「deployment」の検索結果

Implement GitOps with ArgoCD for declarative Kubernetes 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 Azure resources with ARM templates and Bicep. Create modular deployments and manage dependencies. Use when deploying Azure-native IaC.

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。

Orchestrates Android development tasks including project creation, deployment, SDK management, and environment diagnostics using the `android` command-line tool.

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。

Harden AI/LLM deployments against prompt injection, data exfiltration, model theft, and supply chain attacks.

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Build production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.

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Build automated evaluation suites for AI agents using golden datasets, rubrics, and regression gates. Use when shipping agent features, validating prompt changes, or gating deployments on quality.

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 a coding task should be driven end-to-end from issue intake through implementation, review, deployment, and acceptance verification with minimal human re-intervention.

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Analyzes an existing codebase using strategic Domain-Driven Design to discover bounded contexts, surface ubiquitous language and semantic collisions, find places where code boundaries diverge from domain boundaries, and produce an evidence-backed domain and context map. Use when the goal is DDD-specific: bounded context discovery, ubiquitous language analysis, domain model discovery, or mapping contested ownership and responsibility. The entire repository is a valid scope; no module or directory must be named first. Does not assess architectural coupling, cohesion, or technical debt — use architectural-analysis. Does not design service communication, integration patterns, or deployment topology — use architectural-analysis or plan-a-feature. Does not refactor code, diagnose bugs, or review code quality — use refactor, investigate, or code-review.

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Plan and verify software releases with versioning, changelogs, release branches, feature flags, canaries, migration gates, rollback, deployment checks, and release readiness. Use when preparing a release, shipping a risky PR, coordinating app/backend/database rollout, recovering from a bad deploy, or defining release policy for a repo.

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Applies the reasoning of Pieter Abbeel, robotics and reinforcement learning expert, UC Berkeley professor, and co-founder of Covariant. Use this skill whenever you are designing AI systems, tackling Sim2Real transfer, deploying machine learning in the physical world, or evaluating reinforcement learning architectures. Trigger this skill for questions about domain randomization, reward design, bootstrapping real-world AI, robotics hardware assumptions, or shifting from hard-coded rules to data-driven deep learning. It helps ground theoretical AI in physical embodiment and pragmatic 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。

Test web applications end-to-end by simulating user interactions and verifying expected outcomes. Trigger when the user asks to: test a web app, verify a user flow, run end-to-end tests, QA a feature, check that a page works correctly, validate user journeys, or test a 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。

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

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Fix "Requested backend named 'X' does not exist" or TLS alert errors in Fastly Compute@Edge. Use when: (1) Backend works locally but fails in production with "backend does not exist", (2) TLS alert received (alert_id=0) errors when calling external APIs from Fastly, (3) Backends defined in fastly.toml aren't available after deployment. The fastly.toml [[backends]] section only applies during initial service creation - existing services require backends to be added via CLI or API with proper SSL/SNI configuration.

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Fix ArgoCD ExternalSecret deployment failing with "namespace X is not permitted in project Y". Use when: (1) ExternalSecret shows OutOfSync in ArgoCD but won't sync, (2) ArgoCD application status shows "namespace X is not permitted in project 'infrastructure'", (3) ExternalSecret targets a namespace managed by a different ArgoCD project, (4) Using apps-of-apps pattern with separate infrastructure and application projects.

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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.

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Creates visual representations of system structure including architecture diagrams, data flow diagrams, deployment diagrams, and sequence diagrams. Use when Claude needs to visualize system components, infrastructure, data flows, or interactions. Supports Mermaid (recommended for Markdown/GitHub), PlantUML (for detailed UML), and Graphviz/DOT (for complex networks). Trigger when users request diagrams, visualizations, or ask to "show", "diagram", "visualize", or "map out" system architecture, infrastructure, data flows, or component interactions.

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Statically analyze code to detect security vulnerabilities including buffer overflows, injection risks (SQL, command, XSS), insecure deserialization, improper authentication, hard-coded credentials, and unsafe cryptography. Use when: (1) Performing security code review, (2) Analyzing code for OWASP Top 10 vulnerabilities, (3) Identifying CWE-classified weaknesses, (4) Generating security audit reports, (5) Reviewing code before deployment, or (6) Assessing third-party code security. Findings categorized by CWE ID and severity (Critical/High/Medium/Low).

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Generate Dockerfiles, Docker Compose configurations, and Kubernetes manifests for containerizing applications. Use when: (1) Creating Dockerfiles for Node.js, Python, Java, Go, or other applications, (2) Setting up multi-service environments with Docker Compose, (3) Generating Kubernetes deployments, services, and ingress configurations, (4) Optimizing container images for production, (5) Implementing containerization best practices. Provides both ready-to-use templates and custom-generated configurations based on project requirements.

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。

Self-hosted enterprise deployments with assisted setup and dedicated support

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Use when the user asks to take a feature or bug fix from prompt to implementation, especially prompts like "/create a new feature", "build this feature end-to-end", "take this from plan to PR", or "own this change through validation and handoff". This skill is for repo-local delivery workflows that must create and maintain implementation plans, choose appropriate tests, run deterministic validation, open a draft PR against main, and return the preview deployment URL when one is available.

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 the user wants to open a pull request or finish a branch handoff. Read the PR template, inspect changes vs main, run the release skill first if the branch name looks like a version, validate the branch with the shared repo checks, open a draft PR targeting main, and return the preview deployment URL when one 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。

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.

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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。

Dokku is a self-hosted Platform-as-a-Service built on Docker that provides Heroku-like git-push deployment on your own infrastructure. With 32,000+ GitHub stars, it supports buildpacks, Dockerfiles, custom domains, SSL via Let's Encrypt, and a rich plugin ecosystem for databases, caching, and storage.

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。