'deployment' 검색 결과

Build Next.js 14+ applications with App Router, covering pages, server-side processing, data fetching, and caching. The skill also guides performance improvements, search engine metadata, and production deployment to Vercel or a self-hosted environment.

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• Building pages and layouts with App Router
• Implementing form updates with Server Actions
• Configuring data fetching and cache revalidation

Manage Flow Nexus accounts, isolated cloud environments for running code, and application deployment. The skill also covers publishing templates, tracking credits and payments, submitting coding challenges, managing stored files, and checking execution logs.

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• Create a cloud environment and run code
• Publish an app or deploy a template
• Check credit balances and configure automatic refills

Organize software releases on GitHub, from version suggestions and release notes to testing, builds, and deployment. Coordinate multiple packages or repositories, roll changes out in stages, and configure rollback to restore an earlier release when problems occur.

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• Preparing version updates and release notes
• Coordinating releases across packages and repositories
• Deploying in stages with monitoring and rollback

Create and improve GitHub Actions workflows for automated testing and deployment. Coordinate multiple AI agents to review pull requests, investigate failed runs, scan for security issues, and manage releases across repositories.

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• Create workflows for automated testing and deployment
• Investigate failed runs and suggest fixes
• Coordinate code reviews and security checks

Create and edit EAS workflow YAML files to automate builds and deployment for Expo projects. The skill consults current documentation and validates configuration structure, required parameters, job dependencies, and expressions against the published schema.

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• Create an EAS workflow for builds and deployment
• Edit workflow triggers and job dependencies
• Validate existing workflow YAML files

Prepare and deploy Expo apps to iOS and Android stores or the web using EAS, Expo's build and deployment services. Covers production builds, store submissions, beta distribution, preview deployments, and automated release workflows.

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• Prepare Expo apps for iOS and Android store submission
• Distribute an iOS beta through TestFlight
• Deploy a web app and create a PR preview

Build image and video AI systems for object detection and segmentation, which identifies separate image regions. The skill covers custom model training, dataset pipelines, inference optimization, real-time processing, and deployment and monitoring in production.

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• Developing object detection and image segmentation systems
• Training custom vision models with project data
• Optimizing inference for real-time video processing

Set up Auto Ontology with Helm or Docker Compose, or connect an agent to an existing deployment through MCP, an agent connection protocol. Guides database connections, readiness checks, and troubleshooting for startup and sign-in problems.

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• Installing Auto Ontology on Kubernetes
• Running the stack on one machine with Docker Compose
• Connecting an agent to an existing deployment

Guides initial BlueField-4 setup through its BMC, the hardware management controller. Covers OS installation methods, firmware updates, post-install checks, and troubleshooting, with action-specific confirmation and maintenance safeguards for changes that can disrupt or damage the device.

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• Install an OS on a new BlueField-4 through its BMC
• Choose HTTP Boot, PXE, or Redfish Virtual Media
• Update firmware and verify activation

Check DOCA installation health, prepare build and runtime requirements, and investigate environment failures such as missing libraries or memory settings. Helps choose container learning or hardware deployment paths based on the available system.

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• Check whether a DOCA installation is healthy
• Investigate library detection and runtime environment failures
• Start learning through an NGC DOCA container without hardware

Operate NVIDIA DOCA Management Service to read, change, and monitor BlueField or ConnectX settings locally or remotely. Get guidance on deployment, authentication, management requests, logs, and diagnosing failures across the service and its backend.

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• Read or change local BlueField settings
• Choose deployment and authentication for remote management
• Read, update, and subscribe to settings through gNMI

Run and supervise DOCA applications directly on an x86 host or BlueField Arm hardware. Covers process launch, hardware resource assignment, isolation between workloads, and troubleshooting application failures or BlueField recovery problems.

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• Launching a DOCA application directly on hardware
• Investigating systemd restart loops
• Assigning CPU and device resources to multiple workloads

Generate small-molecule candidates from a starting structure, optimize supported molecular properties, and save results for validation. Local deployment also supports embeddings, numerical representations of molecules, and workflows that convert between molecular structures and learned internal representations.

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• Generate molecular candidates around a seed structure
• Optimize candidates for QED or plogP
• Obtain molecular embeddings with a local deployment

Intelligently deploys Azure OpenAI models to optimal regions by analyzing capacity across all available regions. Automatically checks current region first and shows alternatives if needed. USE FOR: quick deployment, optimal region, best region, automatic region selection, fast setup, multi-region capacity check, high availability deployment, deploy to best location. DO NOT USE FOR: custom SKU selection (use customize), specific version selection (use customize), custom capacity configuration (use customize), PTU deployments (use customize).

