deployment
Use when setting up CI/CD pipelines, creating deployment configurations, generating deploy checklists, or configuring infrastructure. Triggers: new project needs deployment, migrating CI/CD provider, adding staging/production environments, automating release process, setting up monitoring for deploys.
What this skill does
# Deployment
## Overview
Set up CI/CD pipelines and deployment configurations that automate the path from code to production. This skill detects the deployment target, generates pipeline config, creates pre/post-deploy checklists, and configures monitoring — producing a fully automated, rollback-ready deployment pipeline.
**Announce at start:** "I am using the deployment skill to set up the deployment pipeline."
## Phase 1: Detect Deployment Target
**STOP after this phase — present findings to user for confirmation before proceeding.**
Ask questions to identify the full deployment context:
**Platform Detection:**
- Where does this deploy? (Vercel, AWS, GCP, Azure, DigitalOcean, self-hosted)
- Container-based? (Docker, Kubernetes)
- Serverless? (Lambda, Cloud Functions, Edge Functions)
**CI/CD Detection:**
- What CI system? (GitHub Actions, GitLab CI, CircleCI, Jenkins)
- What triggers deployments? (push to main, tags, manual)
- Multi-environment? (dev, staging, production)
**Infrastructure Detection:**
- Database migrations needed?
- Environment variables management? (secrets manager, .env)
- CDN/caching? Asset pipeline?
- Monitoring/alerting? (Datadog, Sentry, New Relic)
### Platform Selection Decision Table
| Project Type | Recommended Platform | CI/CD | Why |
|---|---|---|---|
| Static site / SPA | Vercel, Netlify, Cloudflare Pages | Built-in | Zero config, edge CDN |
| Node.js API | AWS ECS, Cloud Run, Railway | GitHub Actions | Container support, auto-scaling |
| Monorepo (frontend + backend) | Vercel + AWS / Railway | GitHub Actions | Split concerns, independent scaling |
| Enterprise / compliance-heavy | AWS EKS, GKE | GitLab CI, Jenkins | Full control, audit trails |
| Hobby / side project | Railway, Fly.io, Render | Built-in or GitHub Actions | Simple, low cost |
| ML / data pipelines | AWS SageMaker, GCP Vertex | GitHub Actions + Airflow | GPU support, pipeline orchestration |
## Phase 2: Design Pipeline
**STOP after this phase — present pipeline design to user for approval before generating config.**
### Standard Pipeline Stages
```
┌─────────┐ ┌──────────┐ ┌──────────┐ ┌──────────┐ ┌──────────┐
│ Build │──▶│ Test │──▶│ Lint/ │──▶│ Deploy │──▶│ Verify │
│ │ │ │ │ Check │ │ │ │ │
└─────────┘ └──────────┘ └──────────┘ └──────────┘ └──────────┘
```
**Build:** Install dependencies, compile, bundle
**Test:** Unit tests, integration tests, coverage check
**Lint/Check:** Linting, type checking, security audit
**Deploy:** Push to target environment
**Verify:** Health checks, smoke tests, monitoring
### Branch Strategy Decision Table
| Branch | Action | Environment | Gate |
|---|---|---|---|
| `feature/*` | Build + Test + Lint | None | PR checks pass |
| `main` | Build + Test + Lint + Deploy | Staging | All checks green |
| `release/*` or tags | Build + Test + Lint + Deploy | Production | Manual approval |
| `hotfix/*` | Build + Test + Deploy | Production (expedited) | Senior approval |
### Deployment Strategy Decision Table
| Strategy | When to Use | Risk Level | Rollback Speed |
|---|---|---|---|
| Direct deploy | Solo/hobby projects, staging | High | Slow (redeploy) |
| Blue-green | Apps with health checks, low-downtime needs | Low | Instant (switch) |
| Canary | High-traffic production, gradual rollout | Very Low | Fast (reroute) |
| Rolling | Kubernetes clusters, stateless services | Low | Medium |
| Feature flags | Decoupled deploy from release | Very Low | Instant (toggle) |
## Phase 3: Generate Config
### GitHub Actions Example
```yaml
name: CI/CD Pipeline
on:
push:
branches: [main]
pull_request:
branches: [main]
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
jobs:
build-and-test:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-node@v4
with:
node-version: '20'
cache: 'npm'
- run: npm ci
- run: npm run lint
- run: npm run type-check
- run: npm test -- --coverage
- run: npm run build
deploy-staging:
needs: build-and-test
if: github.ref == 'refs/heads/main'
runs-on: ubuntu-latest
environment: staging
steps:
- uses: actions/checkout@v4
