Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Remember when we thought the application layer was where all the fun happened? Firewalls, WAFs, EDR, dashboards galore — the entire security industrial complex built around watching what apps do. Well, with “agentic AI” running the show, that middle ground is turning into a bypass lane. Instead of clicking through UIs or APIs, your AI buddy is making direct system calls, automating workflows at the OS and hardware level.

As IT environments become more complex, organizations face rising threat volumes, persistent cybersecurity talent shortages, and adversaries capable of dwelling undetected for days and moving laterally within hours. In this context, choosing between SIEM and XDR is no longer a technical preference; it’s a strategic decision that shapes how your organization defends itself.

Imagine security data and analytics like a carnival’s hall of mirrors. From convex mirrors that show you a shorter, squatter version of something to the concave mirrors that show a highly magnified image, you see the same object in multiple ways. Every view gives you a different insight and provides a unique vantage point. Online Analytical Processing (OLAP) systems are different mirrors that allow security teams to create focused analytics models for different insights about your security posture.

In today’s modern SOC, more data doesn’t always mean better outcomes. Security teams are overwhelmed by irrelevant telemetry, storage bills are out of control, and compliance regulations demand long-term retention—even for data with little threat value. Legacy SIEMs treat all logs the same, flooding analysts with noise and slowing down response times. The result? Bloated infrastructure, delayed investigations, and boardroom frustration over unproven ROI.

Learn to create custom detection rules in Elastic Security following real detection use cases. This blog will guide you through creating custom detection rules in Elastic Security, equipping you with best practices for using Elasticsearch Query Language (ES|QL) and Elastic AI Assistant to refine threat detection logic and add crucial context for analysts. You’ll learn how to effectively preview, test, and enhance your rules, ultimately strengthening your security operations.