Features

Explore the powerful capabilities of AIK8s Operator, from predictive incident prevention to intelligent auto-remediation.

Time-Series Anomaly Detection

Analyzes metrics, logs, and traces to predict incidents before they occur

Leverages advanced machine learning algorithms to analyze real-time telemetry data, identifying patterns that precede failures. Predicts incidents with high accuracy, giving your team time to prepare and respond.

Pattern Recognition

Learns from incident history to predict similar failures

Builds a knowledge base from past incidents, recognizing recurring failure patterns. Automatically correlates events across your cluster to surface potential issues early.

Capacity Forecasting

Predicts resource needs 6-24 hours ahead

Analyzes resource utilization trends to forecast future demand. Recommends proactive scaling actions to prevent performance degradation and ensure smooth operations.

Change Impact Analysis

Predicts deployment and config changes impact before rollout

Simulates the effects of planned changes across your cluster. Identifies potential risks and affected resources before you deploy, enabling safer rollouts.

Knowledge Graph

Builds dependency graph of all cluster resources

Creates a comprehensive map of relationships between pods, services, deployments, and other resources. Enables intelligent root cause analysis and impact assessment.

Multi-Cluster Support

Unified view and control across all clusters

Manages multiple Kubernetes clusters from a single control plane. Provides consistent policies and observability across development, staging, and production environments.