# [platform-specific deploy steps]
deploy-production:
needs: build-and-test
if: startsWith(github.ref, 'refs/tags/v')
runs-on: ubuntu-latest
environment: production
steps:
- uses: actions/checkout@v4
# [platform-specific deploy steps]
```
### GitLab CI Example
```yaml
stages:
- build
- test
- deploy
build:
stage: build
script:
- npm ci
- npm run build
artifacts:
paths: [dist/]
test:
stage: test
script:
- npm run lint
- npm run type-check
- npm test -- --coverage
deploy-staging:
stage: deploy
environment: staging
script:
- # platform-specific deploy
only:
- main
deploy-production:
stage: deploy
environment: production
script:
- # platform-specific deploy
when: manual
only:
- tags
```
## Phase 4: Create Deployment Checklists
**STOP — present checklists to user. Customize based on their stack.**
### Pre-Deploy Checklist
```markdown
## Pre-Deploy Checklist
- [ ] All tests passing on CI
- [ ] Code reviewed and approved
- [ ] No critical/high security vulnerabilities
- [ ] Environment variables configured for target environment
- [ ] Database migrations tested (if applicable)
- [ ] Feature flags configured (if applicable)
- [ ] Rollback plan documented
- [ ] Monitoring/alerts configured
- [ ] Changelog updated
- [ ] Version bumped
```
### Post-Deploy Verification
```markdown
## Post-Deploy Verification
- [ ] Health check endpoint returns 200
- [ ] Smoke tests passing
- [ ] Error rate within normal range
- [ ] Response times within SLA
- [ ] Database migrations applied successfully
- [ ] Feature flags active/inactive as expected
- [ ] Monitoring dashboard showing expected metrics
- [ ] No new errors in error tracking (Sentry, etc.)
```
## Phase 5: Review and Finalize
Present the complete pipeline configuration to the user:
1. VERIFY CI/CD config file syntax is valid
2. VERIFY all environment variables are documented
3. VERIFY rollback plan exists
4. VERIFY pre/post-deploy checklists are complete
5. VERIFY the pipeline can be tested locally (act, etc.)
Save config to `.github/workflows/` or equivalent.
## Anti-Patterns / Common Mistakes
| Anti-Pattern | Why It Is Wrong | What to Do Instead |
|---|---|---|
| Manual production deploys | Error-prone, no audit trail | Automate via CI/CD pipeline |
| No rollback plan | Stuck if deploy breaks production | Define rollback before every deploy |
| Skipping staging | Bugs found in production | Always deploy to staging first |
| Secrets in code/config files | Security breach risk | Use secrets manager or env vars |
| `latest` tag for production images | Non-reproducible deploys | Pin specific version tags |
| No concurrency control | Conflicting deploys | Add concurrency groups to CI |
| Deploying without health checks | No visibility into deploy health | Add health endpoint + post-deploy check |
| Alert fatigue from noisy monitors | Real issues get missed | Alert on symptoms, tune thresholds |
## Key Principles
- **Automate everything** — no manual steps in the critical path
- **Fast feedback** — fail early, fail fast
- **Environment parity** — staging matches production
- **Rollback-ready** — every deploy has a rollback plan
- **Observable** — monitoring before, during, and after deploy
- **Secure** — no secrets in code, use secrets management
- **Idempotent** — deploying the same version twice produces the same result
## Integration Points
| Skill | Integration |
|---|---|
| `senior-devops` | Provides Docker, K8s, and IaC patterns used in deploy config |
| `git-commit-helper` | Conventional commits drive changelog and version bumping |
| `finishinRelated in Cloud & DevOps
appbuilder-action-scaffolder
IncludedCreate, implement, deploy, and debug Adobe Runtime actions with consistent layout, validation, and error handling. Use this skill whenever the user needs to add actions to an App Builder project, understand action structure (params, response format, web/raw actions), configure actions in the manifest, use App Builder SDKs (State, Files, Events, database), deploy and invoke actions via CLI, debug action issues, or implement patterns such as webhook receivers, custom event providers, journaling consumers, large payload redirects, action sequence pipelines, and Asset Compute workers. Also trigger when users mention serverless functions in Adobe context, action logging, IMS authentication for actions, or cron-style scheduled actions.
