Results for “deployment”

ML pipeline design — data versioning, experiment tracking, deployment patterns, drift monitoring. Use when building an ML pipeline from data to deployment, setting up MLOps tooling (DVC, MLflow, model registry), choosing deployment patterns (shadow, canary, A/B), or designing monitoring for drift and degradation.

Designs and implements CI/CD pipelines with automated testing, build automation, deployment, and rollback strategies.

Configures ArgoCD for GitOps-based Kubernetes deployments, including installation, project and application setup, and Kustomize overlays for multi-environment management.

C4 Container Level: System Deployment

Create and deploy browser automation functions with the Stagehand CLI, from interactive site exploration to production deployment.

Build and manage Convex backends: schema design, TypeScript functions, real-time subscriptions, auth, file storage, scheduling, and deployment.

Performs security scanning, compliance checks, deployment planning, and infrastructure setup, with optional dependency auditing and bundle size analysis.

Orchestrates Python data pipelines with Prefect flows, tasks, retries, caching, parallel execution, and deployments to work pools.

Deploy applications and websites to Vercel. Use this skill when the user requests deployment actions such as "Deploy my app", "Deploy this to production", "Create a preview deployment", "Deploy and give me the link", or "Push this live". No authentication required - returns preview URL and claimable deployment link.

Generate operational runbooks from a service name — deployment, incident response, maintenance, and rollback workflows. Templated structure customizable per environment.

Provides a structured pre-launch checklist, staged rollout plan, monitoring setup, and rollback strategy for safe production deployments.

Discovers available Azure OpenAI model capacity across regions and projects, analyzes quota limits, and recommends optimal deployment locations.

Guides building original LangGraph agents for Warden Protocol, from setup to deployment and publishing in Warden Studio.

Automates Azure OpenAI model deployment by checking capacity across regions and deploying to the best available option.

Guides reliable application deployment with CI/CD pipelines, zero-downtime strategies, rollback plans, and post-deploy monitoring.

Implements gradual traffic shifting, automated canary deployments with metric analysis, rollback automation, and observability dashboards for progressive releases.

Manages env0 infrastructure-as-code environments via the env0 API, covering discovery, deployment, cost tracking, variables, and policies.

MLOps lead for deployment, monitoring, and scaling. Use when the user asks to talk to McGonagall, requests deployment help, or needs CI/CD for AI systems.

Automates CI/CD pipeline setup, quality gates, test runners, and deployment strategies for GitHub Actions.

Generate infrastructure code (Bicep/Terraform), azure.yaml, and Dockerfiles for Azure deployment, with a mandatory planning workflow.

Design schemas, write TypeScript functions, and manage real-time subscriptions, auth, file storage, scheduling, and deployment for Convex backends.

Manages the machine learning lifecycle with experiment tracking, model versioning, reproducible runs, and deployment through the MLflow platform.

Deploy and serve LLMs in production with vLLM, Ollama, TGI, and llama.cpp, including quantization and GPU optimization.

Automates Ansible AWX setup on Kubernetes and provides playbooks for deploying backends, running database migrations, and managing Kubernetes deployments.

Design schemas, write TypeScript functions, and manage real-time data, auth, storage, scheduling, and deployment for Convex backends.

This skill should be used when building token launch tools, implementing Clanker integration, or adding fee claiming functionality. Covers ERC20 deployment, metadata updates, and trading fees.

Plans and coordinates the deployment of a model to Amazon SageMaker AI, selecting the appropriate pathway (real-time, serverless, async, batch, or Bedrock CMI) based on model type, traffic, latency, and cost constraints.

Run pre-deployment validation checks for Azure readiness, including configuration, infrastructure (Bicep or Terraform), RBAC role assignments, and managed identity permissions.

Validates Bicep deployments to Azure before execution, including syntax checks, what-if analysis, and permission verification.

Deploy, manage, and scale applications on Kubernetes clusters using manifests, Helm charts, and autoscaling configurations. Use when the user requests kubernetes deployment or provides relevant inputs for this workflow.

Handles containerization, CI/CD pipelines, and deployment setup.

Configure deployment settings for /land-and-deploy.

Build full-stack Vue applications with Nuxt 4, covering SSR, file-based routing, auto-imports, server routes, and deployment.

Build AI applications using the Azure AI Projects SDK for TypeScript, managing agents, connections, deployments, datasets, indexes, and evaluations.

Diagnose failed or unhealthy Dynamo deployments by collecting a read-only debug bundle, classifying failures, and providing step-by-step remediation guidance.

Design schemas, write TypeScript functions, set up real-time subscriptions, authentication, file storage, scheduling, and deployment for Convex reactive backend projects.