Skill UI

A comprehensive checklist for deploying large-scale, production-ready GPU workloads on Vast.ai. It covers critical lifecycle stages including account authentication, instance validation, data encryption, persistent checkpointing strategies, fault tolerance for spot instances, robust monitoring (utilization & cost), and strict cost controls, ensuring reliable and stable ML/AI deployments.

This guide details the production-grade reference architecture for running complex GPU compute workflows on Vast.ai. It covers the foundational three-tier pattern—Orchestrator, GPU Workers, and Artifact Storage—providing blueprints for job queue management, fault-tolerant training pipelines, and robust checkpointing. Use this when designing scalable and reliable ML/AI training systems.

This comprehensive guide outlines security best practices for utilizing Vast.ai's cloud environment. It covers secure API key management, hardening SSH access to GPU instances, implementing proper data cleanup before instance destruction, and adhering to robust network security protocols. Use this when setting up, auditing, or deploying sensitive AI/ML workloads on shared cloud hardware.

Configure Vercel's advanced role-based access control (RBAC) for enterprise environments. This guide covers setting up granular team roles, managing project-level access groups, integrating SAML SSO for secure authentication, and enabling detailed audit logging. Use this when implementing strict security protocols and enforcing the principle of least privilege across your team's deployments and resources.

This comprehensive guide details the process of migrating applications to Vercel from various platforms, including Netlify, AWS, and Cloudflare. It covers critical steps such as configuration mapping (e.g., netlify.toml to vercel.json), migrating serverless functions, setting up environment variables, implementing DNS cutovers, and validating feature parity using advanced techniques like the Strangler Fig pattern, ensuring a smooth and reliable transition.

Automates Vertex AI deployment tasks, offering step-by-step guidance, production-ready code, and validation for model serving, MLOps pipelines, monitoring, and optimization when you mention Vertex AI Deployer.

Specializes in provisioning Vertex AI infrastructure with Terraform, covering Model Garden, Gemini endpoints, vector search indexes, ML pipelines, and enterprise-grade production deployments.

Automates wandb experiment logger tasks within ML training, providing guidance, best practices, and code or configuration examples plus validation to keep data prep, training, hyperparameter tuning, and experiment tracking consistent.

Creates complex claude.ai HTML artifacts by initializing a ready React+TypeScript Vite project, leveraging Tailwind and shadcn/ui components, and bundling everything into a single inline HTML file for sharing in conversations.

This skill provides AI-assisted capabilities for creating and managing Continuous Integration/Continuous Deployment (CI/CD) workflows using GitHub Actions. It can generate new workflows from project requirements, optimize existing pipelines, debug failures, and implement industry-standard security best practices, streamlining the entire development and deployment process.

This guide details how to configure Windsurf for professional enterprise deployment, covering critical security and governance features. Key areas include setting up SSO/SAML authentication, defining role-based permissions (Owner, Admin, Member), establishing organization-wide AI policies and data controls, managing user seats, and implementing comprehensive audit trails for compliance.

This skill integrates advanced AI assistance into Git workflows within the Windsurf IDE. It automates complex source control tasks, including generating descriptive commit messages from staged changes, suggesting optimal branch names, assisting with merge conflict resolution, and streamlining common Git operations. Ideal for developers managing version control or needing robust support for collaborative coding environments.