「ai deployment」の検索結果

Hugo static site generator with Tailwind v4, headless CMS (Sveltia/Tina), Cloudflare deployment. Use for blogs, docs sites, or encountering theme installation, frontmatter, baseURL errors.

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Use for Docker with Bun, Dockerfiles, oven/bun image, containerization, and deployments.

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Set up a continuous integration and continuous delivery (CI/CD) pipeline for a software project, automating builds, tests, and deployments across environments. Use when the user requests ci cd or provides relevant inputs for this workflow.

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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.

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Validate release readiness with evidence-based go/no-go decisions. Covers go/no-go checklists, smoke test suite design, staged rollout validation, rollback criteria and procedures, and post-deployment verification. Ensures release confidence comes from data, not feelings. Use when: "release ready," "go/no-go," "smoke test," "release checklist," "rollback plan," "staged rollout," "canary deploy." Not for: safe-release techniques (flags, canary, dark launch) applied during the rollout itself — use testing-in-production; scheduled probes that run continuously after release — use synthetic-monitoring; designing new tests from prod telemetry — use observability-driven-testing. Related: testing-in-production, qa-metrics, ci-cd-integration, ai-system-testing.

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Implement consumer-driven contract testing with Pact-JS (v16). Covers consumer test writing, broker-driven provider verification, Pact Broker setup, can-i-deploy as a deployment gate, webhook-triggered verification, pending pacts, and schema-first vs consumer-first approaches (OpenAPI/Ajv, Schemathesis). Use when: "contract test," "Pact," "consumer-driven," "API contract," "provider verification," "can-i-deploy." Not for: stubbing or mocking a dependency to isolate a test — use service-virtualization; general REST/GraphQL endpoint assertions against your own API — use api-testing. Related: api-testing, service-virtualization, ci-cd-integration, test-environments.

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Builds full-stack web applications with AdonisJS — a batteries-included Node.js framework with ORM, auth, validation, and mailer built-in. Use when someone asks to "build a web app with Node.js", "Laravel for Node.js", "full-stack Node framework", "AdonisJS", "batteries-included backend", or "Node.js with built-in ORM and auth". Covers Lucid ORM, auth (sessions, tokens, social), VineJS validation, Edge templates, and deployment.

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Advanced GitHub Actions workflow automation with AI swarm coordination, intelligent CI/CD pipelines, and comprehensive repository management

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Cloud-based AI swarm deployment and event-driven workflow automation with Flow Nexus platform

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Build and debug Python applications using AgentScope 2.x. Consult this skill for AgentScope APIs, agent tools, multi-agent orchestration, and agent service deployment.

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Advanced GitHub Actions workflow automation with AI swarm coordination, intelligent CI/CD pipelines, and comprehensive repository management

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Choose deployment target based on project type. Static sites to CF Pages, APIs to VPS, serverless to Workers.

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Cloud-based AI swarm deployment and event-driven workflow automation with Flow Nexus platform

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Advanced GitHub Actions workflow automation with AI swarm coordination, intelligent CI/CD pipelines, and comprehensive repository management

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Design a service mesh deployment — technology selection, mTLS policy, and traffic management config. Use when asked "should we use a service mesh", "Istio or Linkerd", or "design our mTLS policy".

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Build zero-downtime database migrations — forward SQL, rollback SQL, deployment sequence. Use when asked to "write migration", "schema change", "add column", "rename table", "drop column", or "migrate safely".

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Reliability engineering for cloud systems — SLIs, SLOs, error budgets, SRE practices, runbooks, incident response, on-call rotation, blameless postmortems, chaos engineering, and the NASA Systems Engineering methodology (MCR/SRR/PDR/CDR/ORR phase gates, TAID verification, requirements tracing) adapted to cloud operations. Use when establishing SLOs for a new service, running an incident, writing a runbook, preparing a launch readiness review, or bringing NASA SE discipline to cloud deployments.

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Supervised and unsupervised learning, bias-variance tradeoff, cross-validation, decision trees, ensemble methods, neural network fundamentals, and the practitioner's workflow from problem framing through deployment. Covers classification, regression, clustering, dimensionality reduction, regularization, hyperparameter tuning, and evaluation metrics. Use when building predictive models, selecting algorithms, or understanding the machine learning pipeline.

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OpenStack Heat orchestration service skill. Use when working with HOT templates, stack lifecycle management, auto-scaling groups, nested stacks, resource type registry, template validation, or infrastructure-as-code patterns within OpenStack. Covers deployment via Kolla-Ansible, template authoring, stack operations, and troubleshooting common orchestration failures.

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Dasel v3 patterns for querying Tomcat web.xml deployment descriptors — use when inspecting servlet enumeration, filter chain discovery, listener listing, context parameter extraction, or init-param inspection in web.xml files

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Expert LLM architect specializing in large language model architecture, deployment, and optimization. Masters LLM system design, fine-tuning strategies, and production serving with focus on building scalable, efficient, and safe LLM applications.

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Kubernetes 工作负载编排，覆盖 Deployment / Service / Ingress / HPA / PDB。Helm Chart 管理、ArgoCD GitOps 部署、资源调优、高可用设计。

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AppFlowy brings documents, projects, wikis, and AI-assisted collaboration into a self-hosted or desktop-friendly workspace. This skill helps agents work from the real AppFlowy project, docs, and deployment methods when users need an open source Notion-style environment with local control.

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Turn a KOL roster + subreddit brand-fit analysis into a deployable creator network. Splits creators into KOL (authority) and KOC (grassroots) layers, matches each to a main + secondary subreddits by real gear/shooting-type ∩ community fit, and emits an account×subreddit deployment_matrix (with a ≤3-per-sub ceiling + no-cross-interaction rule) plus per-creator persona_cards. Route A disclosed-compliance baked into every card (FTC disclosure required on any material connection). Consumes reddit-kol-finder's kol_roster.json natively. READ-ONLY, deterministic, no LLM key needed.

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