「ai deployment」の検索結果

Expert knowledge for Azure App Service development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring App Service plans/slots, VNet integration, managed identity/Key Vault, CI/CD deployments, or diagnostics, and other Azure App Service related development tasks. Not for Azure Functions (use azure-functions), Azure Static Web Apps (use azure-static-web-apps), Azure Spring Apps (use azure-spring-apps), Azure Container Apps (use azure-container-apps).

日本語の概要は準備中です。原文の説明を表示しています。

Expert knowledge for Azure Kubernetes Service Edge Essentials development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when managing AKS Edge/Hybrid with Arc, GitOps, IoT/OPC/ONVIF, TPM/Key Vault secrets, or AI model workloads, and other Azure Kubernetes Service Edge Essentials related development tasks. Not for Azure Kubernetes Service (AKS) (use azure-kubernetes-service), Azure IoT Edge (use azure-iot-edge), Azure Stack Edge (use azure-stack-edge), Azure Container Apps (use azure-container-apps).

日本語の概要は準備中です。原文の説明を表示しています。

Expert knowledge for Azure AI Search development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building indexes, skillsets, indexers, vector/semantic search, or RAG knowledge bases with Azure AI Search, and other Azure AI Search related development tasks. Not for Azure Data Explorer (use azure-data-explorer), Azure Synapse Analytics (use azure-synapse-analytics), Azure Cosmos DB (use azure-cosmos-db).

日本語の概要は準備中です。原文の説明を表示しています。

CI/CD pipeline design methodology, deployment strategies, GitHub Actions patterns, and branch/release strategies. Load when designing pipelines or deployment workflows.

日本語の概要は準備中です。原文の説明を表示しています。

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.

日本語の概要は準備中です。原文の説明を表示しています。

Implementing multi-layer security scanning (container, SAST, DAST, SCA, secrets), SBOM generation, and risk-based vulnerability prioritization in CI/CD pipelines. Use when building DevSecOps workflows, ensuring compliance, or establishing security gates for container deployments.

日本語の概要は準備中です。原文の説明を表示しています。

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.

日本語の概要は準備中です。原文の説明を表示しています。

Machine learning development patterns, model training, evaluation, and deployment. Use when building ML pipelines, training models, feature engineering, model evaluation, or deploying ML systems to production.

日本語の概要は準備中です。原文の説明を表示しています。

This skill should be used when troubleshooting Firebase emulator issues, rules violations, function errors, auth problems, or deployment failures. Triggers on "error", "not working", "debug", "troubleshoot", "failing", "broken", "permission denied", "emulator issue".

日本語の概要は準備中です。原文の説明を表示しています。

Docker, Kubernetes, and AWS ECS/Fargate patterns. Triggers on: Dockerfile, docker-compose, kubernetes, k8s, helm, pod, deployment, service, ingress, container, image, ecs, fargate, task definition, ecs service, awsvpc, FARGATE_SPOT, ALB, ecs vs kubernetes.

日本語の概要は準備中です。原文の説明を表示しています。

Validates entire engineering proof chain. Verifies architecture, backend maps, backend code, standardization, frontend types, infrastructure topology all compose correctly. This is the final DEPLOYMENT GATE - deployment blocked if proof chain invalid. Use when engineering thread completes all actions.

日本語の概要は準備中です。原文の説明を表示しています。

AWS Bedrock AgentCore comprehensive expert for deploying and managing AI agents at scale. Use when working with any AgentCore service including Gateway, Runtime, Memory, Identity, Code Interpreter, Browser, Observability, Agent Registry, or Evaluations. Covers agent deployment, MCP tool integration, credential management, agent discovery, governance workflows, and automated quality assessment. Essential when user mentions AgentCore, agent runtime, agent registry, agent evaluation, MCP gateway, deploy agent, register MCP server, discover agents, evaluate agent quality, agent credentials, or wants to build, deploy, catalog, or monitor AI agents on AWS.

日本語の概要は準備中です。原文の説明を表示しています。

Provides patterns to deploy ECS tasks and services with GitHub Actions CI/CD. Use when building Docker images, pushing to ECR, updating ECS task definitions, deploying ECS services, integrating with CloudFormation stacks, configuring AWS OIDC authentication for GitHub Actions, and implementing production-ready container deployment pipelines. Supports ECS deployments with proper security (OIDC or IAM keys), multi-environment support, blue/green deployments, ECR private repositories with image scanning, and CloudFormation infrastructure updates.

