「deploy」の検索結果

Creates Dockerfiles, configures CI/CD pipelines, writes Kubernetes manifests, and generates Terraform/Pulumi infrastructure templates. Handles deployment automation, GitOps configuration, incident response runbooks, and internal developer platform tooling. Use when setting up CI/CD pipelines, containerizing applications, managing infrastructure as code, deploying to Kubernetes clusters, configuring cloud platforms, automating releases, or responding to production incidents. Invoke for pipelines, Docker, Kubernetes, GitOps, Terraform, GitHub Actions, on-call, or platform engineering.

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 for hands-on Pulumi CLI work: running deployments, fixing broken stacks, and managing infrastructure state. Handles: recovering from stuck or interrupted `pulumi up` with pending operations, cleaning orphaned resources from state after out-of-band cloud deletions, protecting critical resources from accidental `pulumi destroy`, moving resources between stacks without recreating them, targeting specific resources during deployment, migrating between backends (local file to Pulumi Cloud, S3), stack lifecycle management, state export/import/repair, CI/CD pipeline setup, and importing existing cloud resources. Use this skill — not the language-specific Pulumi skills — whenever the user's question is about operating, troubleshooting, or recovering Pulumi infrastructure rather than writing program code.

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 when deploying or managing Kubernetes workloads. Invoke to create deployment manifests, configure pod security policies, set up service accounts, define network isolation rules, debug pod crashes, analyze resource limits, inspect container logs, or right-size workloads. Use for Helm charts, RBAC policies, NetworkPolicies, storage configuration, performance optimization, GitOps pipelines, and multi-cluster 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。

Creates Pulumi infrastructure-as-code projects in Python, defines cloud resources (AWS, Azure, GCP), configures ESC environments for secrets management, sets up OIDC authentication for secure deployments, and builds multi-language component resources. Use when creating Pulumi Python projects, writing infrastructure code, configuring cloud providers, managing secrets with Pulumi ESC, setting up OIDC for Pulumi, automating infrastructure deployments with Python, creating reusable Pulumi components in Python, or configuring Python toolchains (pip, poetry, uv) for Pulumi. Also use when the user mentions pyproject.toml with Pulumi, component_provider_host, or Python virtual environments for infrastructure code.

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 cloud infrastructure through natural language conversations with Pulumi Neo, an AI agent for platform engineers. Enables infrastructure analysis, resource provisioning, stack deployment, and configuration management via conversational AI. Use when creating Neo tasks, requesting infrastructure analysis, automating cloud deployments, managing infrastructure as code (IaC), provisioning AWS/Azure/GCP resources, managing infrastructure through natural language prompts, reviewing PRs with Neo, handling Neo approval workflows, or checking Neo task status and events. Also use when the user mentions "Pulumi Neo", "Neo task", "Neo agent", or wants AI-assisted infrastructure 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。

Full-stack app pipeline — build, test, review, and deploy across one or ALL repos. Scans CLAUDE.md, MEMORY.md, TODOs, open PRs, and issues for shippable work. Supports 'ship all' for multi-repo. Use when: 'build and ship', 'ship it', 'ship all', 'deploy everything', 'full pipeline', 'what needs shipping', 'end to end'.

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。

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

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。

Detect project stack and generate GitHub Actions CI/CD workflows — PR checks with lint/test/build/security, deploy pipelines for Vercel/AWS/GCP/Fly/Docker, dependency caching, matrix testing, preview deploys, and Dependabot config

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。

Build and deploy Flutter apps to App Store (TestFlight) and Google Play (internal/production). Auto-detects project structure, pulls signing secrets from AWS Secrets Manager, installs certificates, bumps build numbers, and runs Fastlane. Fully autonomous.

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。

Emergency fix-and-deploy pipeline — diagnose a bug, apply a minimal fix, verify safety, deploy to production, and confirm the service is healthy.

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。

Ship an app from code to production-ready infrastructure: containerize with Docker and multi-stage builds, set up GitHub Actions CI/CD with automated testing and deployment, add monitoring with health checks and alerting, then run preflight verification..

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。

Generates and updates secure, production-ready Kubernetes YAML manifests optimized for GKE Autopilot and GKE Standard clusters. Use when creating or modifying GKE deployment manifests, configuring container security contexts, setting CPU/memory resource limits, defining readiness/liveness/startup probes, mounting secrets and volumes, configuring GKE Gateway API routes, targeting Spot VMs, or deploying AI model inference workloads (vLLM, TGI, Gemma). Don't use for live cluster operations, pod troubleshooting (use gke-workload-troubleshooting), or cluster infrastructure provisioning (use gke-cluster-creation).

