Skill UI

A comprehensive guide for establishing robust, enterprise-grade access control within Databricks. Covers implementing Single Sign-On (SSO) via SCIM, leveraging Unity Catalog for fine-grained Role-Based Access Control (RBAC), defining cluster policies, and enforcing data governance measures like Row-Level Security (RLS) and column masking. Essential for large-scale, secure data platforms.

This utility provides comprehensive security auditing for Kubernetes Role-Based Access Control (RBAC) configurations. It identifies overly permissive roles, dangerous wildcard permissions (*), critical ClusterRoleBindings, and potential privilege escalation paths. By integrating tools like rbac-tool, KubiScan, and Kubeaudit, it helps users enforce the principle of least privilege, crucial for compliance and security assessments on EKS, GKE, and AKS clusters.

This guide provides a comprehensive deep dive into implementing advanced network segmentation and zero-trust security controls within Kubernetes clusters using Calico. It covers standard Kubernetes NetworkPolicy, utilizing Calico's GlobalNetworkPolicy, and defining security Tiers, ensuring fine-grained, least-privilege communication between pods, and establishing robust security architectures for compliance.

This guide details how to use Kubernetes NetworkPolicies to enforce granular, pod-level network segmentation. It covers establishing default deny rules, defining specific ingress and egress rules for services, and implementing zero-trust microsegmentation. Use this skill to build robust security architecture and prevent lateral movement within a container cluster.

OPA Gatekeeper is a powerful Kubernetes admission controller that enforces policies using Rego rules. It utilizes ConstraintTemplates and Constraints to validate, mutate, or deny API requests at the cluster admission stage. This tool is essential for implementing policy-as-code practices, ensuring that Kubernetes deployments adhere to organizational security standards, compliance requirements, and best practices, such as mandating labels or blocking privileged containers.

A comprehensive security auditing tool designed to assess a Kubernetes cluster's compliance posture against established CIS benchmarks. It performs deep checks on control plane components (API Server, etcd, Controller Manager), worker nodes, and Role-Based Access Control (RBAC). Use it for proactive security assessments, compliance validation, and hardening throughout the CI/CD lifecycle.

This guide provides a comprehensive methodology for assessing the security posture of Kubernetes etcd clusters. It covers critical areas including encryption at rest (for secrets), TLS transport security, access control validation, secure backup procedures, and network isolation checks, ensuring cluster data integrity and confidentiality.

A comprehensive guide for systematically evaluating Kubernetes cluster security. It simulates advanced attacker techniques against critical components like the API server, etcd, kubelet, RBAC, and network policies, identifying misconfigurations and vulnerabilities. Essential for security auditors, penetration testers, and DevOps teams performing deep cluster security assessments.

This skill provides a comprehensive guide to hardening managed Kubernetes clusters on major cloud platforms (EKS, AKS, GKE). It details implementing critical security layers, including Pod Security Standards, least-privilege network policies, workload identity (eliminating static cloud credentials), and runtime security monitoring. Essential for securing production environments and meeting compliance requirements.

This guide details securing the CAST AI integration across multiple layers. It covers best practices for API key management (including rotation and secrets storage), implementing least-privilege RBAC using 'kubectl', deploying the Kvisor security agent for runtime scanning, and setting up Kubernetes Network Policies to restrict egress traffic. Use this when hardening production clusters or performing security audits.

A comprehensive guide to connecting any Kubernetes cluster (EKS, GKE, AKS) to CAST AI for cost optimization, autoscaling, and security monitoring. This skill covers the entire setup process, including generating API keys, installing the CAST AI agent via Helm charts, and integrating the provider using Terraform.

A comprehensive, multi-phase checklist for deploying and validating CAST AI cost optimization and autoscaling features on a production Kubernetes cluster. It guides users through prerequisites, initial monitoring setup (Phase 1), full autoscaling enablement (Phase 2), security hardening (RBAC, secrets), and critical validation commands for safe go-live deployment.