日本語の概要は準備中です。原文の説明を表示しています。

Routes substantive ML, AI, data, scientific-computing, and software-engineering requests to the smallest useful set of managed repository skills. Invoke proactively when a request names or implies a package, framework, model family, dataset, modality, workflow, backend, deployment target, evaluation method, or implementation approach that may benefit from repository guidance, even if no repository is named. Narrow progressively from area to family to repository root: inspect only the one or two most likely area pages; compare candidates by capability, task surface, model/data format, training versus inference versus evaluation intent, runtime constraints, and root-skill description; then open only the selected root and relevant sub-skills, references, or scripts. Select multiple repositories only when each adds a distinct capability. Do not load the whole collection, treat dependencies or incidental integrations as capabilities, choose by name alone, or force a match when no exact taxonomy family applies.

日本語の概要は準備中です。原文の説明を表示しています。

Azure OpenAI Service integration. Manage Models, Deployments, Prompts, Completions. Use when the user wants to interact with Azure OpenAI Service data.

日本語の概要は準備中です。原文の説明を表示しています。

Deploy funnelcake (api + relay) to ANY environment (production, staging, poc) on GKE via ArgoCD. Use when: (1) Deploying new funnelcake commits, (2) Building Docker images for GKE (amd64), (3) Running ClickHouse migrations, (4) Troubleshooting ImagePullBackOff errors, (5) Syncing staging/poc after production deployment. Covers complete workflow with PRE-FLIGHT CHECKLIST to prevent common deployment failures.

日本語の概要は準備中です。原文の説明を表示しています。

Fix Cloud Run GPU deployment failures caused by quota errors. Use when: (1) `gcloud run deploy` fails with "You do not have quota for using GPUs with zonal redundancy" AND "You do not have quota for using GPUs without zonal redundancy", (2) The service already exists and is running with a GPU, (3) You only need to update the container image, not change GPU config. Uses `gcloud run services update --image` instead of `gcloud run deploy` to bypass quota re-validation on existing GPU services.

日本語の概要は準備中です。原文の説明を表示しています。

Design, implement, and validate reproducible machine-learning pipelines spanning data preparation, training, evaluation, registry, and deployment gates. Use when the user requests an ML pipeline, needs to turn model scripts into an orchestrated workflow, or provides pipeline components that must be connected safely.

日本語の概要は準備中です。原文の説明を表示しています。

Expert SurrealDB 3 architect and developer skill (tracks v3.1.4+). SurrealQL mastery, multi-model data modeling (document, graph, vector, time-series, geospatial), schema design, security, deployment, performance tuning, SDK integration (JS, Python, Go, Rust, Java, .NET, C, PHP, Swift, Kotlin, Ruby), Surrealism WASM extensions, SurrealML scope coverage (preview), built-in MCP (v3.1+) and standalone SurrealMCP, LangChain Python integration, editor tooling (LSP v0.1.6, tree-sitter, CodeMirror v1.0.6, VS Code/JetBrains/Neovim/Zed), and ecosystem integrations (Surrealist v3.9, Surreal-Sync, SurrealFS, SurrealKit v0.7, n8n, Agent Skills, setup-surreal). Universal skill for 30+ AI agents.

日本語の概要は準備中です。原文の説明を表示しています。

Docker containerization expert with deep knowledge of multi-stage builds, image optimization, container security, Docker Compose orchestration, and production deployment patterns. Use PROACTIVELY for Dockerfile optimization, container issues, image size problems, security hardening, networking, and orchestration challenges.

日本語の概要は準備中です。原文の説明を表示しています。

Internal — for Boundless team members only. Monitor Boundless deployment pipelines (AWS CodePipeline + CodeBuild) on the ops account. Use when the user wants to track a deployment after merging a PR, check whether a commit has rolled out to staging/prod, diagnose a failed deployment, watch the status of a specific pipeline, or get prompted to approve a production rollout once staging succeeds. Do NOT use for service runtime debugging (use ops-logs-query) or for deploying dev infrastructure (use ops-infra-deploy).

日本語の概要は準備中です。原文の説明を表示しています。

Create operational playbooks for incident response, deployments, and maintenance during PRD v0.8 Deployment & Ops. Triggers on requests to create runbooks, document procedures, or when user asks "how do we handle incidents?", "runbook", "operational procedures", "on-call guide", "incident response", "maintenance procedures". Outputs RUN- entries with step-by-step operational procedures.

日本語の概要は準備中です。原文の説明を表示しています。

You are an expert in Bolt.new by StackBlitz, the AI-powered full-stack development environment that runs entirely in the browser. You help developers go from idea to deployed app in minutes using natural language prompts — Bolt generates complete applications with frontend, backend, database, and deployment, all running in a WebContainer without local setup.

日本語の概要は準備中です。原文の説明を表示しています。

Expert guidance for CapRover, the open-source PaaS that turns any Linux server into a Heroku-like platform with automatic HTTPS, one-click app deployment, and Docker-based containerization. Helps developers deploy applications, configure custom domains, and manage the CapRover cluster.

日本語の概要は準備中です。原文の説明を表示しています。