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。

Deploys a baseline landing zone foundation for a Google Cloud Organization, establishing security guardrails using Organization Policies, resource hierarchy folders and projects, billing association, and centralized logging and monitoring. Deploys Google Cloud's recommended security controls and architecture. Use when setting up a new Google Cloud Organization or establishing a secure, enterprise-grade landing zone foundation. Don't use for individual project onboarding (use google-cloud-recipe-onboarding or product-specific skills 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 GKE application onboarding, covering containerization, deployment manifests, and migration. Use when onboarding or deploying an application to GKE for the first time, or containerizing an app for GKE. Don't use for general GKE cluster administration or upgrades (use gke-basics or gke-upgrades 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。

Agent Platform Model Tuning. Use when you need to fine-tune open models or Gemini models using Agent Platform infrastructure. Don't use for model training outside Agent Platform, model deployment to endpoints (use `agent-platform-deploy`), or managing serving endpoints (use `agent-platform-endpoint-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。

Manages GenAI tuning jobs in Agent Platform. Use this to list, get, or cancel ongoing model tuning jobs. Don't use for fine-tuning models (use `agent-platform-tuning`), deploying models to endpoints (use `agent-platform-deploy`), or managing serving endpoints (use `agent-platform-endpoint-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。

Measures and improves the quality of AI models and agents on Google Cloud using the Eval Quality Flywheel methodology. Use when evaluating an agent or model, building an eval dataset, picking or writing evaluation metrics, analyzing failures, comparing results before and after a fix, or when guidance is needed on Agent Platform eval methodology — including dataset schema, LLM-as-judge scoring, and common failure causes. For fine-tuning, use agent-platform-tuning. For general production deployment, use agent-platform-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。

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。

Configures best-practice alerting policies for AI agents using OpenTelemetry (OTel) metrics, generating output as Terraform (.tf) configuration files. Use when analyzing, writing, or deploying alerting policies to monitor agent latency, error rates, token usage, and quality metrics. Don't use for standard infrastructure monitoring unrelated to AI agents, or when the agent is not instrumented with OpenTelemetry (for Reliability, Cost, Safety, Security alerts). NOTE: Reliability, Cost, Safety, and Security alerts use generic OTel metrics and work across runtimes (such as Cloud Run, Vertex AI). Quality alerts rely on Vertex AI Online Monitors and are strictly bound to Vertex AI 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。

Use this skill when building, reviewing, or refreshing a RACI (Responsible / Accountable / Consulted / Informed) matrix for a Salesforce project so that every Salesforce-specific decision — data model change, automation tier choice, security model, integration boundary, deployment, license/edition — has exactly one accountable owner and a documented escalation path that downstream agents can route to. Trigger keywords: RACI matrix salesforce project, stakeholder authority salesforce, escalation path salesforce decisions, who approves data model change, salesforce decision rights, REFUSAL_NEEDS_HUMAN_REVIEW routing. NOT for the change advisory board operating model itself (use admin/change-management-and-deployment). NOT for end-user training rollout plans (use admin/change-management-and-training). NOT for the technical mechanics of permission set assignment authority (use admin/permission-set-architecture). NOT for pure stakeholder requirements elicitation (use admin/requirements-gathering-for-sf). More trigger keywords: who approves a sandbox refresh, who signs off a data load, release update activation owner, delegated admin authority vs RACI, multi-org decision rights, escalation time-box.

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 when creating, configuring, auditing, or troubleshooting an Agentforce agent end-to-end: agent definition, agent user setup, channel assignment, system instructions, activation, and lifecycle management. Triggers: 'create agentforce agent', 'agent not appearing to users', 'how to activate agent', 'agent channel setup', 'agent lifecycle', 'deploy agent to production'. NOT for designing what the agent can DO — an agent that looks up an order, checks a case, or creates a record is action design, use agentforce/agent-actions. NOT for topic boundary design — use agentforce/agent-topic-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。

RecordType ID differences across orgs: dynamic lookup via Schema.SObjectType methods, DeveloperName for stable refs, hard-coded ID anti-patterns, record-type caching, deployment impact. NOT for deciding whether to use record types at all — use admin/record-types-and-page-layouts. NOT for layout/profile explosion at scale — use admin/record-type-strategy-at-scale. NOT for hard-coded Profile, Queue or User IDs in Apex — use apex/apex-hardcoded-id-elimination.

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 when preparing for a Salesforce seasonal release — triaging release notes, reviewing Release Updates, opting into Sandbox Preview, and communicating change impact to stakeholders. Triggers: 'upcoming Salesforce release', 'release notes triage', 'Release Updates', 'sandbox preview opt-in', 'release readiness checklist', 'production upgrade date', 'feature impact', 'critical update', 'roll out the Spring release safely', 'is our org ready for the Spring release', 'release update settings metadata', 'FlowSettings release update field', 'release run sheet', 'preview sandbox refresh freeze', 'settings deploy flipped a release update'. Also covers: which Release Updates are deployable as Settings metadata, the release run sheet artefact, and the preview opt-in refresh-date rule. NOT for planning your own release train — use devops/release-management. NOT for user training and go-live comms — use admin/change-management-and-training.

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。