3.3천건 · 관련도순
Deploy FastGPT on your own server using its official installation script and Docker Compose, which runs its services together. Check service health and access, investigate deployment problems, and receive the access URL, initial login details, and next steps.
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Create CI/CD configurations, which automate build, test, and deployment steps, alongside Terraform infrastructure templates and Kubernetes deployment files. Generate health-check and rollback instructions to review before applying changes to cloud infrastructure or application environments.
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Deploy web projects to Netlify with its command-line tool. The skill checks authentication and project settings, links or creates a site, and publishes a preview or production version with deployment URLs and log links.
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Design and deploy a Google Cloud global external Application Load Balancer with caching and web attack protection. Matches settings to workload types, discovers existing backends, and generates Terraform or gcloud deployment scripts.
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Deploy and configure LangBot with Docker Compose or Kubernetes. Set up application settings, plugin execution, the Box sandbox for isolated commands, and API authentication, with guidance on hosting choices and common deployment problems.
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Deploy the QM package from an organization-owned deployment repository to Fly.io or AWS. Set up an administrator, choose a model provider and sign-in method, configure connectors, and optionally activate Slack, with acceptance checks before handoff.
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Choose a serving container for models deployed on SageMaker. Match the model type to a compatible image, retrieve its address from the AWS catalog, and check regional availability, CPU or GPU variants, and required host settings.
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Prepare a deployment checklist covering tests, approvals, database changes, release steps, and monitoring. Tailor it to the release and document rollback triggers, the conditions for reverting a change, before production deployment begins.
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Deploy an application to an environment that has already been configured. Use it when the destination is established and the next task is to put the application into that environment.
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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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Configures CI/CD pipelines using AWS CodePipeline, CodeBuild, CodeDeploy, CodeConnections, and CodeArtifact. Covers CodePipeline V2 (triggers, variables, execution modes, cross-account), buildspec.yml (caching, VPC, Docker), CodeDeploy strategies (blue/green, canary, linear), CodeArtifact (private package registries, auth tokens, cross-account), and source connections (GitHub, GitLab, Bitbucket). Applies when CodePipeline, CodeBuild, CodeDeploy, CodeConnections, CodeArtifact, buildspec.yml, appspec.yml, or CI/CD pipeline orchestration is referenced. Does NOT cover: ECS Fargate services or task definitions (use aws-containers), CDK Pipelines or cdk deploy (use aws-cdk), sam deploy (use aws-serverless), Amplify deployments (use aws-amplify), or GitHub Actions/GitLab CI.
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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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Surfaces PAC CLI upload errors and Dataverse async operation errors, pattern-matches against a known failure catalog, and optionally auto-fixes identified issues. Use when asked to: "diagnose deployment", "debug deployment", "deployment failed", "show deployment errors", "fix deployment issues", "show upload logs", "why did my deploy fail", or "troubleshoot upload".
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Pre-deployment privacy compliance checklist for AI/ML systems covering DPIA completion, lawful basis verification, transparency notices, human oversight mechanisms, bias testing, and post-deployment monitoring setup. Keywords: AI deployment, privacy checklist, go-live, model deployment, compliance gate.
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World-class continuous integration and deployment - GitHub Actions, GitLab CI, deployment strategies, and the battle scars from pipelines that broke productionUse when "ci/cd, cicd, pipeline, github actions, gitlab ci, circleci, jenkins, workflow, deployment, deploy, release, blue green, canary, rollback, build, test automation, continuous integration, continuous deployment, cicd, github-actions, gitlab-ci, deployment, automation, devops, pipelines, continuous-integration, continuous-deployment" mentioned.
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AppDeploy Skill workflow skill. Use this skill when the user needs Deploy web apps with backend APIs, database, and file storage. Use when the user asks to deploy or publish a website or web app and wants a public URL. Uses HTTP API via curl and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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Deploy and operate apps on Prisma Compute with the Prisma 8 CLI. Use whenever the user mentions Prisma Compute, deploying or hosting a Prisma app, `prisma deploy`, `prisma dev module.ts`, Prisma Composer apps (`module.ts`, `compute()`, the `composer` section of `prisma.config.ts`), preview stages, deploy on push (`prisma git connect`, `prisma/cloud-deploy-action`), `prisma service` logs, versions, rollback, or custom domains, `project env`, `PRISMA_SERVICE_TOKEN`, regions, 504s, sleeping instances, or `waitUntil`; also when a project still uses the removed `@prisma/cli app deploy`, `prisma.compute.ts`, `defineComputeConfig`, `compute:deploy`, or `build logs` surface.
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Deploys websites, web apps, APIs, and agents to the internet with a strict pre-deploy audit and a preview → health-check → prod flow. Handles plain HTML/CSS/JS pages and static sites (Astro, Hugo, Jekyll, Eleventy, Vite) as well as Next, Remix, Nuxt, SvelteKit, FastAPI, Flask, Express, MCP servers, Claude Agent SDK scripts, Python workers, and Dockerized projects. Routes to free static hosts — Cloudflare Pages, Netlify, GitHub Pages, Render — or to Vercel, Railway, Docker+SSH VPS, or a cloudflared tunnel, and can also run the project locally. Use when the user says "/all-deploy", "/deploy", "/despliega", "deploy this", "ship this", "push to prod", "get this online", "publish my website", "sube mi página web", "publicar mi página", "hosting gratis", "free hosting", "custom domain", "dominio propio", "run it locally", "corre esto localmente", or otherwise asks to publish a site or project to a URL.
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Deploy applications to Kubernetes clusters using kubectl manifests for Deployments, Services, ConfigMaps, Secrets, and Ingress resources. Implement health checks, resource limits, rolling updates, and Helm chart packaging for production deployments. Use when deploying new applications to EKS, GKE, AKS, or self-hosted clusters, migrating from Docker Compose to container orchestration, implementing zero-downtime rolling updates, or setting up multi-environment deployments across dev, staging, and production.
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Deploy applications and websites to Vercel. Use when the user requests deployment actions like "deploy my app", "deploy and give me the link", "push this live", or "create a preview deployment".
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Create a SageMaker endpoint (real-time, real-time scale-to-zero, or async) with autoscaling, CloudWatch alarms, and tagging enabled by default. Use this skill whenever about to create a SageMaker endpoint, write deployment code that calls `create_endpoint`, or finalize a deployment after the image URI and IAM role are known. Provides deploy.py for real-time endpoints, deploy_ic.py for real-time endpoints that scale to zero instances via inference components, and deploy_async.py for async endpoints (also scale-to-zero). This is the last step in the SageMaker deployment workflow. Never generate a bare `create_endpoint` call without these defaults — endpoints without autoscaling or alarms are demos, not deployments.
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Deploy applications and websites to Vercel. Use when the user requests deployment actions like "deploy my app", "deploy and give me the link", "push this live", or "create a preview deployment".
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Use when deploying this teleprompt app with get-convex/static-hosting, especially when the user says /deploydev, /deployprod, deploy dev, deploy prod, deploy production, upload static hosting, or asks which Convex static-hosting command to run. Keeps dev uploads on fearless-dolphin-422 and production uploads on befitting-dodo-95.
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Deploy Abridge clinical AI integration to HIPAA-compliant cloud infrastructure. Use when deploying to GCP Cloud Run, AWS ECS, or Azure Container Apps with healthcare-grade secrets management and compliance controls. Trigger: "deploy abridge", "abridge production deploy", "abridge Cloud Run", "abridge AWS deploy", "abridge HIPAA infrastructure".
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