Enables AI assistants to manage and analyze containers across Docker and Podman through natural language, providing unified inspection, monitoring, and diagnostics.
Enables AI agents to query cluster-wide network traffic, investigate API calls, and perform root cause analysis using natural language, with access to decrypted TLS traffic and Kubernetes context.
AI-powered Kubernetes diagnostics that analyzes pod crashes, logs, and cluster health to provide root cause analysis and actionable solutions for common issues like CrashLoopBackOff, OOM kills, and connection errors.
Enables interactive Kubernetes cluster monitoring and troubleshooting through natural language queries. Users can diagnose pod issues, check service status, and investigate cluster problems using conversational AI.
Enables read-only, stack-aware diagnostics for microservices on Kubernetes, turning debugging runbooks into conversational tools that investigate slow requests, changes, leaks, and in-pod conditions without exposing cluster credentials.
Enables AI agents to inspect and manage Linux kernel-level eBPF security policies, including real-time status monitoring, policy retrieval, dynamic rule injection, and pre-execution SQL/syscall validation via natural language.