Skill UI

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.

This guide outlines best practices for configuring and securing Adobe API access across Development, Staging, and Production environments. It details the use of separate Developer Console projects, implementing least-privilege OAuth scopes, and integrating robust secret management solutions (GCP Secret Manager, AWS Secrets Manager, HashiCorp Vault) into CI/CD pipelines for secure, scalable deployments.

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.

This skill provides comprehensive guidance for deploying and managing GPU-accelerated AI inference services on CoreWeave Kubernetes (CKS). It covers best practices including containerization using NVIDIA CUDA base images, configuring specific GPU resource limits (A100/H100), setting up robust health checks, and executing controlled rolling updates. Ideal for managing multi-model inference and scaling demanding AI workloads in a cloud environment.

A comprehensive solution for monitoring CoreWeave cluster events and GPU workload status using webhooks. It tracks critical lifecycle events such as pod readiness, job completion, volume attachment, and node health. Essential for building automated scaling, alerting, and recovery pipelines for large-scale GPU-accelerated inference and training workloads.

This skill provides advanced integration for deploying applications on Fly.io, focusing on edge computing architectures. It covers building production-ready Docker images, configuring `fly.toml` for services and health checks, and executing sophisticated deployment strategies like blue-green and canary releases. It ensures reliable, scalable deployment across multiple regions, including automated rollbacks and micro-VM optimization.

A comprehensive guide and toolset for load testing HubSpot integrations and planning for high-volume traffic. This resource details HubSpot's specific API rate limits (per-second and daily) and provides k6 scripts and capacity calculators to ensure your application scales reliably before deployment in production.

This comprehensive skill guides users through the entire Fluid storage extension lifecycle within KubeSphere. It allows for installing, upgrading, and uninstalling the Fluid extension, and managing various data resources. Users can generate YAML manifests for Datasets and specialized runtimes (Alluxio, JuiceFS, Thin), perform data loading/cache warming, scale operations, and troubleshoot issues using both kubectl and KubeSphere APIs.

This skill provides guidelines and mechanics for managing multi-tenant environments within KubeSphere. It focuses on the controlled creation and configuration of core resources—including workspaces, projects, and users—while strictly adhering to least privilege principles. It details the proper use of RBAC roles (Viewer, Regular, Admin) and guides users through the process of setting up organizational boundaries and access controls for secure, scalable deployment.

This advanced skill explores offensive reconnaissance techniques focused on defeating modern operating system security boundaries and mitigations. Topics include kernel/user boundary manipulation, sandbox escapes (AppContainer, LPAC), COM/RPC boundary exploitation, hypervisor interactions, and various integrity level bypassing methods. It is essential for planning advanced privilege escalation paths and understanding deep Windows security architecture, including AMSI, WDAC, and ETW manipulation.

Provides a comprehensive, production-ready deployment solution for OneNote integrations in containerized environments. This skill addresses critical issues like MSAL token persistence (supporting both file and Redis caches), implementing deep health/readiness checks that validate actual Graph API connectivity, and managing graceful shutdowns. Ideal for containerizing OneNote services for robust, scalable production use with Docker and Kubernetes.

This guide provides comprehensive guidance on scaling Qdrant, a vector database. It helps users diagnose performance bottlenecks and determine the optimal horizontal or vertical scaling strategy. Strategies are categorized based on specific needs: increasing data volume, improving query throughput (QPS), minimizing query latency, or managing high query result volumes.