orchestrating-datacloud
IncludedSalesforce Data Cloud product orchestrator for connect→prepare→harmonize→segment→act workflows. Use this skill when the user needs a multi-step Data Cloud pipeline, cross-phase troubleshooting, or data space and data kit management. TRIGGER when: user needs a multi-step Data Cloud pipeline, asks to set up or troubleshoot Data Cloud across phases, manages data spaces or data kits, or wants a cross-phase sf data360 workflow. DO NOT TRIGGER when: work is isolated to a single phase (use the matching phase-specific skill), the task is STDM/session tracing/parquet telemetry (use observing-agentforce), standard CRM SOQL (use querying-soql), or Apex implementation (use generating-apex).
github-project-automation
IncludedAutomate GitHub repository setup with CI/CD workflows, issue templates, Dependabot, and CodeQL security scanning. Includes 12 production-tested workflows and prevents 18 errors: YAML syntax, action pinning, and configuration. Use when: setting up GitHub Actions CI/CD, creating issue/PR templates, enabling Dependabot or CodeQL scanning, deploying to Cloudflare Workers, implementing matrix testing, or troubleshooting YAML indentation, action version pinning, secrets syntax, runner versions, or CodeQL configuration. Keywords: github actions, github workflow, ci/cd, issue templates, pull request templates, dependabot, codeql, security scanning, yaml syntax, github automation, repository setup, workflow templates, github actions matrix, secrets management, branch protection, codeowners, github projects, continuous integration, continuous deployment, workflow syntax error, action version pinning, runner version, github context, yaml indentation error
sf-datacloud
IncludedSalesforce Data Cloud product orchestrator for connect→prepare→harmonize→segment→act workflows. TRIGGER when: user needs a multi-step Data Cloud pipeline, asks to set up or troubleshoot Data Cloud across phases, manages data spaces or data kits, or wants a cross-phase `sf data360` workflow. DO NOT TRIGGER when: work is isolated to a single phase (use the matching sf-datacloud-* skill), the task is STDM/session tracing/parquet telemetry (use sf-ai-agentforce-observability), standard CRM SOQL (use sf-soql), or Apex implementation (use sf-apex).
fabric-cli
IncludedUse this skill for Fabric.so CLI workflows with the `fabric` terminal command: diagnose/install/login, search or browse a Fabric library, save notes/links/files, create folders, ask the Fabric AI assistant, manage tasks/workspaces, generate shell completion, check subscription usage, produce JSON output, and use Fabric as persistent agent memory. Do not use for Microsoft Fabric/Azure/Power BI `fab`, Daniel Miessler's Fabric framework, Python Fabric SSH, Fabric.js, or textile/fashion fabric.
lark
IncludedLark/Feishu CLI skills: lark-cli operations for docs, markdown, sheets, base, calendar, im, mail, task, okr, drive, wiki, slides, whiteboard, apps, approval, attendance, contact, vc, minutes, event. Use when the user needs to operate Lark/Feishu resources via lark-cli, send messages, manage documents, spreadsheets, calendars, tasks, OKRs, deploy web pages, or any Feishu/Lark workspace operations.