New Relic Expands AIops Services - Latest News

New Relic Enhances AI-Powered Incident Response Capabilities

Recently, New Relic, a publicly traded observability service, has been integrating more machine learning tools into its platform to assist with AI-driven incident response. The company is now expanding these features with the introduction of its “New Relic Applied Intelligence Service” enhancements.

New Features and Capabilities

This expansion encompasses an anomaly detection service, now accessible even to free users. Furthermore, the platform can now consolidate alerts originating from various tools, intelligently identifying them as stemming from a single underlying issue. New ML-based root cause analysis is also included, designed to minimize uncertainty during problem resolution.

A new capability, currently in public beta, allows New Relic to identify patterns and anomalies within log data stored on its data platform.

According to Michael Olson, New Relic’s director of product marketing, the primary goal is to enable organizations of all sizes to benefit from AI-enhanced operational practices.

“We introduced our initial AIops capabilities with New Relic Applied Intelligence approximately a year ago,” Olson stated. “Adoption has grown significantly. However, we’ve learned that organizations hesitant to adopt AIops often cite challenges like steep learning curves, lengthy implementation processes, and a lack of confidence in AI and machine learning.”

Real-Time Problem Detection and Alert Grouping

The updated platform is designed to detect emerging issues in real-time, eliminating the need for pre-configured alerts. Upon detection, it intelligently groups alerts from New Relic and other integrated tools, reducing alert fatigue and allowing engineers to concentrate on resolving the incident.

“Engineers will receive a single, actionable issue instead of a flood of alerts when a problem impacts multiple tools,” Olson explained. “Alerts are automatically grouped based on timing, frequency, and contextual information found within the alert messages. We can now also analyze relationship data across systems to intelligently correlate and group alerts.”

AI-Assisted Root Cause Analysis

A key improvement for operations teams is New Relic’s ability to identify the likely root cause of problems. Guy Fighel, general manager of applied intelligence and vice president of product engineering at New Relic, emphasized that the intention is to augment, not replace, human expertise.

“We aim to provide a transparent experience, allowing teams to leverage their own knowledge to refine decisions and correlations within the system,” Fighel explained. “This allows for customization based on specific environments and needs. Because of the extensive data from various tools flowing into New Relic One, our probable root cause analysis is highly accurate. However, it remains a probable cause; we will never definitively instruct users to fix an issue without acknowledging the possibility of error.”

The AI system actively solicits user feedback, continuously refining the model with each new incident.

Fighel noted that New Relic’s tools utilize a combination of statistical analysis methods and machine learning models, some tailored to individual users and others applied across the entire user base. He also highlighted the team’s strong background in site reliability engineering, ensuring a deep understanding of the challenges in this domain.

Enhanced Integrations and Data Agnosticism

New Relic is also introducing a new integration with PagerDuty and other incident management tools, enabling bidirectional synchronization of issue status.

“Our goal is to integrate seamlessly with our customers’ existing workflows and remain data source agnostic, allowing them to ingest data from any source,” Olson said. “We can then enrich that data, reduce noise, and ultimately help our customers resolve problems more quickly.”

Image Credits: New Relic

Image Credits: New Relic

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