AI & ML News

New Relic Boosts AIOps with First AI-Recommended Alerts

"We've seen rapid adoption of AIOps among Asia Pacific organisations and a clear mandate for use of automation to manage complexities and derive efficiencies in enterprises."

Engineers use New Relic platform for AI-driven alert recommendations, covering gaps and generating new alerts effortlessly

New Relic  has enhanced its AIOps capabilities with recommended alerts. This provides the ability to quickly detect and easily resolve alert coverage gaps by using AI to identify anomalous behavior, determine areas of the technology stack that aren’t being monitored, and recommend new alerts to engineers. The industry’s only observability solution that reduces the need to manually build numerous alert conditions using AI makes it easier to understand which signals are most important or what thresholds indicate performance problems. 

“In an increasingly dynamic landscape, it’s easy for engineering teams to be overwhelmed by the need to configure alerts across different layers of the technology stack, especially since manually creating alert policies can be time- and resource-intensive. This can cause enormous gaps in the team’s alerting policies, leaving them blind and incapable of responding quickly and confidently when things break,” said New Relic Chief Product Officer Manav Khurana. 

“We’ve seen rapid adoption of AIOps among Asia Pacific organisations and a clear mandate for use of automation to manage complexities and derive efficiencies in enterprises.”

Peter Marelas, Chief Architect, APJ at New Relic

“We’ve seen rapid adoption of AIOps among Asia Pacific organisations and a clear mandate for use of automation to manage complexities and derive efficiencies in enterprises,” said Peter Marelas, Chief Architect, APJ at New Relic. 

 New Relic recommended alerts streamlines alerting with its alert coverage gaps feature, which continuously and automatically highlights areas in an organization’s technology stack that are missing alert coverage across application performance monitoring (APM), mobile and browser entities. Then, New Relic fills alerting gaps by recommending new alerts with pre-populated alert conditions, such as error percentage or response time. 

New Relic recommended alerts builds upon New Relic AI, a suite of AIOps capabilities that understands historical alerts and applies machine learning (ML) and AI to significantly reduce alert noise, enrich incidents with context, and provide intelligence and automation to engineering teams in real-time. 

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