Skill UI

This guide sets up a robust local development loop for integrated Kubernetes infrastructure using CAST AI. It allows developers to test autoscaler policies, validate Terraform modules, and measure potential cloud cost savings in a dev environment before deploying to production. This is essential for building cost-aware and efficient CI/CD pipelines.

A comprehensive reference architecture guide for deploying and managing CAST AI across multiple Kubernetes clusters (Dev, Staging, Prod). It details best practices for infrastructure provisioning using Terraform, focusing heavily on cost optimization techniques such as autoscaling, spot instance management, and environment-specific resource policies. Ideal for setting up team standards and ensuring reliable, cost-effective deployments.

Integrates CAST AI cost validation into CI/CD pipelines (GitHub Actions, Terraform). This skill automatically enforces cost governance by checking minimum savings thresholds, validating Terraform plans to prevent destructive changes, and ensuring agent health status before deployment, guaranteeing cost-aware and safe deployments.

This workflow guides users through configuring CAST AI's autoscaler policies to achieve optimal cost management and resource utilization within a Kubernetes cluster. It covers enabling spot instances, setting node downscaler/evictor rules, defining cluster limits, and creating specialized node templates (e.g., for GPU or spot workers) using Terraform. Use this when implementing Phase 2 automation or optimizing cloud spend.

This skill provides a comprehensive guide to setting up robust CI/CD pipelines for Oracle Cloud Infrastructure (OCI). It leverages GitHub Actions and Terraform to automate the deployment, planning, and testing of OCI resources. Instructions cover secure API key authentication, best practices for managing Terraform state, and crucial workarounds for known OCI provider bugs, ensuring stable and reliable cloud deployments.

Provides a comprehensive, production-ready standard 3-tier reference architecture for Oracle Cloud Infrastructure (OCI). The design covers essential components like VCN, public/private subnets, Internet Gateway, NAT Gateway, Service Gateway, and Autonomous Database. It includes deployment steps using Terraform and OCI SDK Python code, making it ideal for designing new cloud environments or migrating existing patterns from other major cloud providers.

This skill provides a comprehensive guide for safely upgrading the Oracle Cloud Infrastructure (OCI) Python SDK and Terraform provider. It addresses known breaking changes, schema modifications, and version incompatibility issues common in OCI tools. By implementing version pinning, pre-upgrade testing, and structured rollback procedures, users can ensure a stable and reliable migration process for both code and infrastructure definitions.

This advanced skill automates the entire lifecycle of cloud infrastructure deployment. Instead of manual documentation review, it researches current best practices across multi-cloud platforms (AWS, GCP, Azure), synthesizes a coherent deployment strategy, and generates production-grade Infrastructure as Code (IaC). It outputs comprehensive artifacts, including Terraform modules, Kubernetes manifests, CI/CD pipelines, monitoring setups, and cost estimates, ensuring secure and optimized deployment.

This comprehensive guide demonstrates how to establish a robust Continuous Integration/Continuous Deployment (CI/CD) pipeline for Snowflake data warehousing. It integrates SchemaChange for managing version-controlled database migrations, GitHub Actions for automated testing and deployment triggering, and Terraform for provisioning and managing underlying Snowflake infrastructure (databases, warehouses, roles). Use this when setting up reliable, repeatable, and automated deployment workflows.

A comprehensive skill to automatically detect, install, and initialize the Terraform CLI based on the operating system. It ensures the required environment is set up (including handling provider downloads and network mirrors) and prepares the working directory for infrastructure deployment. Ideal for initial setup or when receiving 'command not found' errors.

A comprehensive guide for designing and implementing robust Infrastructure as Code (IaC) using Terraform or OpenTofu. Covers module hierarchy design, best practices for naming conventions, structuring multi-environment pipelines, advanced testing strategies (native tests, Terratest, static analysis), and integrating security scanning (trivy, checkov) into CI/CD workflows.

This automated workflow performs a comprehensive review against the AWS Well-Architected Framework (WAF). It scans IaC definitions (Terraform, CloudFormation, CDK) and deployed resources to identify compliance gaps, security risks, and optimization opportunities across six core pillars. Findings are structured and automatically generated as actionable GitHub issues with remediation code examples.