What are the APM use cases for Artificial Intelligence and Data Analytics?

How AI and Data Analytics Help You Extract Business & Application Intelligence

Traditional dashboards and static snapshots are no longer enough to uncover the complex, interdependent causes of application slowdowns. Today’s IT teams need comprehensive diagnostic data and flexible analytics tools to pivot, filter, and visualize performance from multiple angles.

By applying AI and data analytics to high-volume APM data, you can surface actionable insights faster—proactively resolving issues before they disrupt the business. Intuitive queries, machine learning algorithms, and powerful visualizations put you just a few clicks away from answers to nearly any performance question.

How APM Uses AI and Machine Learning

Modern APM solutions leverage AI and machine learning to go beyond basic monitoring and deliver deep, real-time insight into performance.
With AI-driven APM, IT teams can:

• Analyze with precision: Use high-fidelity metrics and full diagnostic data for accurate root-cause analysis.
• Detect issues automatically: Identify anomalies and trigger alerts before service level agreements (SLAs) are breached.
• Uncover hidden patterns: Apply correlation and clustering to group related transactions, revealing problems that would otherwise remain hidden.

Delivering Business-Relevant Insights with APM

AI-powered, big-data APM enables you to query billions of transactions enriched with user and business context—allowing you to generate reports, compare historical performance, and drill down into issues quickly and easily.

Armed with these insights, DevOps teams can:

• Prioritize high-impact fixes: Identify backend components that affect your most critical transactions—by processing time, volume, or financial value—and focus development where it matters most.
• Accelerate troubleshooting: Use integrated log analysis to search across application logs, pinpoint error sources, and immediately see which users and transactions were impacted.