「ai deployment」の検索結果

Audit deployment readiness across CI/CD, containers, monitoring, IaC, secrets, CDN, and DNS — score each area 0-100, identify critical gaps, and optionally auto-fix by chaining deploy sub-skills

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Generates operations-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Operational Excellence pillar of the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify operational requirements, and provide actionable recommendations for deployment, monitoring, and incident management.

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。

Plans and configures multi-tenancy on GKE. Covers namespace isolation, RBAC planning for teams, resource quotas, LimitRanges, network isolation, and cost allocation. Use when designing GKE multi-tenancy, configuring GKE namespaces, setting up resource quotas, or isolating GKE teams. Don't use for single-tenant cluster configuration or general deployment instructions (use gke-basics or gke-app-onboarding instead).

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。

Assists in designing and implementing secure n-tier serverless web applications and microservices on Google Cloud. Use when users need architecture designs, security checklists, Terraform code, or deployment guidance for multi-tier serverless apps, regional data residency / European sovereignty compliance, zero-trust private VPC networking, or Private Service Connect. Don't use for VM, GKE, or non-Google Cloud architectures.

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。

Guides a developer's first steps on Google Cloud, covering account creation, billing setup, project management, and deploying a first resource. Use when a new developer wants to initialize their first Google Cloud project, configure billing, and verify deployment. Don't use for enterprise organization setup (use Google Cloud Setup guided flow for that instead). Don't use for complex multi-project architectures.

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。

Interactively discovers requirements and designs holistic, multi-product system architectures, solution blueprints, and deployment recommendations for complex workloads on Google Cloud. Use when designing end-to-end cloud solutions, selecting and integrating Google Cloud services, generating architecture diagrams, or conducting requirements discovery for new cloud workloads or migrations. Don't use for single-product tasks (use product-specific skills), initial onboarding or authentication (use google-cloud-recipe-*), Well-Architected Framework reviews or audits (use google-cloud-waf-*), or workloads covered by specialized solution skills.

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。

Runs batch and HPC workloads on GKE, utilizing job queues and parallel processing. Use when running GKE batch jobs, configuring GKE HPC, or setting up GKE job queues. Don't use for standard web application deployments (use gke-app-onboarding instead).

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。

Manages core GKE cluster provisioning, credentials, Autopilot vs Standard selection, and workload deployment. Use when creating GKE clusters, fetching kubectl credentials, configuring Workload Identity, or deciding between Autopilot and Standard modes. Don't use for specialized GKE networking (use gke-networking), advanced security hardening (use gke-platform-security or gke-workload-security), or cluster upgrades (use gke-upgrades).

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。

Manages Agent Platform serving endpoints. Use when you need to create, list, describe, update, or delete serving endpoints for model deployment on Agent Platform. Also use when troubleshooting endpoint permission, quota, or resource busy errors. Don't use for deploying models to endpoints or for running model evaluations.

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。

Use this skill when deploying a trained Einstein Discovery model to production records declaratively — activating a prediction definition, mapping output fields to page layouts, adding the Einstein Discovery Action to a Flow, running bulk predict jobs, and monitoring model health via Model Manager UI. Trigger keywords: prediction definition activation, bulk predict job, Einstein Discovery Flow action, Model Manager, prediction field mapping, model refresh activation, scoring job, Einstein Discovery recommendations on record. NOT for authoring the story in CRM Analytics Studio — use admin/einstein-discovery-setup. NOT for programmatic scoring through the API — use agentforce/einstein-discovery-development.

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Entry point for the SfSkills Salesforce library: 1,040 skill packages across 11 domains (admin, agentforce, apex, architect, data, devops, flow, integration, lwc, omnistudio, security), 70 run-time agents and 92 slash commands. Use for any Salesforce, Force.com or Lightning Platform question — Apex, SOQL, SOSL, triggers, Flow, LWC, sObject, custom field, permission set, profile, sharing rule, validation rule, deployment, sandbox, Agentforce, OmniStudio, org setup. This skill does not answer Salesforce questions itself; it routes to the specific skill package that does, then hands off to a domain router.

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。

Router for the 70 SfSkills `devops` skill packages. Salesforce delivery: source tracking, packaging, branching, CI/CD pipelines, environment strategy and deployment troubleshooting. Use when the request mentions deploy, deployment, sfdx, sf CLI, scratch org, sandbox, unlocked package, change set, CI/CD, GitHub Actions, release, rollback, source tracking. Finds and opens the exact skill package to read; it does not contain the guidance itself.

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。

ML Engineer — model deployment, MLOps pipeline, feature store, model monitoring, A/B testing, production ML system design

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。

Fast headless browser for QA testing and site dogfooding. Navigate any URL, interact with elements, verify page state, diff before/after actions, take annotated screenshots, check responsive layouts, test forms and uploads, handle dialogs, and assert element states. ~100ms per command. Use when you need to test a feature, verify a deployment, dogfood a user flow, or file a bug with evidence.

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。

Fast headless browser for QA testing and site dogfooding. Navigate any URL, interact with elements, verify page state, diff before/after actions, take annotated screenshots, check responsive layouts, test forms and uploads, handle dialogs, and assert element states. ~100ms per command. Use when you need to test a feature, verify a deployment, dogfood a user flow, or file a bug with evidence.

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。

Generate a production-ready operations runbook for deploying AI agents. Covers pre-deployment checklists, shadow mode → supervised → autonomous rollout stages, monitoring dashboards, rollback proce...

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, build, test, document, and secure production-grade APIs. Covers the full lifecycle from schema design through deployment, monitoring, and versioning. Use when designing new APIs, reviewing existing ones, generating OpenAPI specs, building test suites, or debugging production issues.

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Deploy smart contracts and bridge assets to Abstract (ZK Stack L2). Use when an agent needs to deploy contracts on Abstract, bridge ETH/tokens to Abstract, trade/swap tokens, place predictions on Myriad Markets, check balances, transfer assets, or interact with Abstract mainnet. Covers zksolc compilation, Hardhat deployment, Relay bridging, DEX trading (Kona, Aborean), Myriad prediction markets, and key contract addresses.

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 smart contracts and bridge assets to Abstract (ZK Stack L2). Use when an agent needs to deploy contracts on Abstract, bridge ETH/tokens to Abstract, trade/swap tokens, check balances, transfer assets, or interact with Abstract mainnet. Covers zksolc compilation, Hardhat deployment, Relay bridging, DEX trading, and key contract addresses.

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。

Assess and manage Azure service quotas and limits to prevent deployment and scaling failures. Use this skill when users ask about quota errors, capacity planning, regional availability, or resource limits.

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。

Deep knowledge about deploying applications to Railway (PaaS, Docker, Nixpacks).

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Plan and implement infrastructure, container, CI/CD, deployment-safety, observability, and rollback changes. Does not read dotenv files or approve/release 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。

Expert DevOps engineer for CI/CD, IaC, Kubernetes, and deployment automation. Activate on: CI/CD, GitHub Actions, Terraform, Docker, Kubernetes, Helm, ArgoCD, GitOps, deployment pipeline, infrastructure as code, container orchestration. NOT for: application code (use language skills), database schema (use data-pipeline-engineer), API design (use api-architect).

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。

Cloudflare Pages CI/CD with preview environments, edge functions, and Wrangler automation. Activate on: Cloudflare Pages, Wrangler deploy, preview environment, edge function, Pages project, Cloudflare Workers integration, custom domain on Pages. NOT for: Worker-specific development (use cloudflare-worker-dev), DNS management (use devops-automator), full-stack app frameworks (use vercel-deployment).

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。