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Found 1,587 Skills
Expert ML engineering covering model development, MLOps, feature engineering, model deployment, and production ML systems.
Expert delivery management covering continuous delivery, release management, deployment coordination, and service operations.
Expert-level ArgoCD GitOps deployment, application management, sync strategies, and production operations
Aspire orchestration for cloud-native distributed applications in any language (C#, Python, Node.js, Go). Handles dependency management, local dev with Docker, Azure deployment, service discovery, and observability dashboards. Use when setting up microservices, containerized apps, or polyglot distributed systems.
This skill should be used when users need to manage progressive delivery via Kargo CLI. It covers freight management, stage promotion, warehouse status, and deployment pipeline operations. Integrates with ArgoCD for GitOps sync. Triggers on requests mentioning Kargo, freight, stage promotion, progressive delivery, or deployment pipelines.
Onnx Converter - Auto-activating skill for ML Deployment. Triggers on: onnx converter, onnx converter Part of the ML Deployment skill category.
Kubernetes and Helm patterns - use for deployment configs, service definitions, ConfigMaps, Secrets, and Helm chart management
Automate your Flutter app releases to beta or production with this handy shell script that handles version bumping, formatting, cleaning, rebuilding, and deployment via Fastlane.
Deployment patterns from Kubernetes to serverless and edge functions. Use when deploying applications, setting up CI/CD, or managing infrastructure. Covers Kubernetes (Helm, ArgoCD), serverless (Vercel, Lambda), edge (Cloudflare Workers, Deno), IaC (Pulumi, OpenTofu, SST), and GitOps patterns.
Analyze AI/ML technical content (papers, articles, blog posts) and extract actionable insights filtered through enterprise AI engineering lens. Use when user provides URL/document for AI/ML content analysis, asks to "review this paper", or mentions technical content in domains like RAG, embeddings, fine-tuning, prompt engineering, LLM deployment.
Open-source workflow automation platform with visual node-based editor, 400+ integrations, webhooks, and self-hosted deployment capabilities
Create and configure Databricks Asset Bundles (DABs) with best practices for multi-environment deployments. Use when working with: (1) Creating new DAB projects, (2) Adding resources (dashboards, pipelines, jobs, alerts), (3) Configuring multi-environment deployments, (4) Setting up permissions, (5) Deploying or running bundle resources