AI-powered observability platform that provides intelligent monitoring, anomaly detection, and automated root cause analysis for applications and infrastructure
New Relic AI transforms application performance monitoring and observability through advanced artificial intelligence and machine learning capabilities. Unlike traditional monitoring tools that rely on static thresholds and manual configuration, New Relic AI automatically detects anomalies, predicts performance issues, and provides intelligent insights across applications, infrastructure, and user experiences. The platform excels at correlating data across distributed systems to identify root causes of performance problems and provide actionable remediation suggestions. New Relic's AI engine analyzes billions of data points from applications, servers, containers, and user interactions to build dynamic baselines and detect deviations that indicate potential issues. The platform provides proactive alerting that reduces noise while ensuring critical issues are identified before they impact users. What sets New Relic AI apart is its ability to understand application dependencies and business impact, prioritizing alerts based on actual customer experience rather than just technical metrics. The AI continuously learns from system behavior and user feedback to improve accuracy and reduce false positives over time. Trusted by leading technology companies including GitHub, Airbnb, and Disney, New Relic has proven its effectiveness in helping development and operations teams maintain high-performing applications while reducing mean time to resolution. The platform's comprehensive observability approach combines application performance monitoring, infrastructure monitoring, and digital experience monitoring in a unified interface powered by intelligent automation.
AI-powered alerting that reduces noise while ensuring critical issues are detected and prioritized appropriately
Use Case:
Perfect for DevOps teams overwhelmed by monitoring alerts who need to focus on issues that matter
Machine learning analysis that automatically identifies the source of performance problems across complex systems
Use Case:
Essential for troubleshooting distributed applications and reducing mean time to resolution
Predictive analytics that identify potential performance problems before they impact users
Use Case:
Critical for maintaining high availability and preventing customer-facing incidents
AI-powered establishment of normal behavior patterns that automatically adapt to application changes
Use Case:
Ideal for applications with variable traffic patterns or frequent deployments
Pricing information is available on the official website.
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