we’re excited to introduce New Relic AI, an AIOps solution for busy DevOps, SRE, and on-call teams that helps you find, troubleshoot, and resolve problems faster. New Relic AI is built to empower your team to get out of reactive “fire-fighting” mode and back into the creative, challenging, exciting work of building great software.

Fast to connect, faster to value: meeting you in the tools you already use

If your DevOps, SRE, or on-call team is tasked with maintaining complex infrastructure, you may rely on a multitude of tools to detect and respond to incidents. There are great tools to observe systems across your full technology stack; tools to notify you when incidents occur; tools to track the status of in-progress and follow-up actions; and tools to communicate with other team members. For on-call teams that are under pressure to reduce mean time to resolution (MTTR), this ever-growing list of tools can pose problems: incident, event, and telemetry data is fragmented, siloed, or redundant, making it harder to find the information needed to diagnose and resolve incidents.

AIOps platforms promise to solve these problems with a centralized, intelligent feed of incident information that displays everything you need to troubleshoot and respond to problems, all behind a single pane of glass. Unlocking this value, though, can require a significant time commitment and workflow shift, potentially costing your team hundreds of hours in integration, configuration, training, and on-boarding tasks.

The New Relic AI approach is radically different. It combines the value of an intelligent system with minimal configuration requirements. We integrate with PagerDuty accounts, New Relic Alerts violations, and other data sources via our REST API. New Relic AI works out of the box and learns over time, automatically correlating, aggregating, and prioritizing your incident data. This streamlined, enhanced information is available right in your team’s PagerDuty account, eliminating noise and driving faster issue resolution.

We’ve also gone a step further by leveraging the notification and collaboration tools you already use. New Relic AI delivers critical insights to your Slack channels, including intelligent incident context and automatic anomaly detection. Crucial information about your production system is now accessible at your fingertips, with no need to change your on-call workflow.

More intelligence throughout the entire DevOps cycle

Rather than narrowing our approach to one specific aspect of the incident response process, we strengthen the relationships between each stage of the process to create a more powerful solution. Focusing only on faster detection, faster understanding, faster response, or faster follow-up is not enough; you need a tool that thinks like your best SREs—from a systems perspective.

Actionable detection

The first step of the incident response process is detecting problems. As New Relic users, your team already has the ability to configure monitors for your existing data. Now, New Relic AI enhances the detection process, automatically surfacing anomalies across multiple tools in your stack and suggesting actions to monitor similar conditions in the future. Best of all, New Relic AI can deliver anomaly information to you via Slack, enabling you to quickly and collaboratively assess potential problems.

New Relic AI enables seamless integration with existing collaboration tools.

Noise reduction

On-call teams are familiar with noisy alerts triggered by low-priority, irrelevant, or flapping issues. These can lead to pager fatigue, cause distractions, and increase the probability that a critical signal will go unnoticed. New Relic AI uses a baseline of industry-standard knowledge, and then learns from your data and your team’s feedback to intelligently suppress alerts you don’t care about and correlate related incidents. The result? Our initial private beta customers have reported that they have seen automatic reductions of noise in excess of 80%, along with more streamlined and more useful alerts.

New Relic AI uses baseline industry knowledge to reduce noise from irrelevant alerts.

Intelligent assistance

Once a tool in your stack identifies a problem and pages your team, the investigation and troubleshooting process begins! Understanding the root cause and determining steps to resolution usually account for the majority of the time between an issue occurring and its remediation. New Relic AI accelerates this process by giving you useful context about your existing issues, including their classification based on the “Four Golden Signals” (latency, traffic, errors, and saturation) and correlated issues from across your environment.

New Relic AI gives you the context required to classify and resolve open issues.

Continuous Improvement

Just like a new team member, New Relic AI gets smarter and builds system-specific knowledge about your team’s infrastructure as it studies your data. Your team can provide feedback about the quality of issue correlations and automatically surfaced information, helping the system to adjust and deliver even more focused, relevant insights over time.

Smarter tools for more perfect software

New Relic’s mission is to instrument, measure, and improve the internet to help our customers create more perfect software, experiences, and businesses. In order to do this, we believe it’s critical to embrace solutions that are easy to connect and configure, work with the tools teams already use, create value throughout the entire observability process, and learn from data patterns and user feedback to get smarter over time. New Relic AI is one more step in this journey. It’s already making a difference for busy DevOps and SRE teams, and we’re excited to see the value it can bring to your teams, too.

New Relic AI is currently in private beta. To follow the latest product updates, or if you are interested in participating in the beta program, tell us a bit more about yourself here.


This post contains “forward-looking” statements, as that term is defined under the federal securities laws, including but not limited to statements regarding the timing, benefits and availability of New Relic AI and the potential value and solutions that New Relic AI can bring to customers. The achievement or success of the matters covered by such forward-looking statements are based on New Relic’s current assumptions, expectations, and beliefs and are subject to substantial risks, uncertainties, assumptions, and changes in circumstances that may cause New Relic’s actual results, performance, or achievements to differ materially from those expressed or implied in any forward-looking statement. Further information on factors that could affect New Relic’s financial and other results and the forward-looking statements in this post is included in the filings New Relic makes with the SEC from time to time, including in New Relic’s most recent Form 10-Q, particularly under the captions “Risk Factors” and “Management’s Discussion and Analysis of Financial Condition and Results of Operations.” Copies of these documents may be obtained by visiting New Relic’s Investor Relations website at or the SEC’s website at New Relic assumes no obligation and does not intend to update these forward-looking statements, except as required by law.

Guy Fighel is the General Manager of applied intelligence and Vice President of product engineering at New Relic. He leads New Relic’s AIOps product and engineering, and is responsible for the company’s overall artificial intelligence and machine learning strategy. Guy was the co-founder and chief technology officer of SignifAI, an event-intelligence company, which was acquired by New Relic in 2019. View posts by .

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