Strengthen Kubernetes security with context-aware runtime anomaly detection. Reduce false positives and enhance protection with advanced profiling.

Armo provides a cloud security platform, focusing on Kubernetes security through its open-source tool, Kubescape. The platform offers runtime-driven security posture management, behavioral-based cloud detection and response, and runtime-based vulnerability management.

Armo

Runtime anomaly detection in Kubernetes enhances security by using context-aware profiling to create detailed application behavior profiles with eBPF technology. This approach minimizes false positives by learning normal behavior patterns and detecting deviations. Integrated seamlessly into existing DevOps workflows through GitOps practices, it improves security with minimal setup and supports flexible alert integration.

Runtime Anomaly Detection in Kubernetes

The challenge of traditional runtime detection

A new approach to runtime anomaly detection

Key benefits of context-aware runtime detection

Practical implementation in Kubernetes environments

How ARMO does modern cloud runtime threat detection