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End-to-end orchestrator: from a business idea, app idea, or existing app to running Azure deployment with cost estimates and pre-deploy approval. Analyzes your app, auto-detects the right Azure services, scaffolds infrastructure code, and deploys — tailored to your app, not a template. Handles moving existing apps to Azure without rewriting or with minimal changes. WHEN: bring your app to Azure, plan my app, cost to run, is my code ready to deploy, deploy my app to the cloud, deploy all my services, what Azure services do I need, plan my Azure deployment, deploy my new app to Azure, one-click deploy, I have an app and want it on Azure, migrate my app to Azure, help me get started, build an app, no code yet, starter project. DO NOT USE FOR: use azd for deployment(use azure-deploy), optimizing existing costs (use cost-optimization), code readiness checks only (use azure-app-onboard-prereq).

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Prepare azd-based Azure projects for deployment: generates azure.yaml, infrastructure (Bicep/Terraform), and Dockerfiles for the Azure Developer CLI (azd) workflow. USE ONLY when the user explicitly wants to use azd as the deployment tool, or the project already has an azure.yaml file. DO NOT USE FOR: non-azd deployments, Python App Service code-only deploys (use python-appservice-deploy), or cross-cloud migration (use azure-cloud-migrate). WHEN: prepare app for azd, create azure.yaml, set up azd infrastructure, modernize app for Azure with azd, deploy with azd, function app, timer trigger, service bus trigger, event-driven function, managed identity, generate Bicep, generate Terraform, create and deploy to Azure.

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Discovers available Azure OpenAI model capacity across regions and projects. Analyzes quota limits, compares availability, and recommends optimal deployment locations based on capacity requirements. USE FOR: find capacity, check quota, where can I deploy, capacity discovery, best region for capacity, multi-project capacity search, quota analysis, model availability, region comparison, check TPM availability. DO NOT USE FOR: actual deployment (hand off to preset or customize after discovery), quota increase requests (direct user to Azure Portal), listing existing deployments.

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Assess whether source code is ready to deploy to Azure — the check BEFORE infrastructure work. Evaluates build health, app completeness, dependencies and local services, stack compatibility, and deployment feasibility. Answers questions about what your app needs before it can be deployed — frameworks, dependencies, and configuration. Checks whether dependencies are compatible and identifies deployment blockers and unsupported frameworks. WHEN: "evaluate my repo", "is my app ready to deploy", "what does my app need to deploy", "what do I need before deploying", "does my app need", "can I ship this to Azure", "scan my repo for issues", "is this app deployable", "check if my app is ready for Azure", "do I need a Dockerfile", "what's blocking my deployment", "are there any blockers", "are my dependencies compatible", "does Azure support my framework", "what needs to change before deploying", "check my app configuration".

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Deploy Apollo.io integrations to production. Use when deploying Apollo integrations, configuring production environments, or setting up deployment pipelines. Trigger with phrases like "deploy apollo", "apollo production deploy", "apollo deployment pipeline", "apollo to production".

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Ships changes safely and often — pipelines, deployment strategies, feature flags, rollback, and database changes. Use this to design a deployment pipeline, reduce release risk, roll out a risky change gradually, plan a schema migration, or work out why releases are infrequent and frightening.

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Design multi-stage CI/CD pipelines with approval gates, security checks, and deployment orchestration. Use when architecting deployment workflows, setting up continuous delivery, or implementing GitOps practices.

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Expert C4 Container-level documentation specialist. Synthesizes Component-level documentation into Container-level architecture, mapping components to deployment units, documenting container interfaces as APIs, and creating container diagrams. Use when synthesizing components into deployment containers and documenting system deployment architecture.

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Intelligently deploys Azure OpenAI models to optimal regions by analyzing capacity across all available regions. Automatically checks current region first and shows alternatives if needed. USE FOR: quick deployment, optimal region, best region, automatic region selection, fast setup, multi-region capacity check, high availability deployment, deploy to best location. DO NOT USE FOR: custom SKU selection (use customize), specific version selection (use customize), custom capacity configuration (use customize), PTU deployments (use customize).

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Discovers available Azure OpenAI model capacity across regions and projects. Analyzes quota limits, compares availability, and recommends optimal deployment locations based on capacity requirements. USE FOR: find capacity, check quota, where can I deploy, capacity discovery, best region for capacity, multi-project capacity search, quota analysis, model availability, region comparison, check TPM availability. DO NOT USE FOR: actual deployment (hand off to preset or customize after discovery), quota increase requests (direct user to Azure Portal), listing existing deployments.

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