convex-self-hosting
Guides self-hosted Convex deployment, authentication setup, environment configuration, troubleshooting, and production deployment considerations.
Guides self-hosted Convex deployment, authentication setup, environment configuration, troubleshooting, and production deployment considerations.
Use when "deploying ML models", "MLOps", "model serving", "feature stores", "model monitoring", or asking about "PyTorch deployment", "TensorFlow production", "RAG systems", "LLM integration", "ML infrastructure"
Google Cloud Platform configuration templates for BigQuery ML and Vertex AI training with authentication setup, GPU/TPU configs, and cost estimation tools. Use when setting up GCP ML training, configuring BigQuery ML models, deploying Vertex AI training jobs, estimating GCP costs, configuring cloud authentication, selecting GPUs/TPUs for training, or when user mentions BigQuery ML, Vertex AI, GCP training, cloud ML setup, TPU training, or Google Cloud costs.
Amazon SageMaker for building, training, and deploying machine learning models. Use for SageMaker AI endpoints, model training, inference, MLOps, and AWS machine learning services.
Expert MLOps engineering covering model deployment, ML pipelines, model monitoring, feature stores, and infrastructure automation.
Enterprise Vercel Edge Platform with AI-powered deployment, Context7 integration
Oracle Cloud Infrastructure expertise for enterprise AI and cloud architecture
Deploy GPU workloads to RunPod serverless and pods - vLLM endpoints, A100/H100 setup, scale-to-zero, cost optimization. Use when: deploy to RunPod, GPU serverless, vLLM endpoint, scale to zero, A100 deployment, H100 setup, serverless handler, GPU cost optimization.
Create and edit Smithy IDL models for defining service APIs. Use when Claude needs to write Smithy code (.smithy files) for service definitions, operations, resources, data structures, or API modeling. Also use when converting APIs from URLs (OpenAPI, Swagger, GraphQL, HTML docs, JSON Schema, Protobuf) to Smithy. Triggers include requests for API definitions, service models, interface definitions, AWS-style APIs, API conversions, or any mention of Smithy IDL.
Validate and debug Vercel AI SDK provider configurations including API keys, environment setup, model compatibility, and rate limiting. Use when encountering provider errors, authentication failures, API key issues, missing environment variables, model compatibility problems, rate limiting errors, or when user mentions provider setup, configuration debugging, or SDK connection issues.
Provision, manage, and terminate RunPod GPU instances for LLM training. Use when user says "spin up GPU", "create RunPod instance", "terminate pod", "check GPU status", "provision training server", or needs cloud GPU resources.
Ultimate 25+ years expert-level backend skill covering FastAPI, Express, Node.js, Next.js with TypeScript. Includes ALL databases (PostgreSQL, MongoDB, Redis, Elasticsearch), ALL features (REST, GraphQL, WebSockets, gRPC, Message Queues), comprehensive security hardening (XSS, CSRF, SQL injection, authentication, authorization, rate limiting), complete performance optimization (caching, database tuning, load balancing), ALL deployment strategies (Docker, Kubernetes, CI/CD), advanced patterns (microservices, event-driven, saga, CQRS), ALL use cases (e-commerce, SaaS, real-time, high-traffic), complete testing (unit, integration, E2E, load, security). Route protection, middleware, authentication implementation in PERFECTION. Use for ANY backend system requiring enterprise-grade security, performance, scalability, and architectural excellence.
Provides backend architecture and scaling guidance; use when the project targets server-side APIs or infrastructure design decisions.
Architecture patterns and strategies for multi-cloud deployments to avoid vendor lock-in.
FastAPI and AWS SAM/Lambda patterns for building production-ready REST APIs. Use when creating API endpoints, implementing serverless functions (Lambda), configuring API Gateway, designing REST APIs, adding error handling, writing API tests, or working with OpenAPI specifications. Includes Pydantic models, CloudWatch logging, and pytest patterns.
Vercel CLI expert for serverless deployment. Use when users need to deploy apps, manage domains, env vars, or Vercel projects.
Serverless deployment patterns for Node.js. Use when deploying to serverless platforms.
Build production-quality Terraform infrastructure code following established style guides and best practices. Use when creating new Terraform code, setting up Terraform projects, modules, or when user mentions building/creating infrastructure, terraform, HCL, terraform modules, or .tf files. Also use when reviewing or validating existing Terraform code against standards. Applies organizational standards using progressive disclosure - loads detailed references only as needed.
Develop code using Shipbox sandboxes with real Cloudflare containers. Use when the user wants to run code in a sandbox, test in isolation, or deploy workers.
Deploys and hosts full-stack web applications on AWS Amplify with SSR support, CI/CD, and backend services. Use when deploying Next.js apps to AWS, setting up Amplify hosting, or configuring Amplify backends.
Vercel deployment using Vercel CLI for Next.js, React, Vue, static sites, and serverless functions. Includes project validation, deployment orchestration, environment management, domain configuration, and analytics integration. Use when deploying frontend applications, static sites, or serverless APIs, or when user mentions Vercel, Next.js deployment, serverless functions, or edge network.