New Relic provides performance management products, mainly application performance management (APM) and digital performance management. The company is evolving its current performance management platforms to include applied intelligence and machine learning that conducts predictive analytics, sends red flags to IT personnel, and advises how to resolve a performance issue.
Performance management describes the processes and tools to identify and resolve issues that affect a network’s or application’s performance. It’s important for companies to monitor their systems closely and to inspect data to prevent network malfunctions and outages that prevent users from accessing the company’s services. The common tools to gather and analyze data include application performance management (APM), network performance management (NPM), and unified performance management (UPM).
Applied Intelligence and New Relic Performance Management
New Relic added the applied intelligence piece into its performance management solution. The company notably shies away from labeling the product as artificial intelligence. Instead, it reinforces it as applied intelligence. The technology also uses machine learning algorithms to detect performance issues. The company states that it’s “taking the massive corpus of data we help you collect from your systems, and running smart algorithms and advanced math at scale to derive insights about things that are different than your normal.”
- Radar: A feed that lists four types of cards to help with monitoring tasks. It provides details on events, successes, advice, and perspective. Each card features the root cause analysis. The cards integrate both with Slack and with Amazon Web Services (AWS).
- Baseline Alerts: IT administrators set up custom alerts for network thresholds they want to monitor. The notification results are based on historical data, applied intelligence, and anomaly detection from Radar.
- APM Error Profiles: The intent of APM Error Profiles is for applied intelligence to automatically create distinct profiles presenting statistics for each error instance so IT admins may compare and detect patterns that identify the root cause quickly.