「ai deployment」の検索結果

Containerize NestJS apps with multi-stage Docker builds, tune Node.js memory, and implement graceful shutdown hooks. Use when writing Dockerfiles, configuring K8s deployments, or adding shutdown hooks for NestJS.

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Draws architecture diagrams as editable draw.io files with a fixed house style, C4 levels, evidence-tagged shapes, and optional multi-view identity checks. Use when producing a system context, container, component, deployment, data flow, sequence, state, or ERD, or redrawing an ASCII or Mermaid one.

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Select and verify the current region-specific serving container URI for a SageMaker model deployment. Use after the deployment pathway is chosen and before endpoint code; never infer an image URI from memory.

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Implement production-ready service mesh deployments with Istio, Linkerd, or Cilium. Configure mTLS, authorization policies, traffic routing, and progressive delivery patterns for secure, observable microservices. Use when setting up service-to-service communication, implementing zero-trust security, or enabling canary deployments.

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Constructs secure, efficient CI/CD pipelines with supply chain security (SLSA), monorepo optimization, caching strategies, and parallelization patterns for GitHub Actions, GitLab CI, and Argo Workflows. Use when setting up automated testing, building, or deployment workflows.

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Manage Azure DevOps projects, work items, repos, PRs, pipelines, wikis, test plans, security alerts, variable groups, environments/approvals, branch policies, and attachments. Use when user asks to: manage sprints, create/update work items, list repos, create PRs, run pipelines, search code, manage wiki pages, check security alerts, manage variable groups, approve deployments, or configure branch policies. Covers 13 domains with 99 tools via REST API.

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Cloud infrastructure design and deployment patterns for AWS, Azure, and GCP. Use when designing cloud architectures, implementing IaC with Terraform, optimizing costs, or setting up multi-region deployments.

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Automation skill for Lovable deployments. Activates when: - yolo_mode: on in CLAUDE.md - Running /deploy-edge or /apply-migration commands - After git push when auto_deploy: on (automatic detection) - Any mention of "yolo mode", "automate Lovable", "browser automation", "Lovable MCP" Uses Lovable MCP (preferred) or browser automation to submit deployment prompts. Runs verification tests based on configuration. Auto-deploys after git push when enabled.

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Comprehensive GitHub release orchestration with AI swarm coordination for automated versioning, testing, deployment, and rollback management

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Operational skill hub for LLM system architecture, evaluation, deployment, and optimization (modern production standards). Links to specialized skills for prompts, RAG, agents, and safety. Integrates recent advances: PEFT/LoRA fine-tuning, hybrid RAG handoff (see dedicated skill), vLLM 24x throughput, multi-layered security (90%+ bypass for single-layer), automated drift detection (18-second response), and CI/CD-aligned evaluation.

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Create and manage database migrations with reversible changes, proper naming conventions, and zero-downtime deployment strategies. Use this skill when creating database migration files, modifying schema, adding or removing tables/columns, managing indexes, or handling data migrations. Apply when working with migration files (e.g., db/migrate/, migrations/, alembic/, sequelize migrations), schema changes, database versioning, rollback implementations, or when you need to ensure backwards compatibility during deployments. Use for any task involving database structure changes, index creation, constraint modifications, or data transformation scripts.

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。

Comprehensive GitHub release orchestration with AI swarm coordination for automated versioning, testing, deployment, and rollback 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。

Comprehensive GitHub release orchestration with AI swarm coordination for automated versioning, testing, deployment, and rollback 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。

Provides AWS CloudFormation patterns for ECS clusters, task definitions, services, container definitions, auto scaling, blue/green deployments, CodeDeploy integration, ALB integration, service discovery, monitoring, logging, template structure, parameters, outputs, and cross-stack references. Use when creating ECS clusters with CloudFormation, configuring Fargate and EC2 launch types, implementing blue/green deployments, managing auto scaling, integrating with ALB and NLB, and implementing ECS best practices.

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Provides comprehensive patterns for deploying Next.js applications to production. Use when configuring Docker containers, setting up GitHub Actions CI/CD pipelines, managing environment variables, implementing preview deployments, or setting up monitoring and logging for Next.js applications. Covers standalone output, multi-stage Docker builds, health checks, OpenTelemetry instrumentation, and production best practices.

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Generates comprehensive operational runbooks for any system or process. Reads codebase, infrastructure config, and deployment scripts to produce structured runbook.md files formatted for on-call engineers. Use when you need operations documentation, incident response guides, deployment procedures, or disaster recovery plans.

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Applies coarse-grained service architecture for deployment independence. Use when independent deployment is needed but shared databases rule out microservices.

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 self-contained Browser Use repo skill for Python agents that automate websites, browser sessions, custom tools, LLM/provider setup, persistent CLI sessions, cloud/sandbox production deployment, MCP, skills, and troubleshooting. Prefer ChatBrowserUse by default and route to focused sub-skills for implementation details.

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Use BiSheng's enterprise LLM application DevOps platform repository, including FastAPI backend, workflow/RAG/Linsight runtimes, permissions, dual React frontends, deployment, and maintainer workflows.

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Route Baichuan2 chat inference, deployment/quantization, and fine-tuning workflows.

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Route Apache Airflow repo tasks across Dag authoring, operations, providers, deployment, and contribution workflows.

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Use when packaging Spring Boot 4 as an OCI image, JVM container, AOT application, or GraalVM native executable. Covers buildpacks, layers, runtime hints, probes, security, and verification.

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Use when packaging a Spring Boot 3 application as an OCI image or GraalVM native executable. Covers buildpacks, layered images, JVM containers, AOT hints, probes, security, and verification.

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Use when an agent, harness, gateway, MCP workflow, or multi-step automation claims completion and the available traces, checkpoints, approvals, tool calls, or deployment records must be judged without trusting self-reported success.

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。