Skill UI

A comprehensive guide for configuring ArgoCD within KubeSphere DevOps. It details implementing GitOps continuous deployment, covering application management, multi-cluster setup, SSO integration via Dex, and best practices for managing application state synchronization from Git repositories. Learn the differences between direct ArgoCD and KubeSphere's tenant-friendly GitOps application creation.

Latch is a robust Python framework designed for building, deploying, and managing complex, scalable bioinformatics workflows as serverless pipelines. It supports integrating multiple analysis tools (like Nextflow/Snakemake) and handles cloud data management (LatchFile/LatchDir) and detailed resource configuration (GPU, CPU, memory). Ideal for running large-scale analyses such as RNA-seq, AlphaFold, and single-cell analysis in a reproducible, production-ready environment.

This guide provides comprehensive instructions for setting up monitoring and observability for Qdrant deployments. It helps users track critical performance metrics, check system health, and diagnose complex production issues such as memory growth or slow query requests. Use cases include setting up Prometheus, Grafana, and implementing robust health checks.

A comprehensive guide to setting up a full-cycle local Web3 development workflow. This skill utilizes Alchemy as the RPC provider, Hardhat for local unit testing, and integrates Mainnet forking and Sepolia testnet deployment. It covers initializing the project, configuring smart contract interactions, and implementing advanced testing patterns.

A comprehensive guide to setting up robust CI/CD pipelines for Algolia indexing. This includes running unit and integration tests against live indices, validating index settings against defined configurations, and implementing automated reindexing upon deployment (e.g., triggering on version tags). It ensures the stability and data consistency of your search service.

This guide provides comprehensive strategies to significantly reduce spending on the Anthropic Claude API. Key techniques include model routing (selecting the most cost-effective model for the task), prompt caching for repeated prompts, using Message Batches for asynchronous tasks, and implementing real-time spend tracking and budget alerts. Essential for managing large-scale, high-cost AI deployments and optimizing cloud LLM expenditures.

A comprehensive guide for configuring and managing Claude API access across disparate environments (Development, Staging, Production). This skill details how to implement isolated API keys, model selection strategies, and crucial spend controls using Anthropic Workspaces, ensuring secure and reliable deployment pipelines for AI applications.

Configure robust CI/CD pipelines for Apify Actor builds and deployments using GitHub Actions. This guide covers setting up unit tests on pull requests, running deep integration tests against the live Apify API, and automating the production deployment process upon merge. Ideal for maintaining reliable, high-quality scraping and automation projects.

A comprehensive guide detailing how to securely configure and manage Canva Connect API integrations across development, staging, and production environments. This resource covers environment strategy, best practices for OAuth credential management, secret handling (AWS, GCP, Vault), and implementing environment isolation guards to ensure secure and scalable deployments.

Provides a comprehensive checklist for deploying Canva Connect API integrations to a production environment. It covers critical aspects like OAuth configuration, robust security measures (e.g., JWK signature verification, least privilege), rate limit handling, error response management, and final production readiness verification, ensuring a smooth and secure launch.

Automate the deployment of CAST AI across various multi-cloud Kubernetes clusters, including EKS, GKE, and AKS. This module uses Terraform Infrastructure as Code (IaC) patterns to reliably configure necessary components like IAM roles, node autoscaling policies, and cluster resources, ensuring standardized onboarding across different cloud environments.

A comprehensive guide for developers on upgrading the Anthropic SDK versions and migrating between different Claude model generations. It covers best practices for version checking, reviewing breaking changes, updating model IDs across the codebase, running output comparison tests, and implementing gradual rollouts using environment variables to ensure stable deployment.