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deployment-pipeline-design — Claude Code skill

Designs staged CI/CD pipelines with approvals, security checks and rollout strategies. Use it for canary, blue-green and rollback planning.

Install into Claude Code · Plugin marketplace All methods and platforms ↓
/plugin marketplace add wshobson/agents
/plugin install cicd-automation@claude-code-workflows
Open on GitHub

What deployment-pipeline-design does

This skill designs CI/CD pipeline structure: stages, job dependencies, parallel work and caching. It can shape a rollout with canary weights, a blue-green switch or rolling parameters, then define readiness checks and post-deployment smoke tests.

The output covers metric thresholds, manual approval flows, rollback triggers and runbook steps. The patterns address Kubernetes, ECS, virtual machines, serverless and platform-as-a-service targets, with monitoring based on Prometheus, Datadog or CloudWatch. Detailed patterns are in references/details.md; extended examples for GitHub Actions, GitLab CI and Azure Pipelines are in references/advanced-strategies.md.

Check production protection rules before relying on an approval gate: a missing reviewer assignment can leave the job waiting indefinitely. Canary promotion also depends on a valid AnalysisTemplate and a Prometheus query that returns data. Database migrations should remain backward-compatible while older code is still deployed.

What it helps with

  • design a staged CI/CD pipeline
  • add approvals between environments
  • choose a canary or blue-green rollout
  • trigger rollback from degraded metrics
  • debug a production gate that never starts

Example prompts for the agent

  • Design a CI/CD pipeline for a Kubernetes service with dev, staging and prod environments, manual approval and a canary rollout.
  • Investigate why the canary never reaches full traffic and propose an `AnalysisTemplate` using Prometheus.
  • Create a rollback plan with backward-compatible database migrations and post-deployment health checks.

How to install deployment-pipeline-design

1Plugin marketplace

/plugin marketplace add wshobson/agents
/plugin install cicd-automation@claude-code-workflows

This installs the whole cicd-automation plugin with all its skills

2Skills CLI (Vercel)

npx skills add wshobson/agents --skill deployment-pipeline-design -a claude-code

3Manually: put the files in place

~/.claude/skills/deployment-pipeline-design/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/deployment-pipeline-design/

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Questions about deployment-pipeline-design

How do I install deployment-pipeline-design in Claude Code?

Add the marketplace with /plugin marketplace add wshobson/agents, then install the plugin with /plugin install cicd-automation@claude-code-workflows.

What does deployment-pipeline-design do?

The skill designs CI/CD pipelines with stages, dependencies, quality gates, approvals and progressive rollout strategies. It also helps diagnose failed gates and plan automated or manual rollback.

Why can a canary deployment stop before reaching full traffic?

Argo Rollouts needs a valid AnalysisTemplate for automatic promotion. If the Prometheus query returns no data, the analysis can remain inconclusive; inconclusiveLimit makes the rollout fail instead of waiting indefinitely.

Source text

SKILL.md · MIT
---
name: deployment-pipeline-design
description: Design multi-stage CI/CD pipelines with approval gates, security checks, and deployment orchestration. Use this skill when designing zero-downtime deployment pipelines, implementing canary rollout strategies, setting up multi-environment promotion workflows, or debugging failed deployment gates in CI/CD.
---

# Deployment Pipeline Design

Architecture patterns for multi-stage CI/CD pipelines with approval gates, deployment strategies, and environment promotion workflows.

## Purpose

Design robust, secure deployment pipelines that balance speed with safety through proper stage organization, automated quality gates, and progressive delivery strategies. This skill covers both the structural design of pipeline architecture and the operational patterns for reliable production deployments.

## Input / Output

### What You Provide

- **Application type**: Language/runtime, containerized or bare-metal, monolith or microservices
- **Deployment target**: Kubernetes, ECS, VMs, serverless, or platform-as-a-service
- **Environment topology**: Number of environments (dev/staging/prod), region layout, air-gap requirements
- **Rollout requirements**: Acceptable downtime, rollback SLA, traffic splitting needs, canary vs blue-green preference
- **Gate constraints**: Approval teams, required test coverage thresholds, compliance scans (SAST, DAST, SCA)
- **Monitoring stack**: Prometheus, Datadog, CloudWatch, or other metrics sources used for automated promotion decisions

### What This Skill Produces

- **Pipeline configuration**: Stage definitions, job dependencies, parallelism, and caching strategy
- **Deployment strategy**: Chosen rollout pattern with annotated configuration (canary weights, blue-green switchover, rolling parameters)
- **Health check setup**: Shallow vs deep readiness probes, post-deployment smoke test scripts
- **Gate definitions**: Automated metric thresholds and manual approval workflows
- **Rollback plan**: Automated rollback triggers and manual runbook steps

## When to Use

- Design CI/CD architecture for a new service or platform migration
- Implement deployment gates between environments
- Configure multi-environment pipelines with mandatory security scanning
- Establish progressive delivery with canary or blue-green strategies
- Debug pipelines where stages succeed but production behavior is wrong
- Reduce mean time to recovery by automating rollback on metric degradation

## Detailed patterns and worked examples

Detailed pattern documentation lives in `references/details.md`. Read that file when the navigation tier above is insufficient.

## Troubleshooting

### Health check passes in pipeline but service is unhealthy in production

The pipeline health check is hitting a shallow `/ping` endpoint that returns 200 even when the database is unreachable. Use a deep readiness check that verifies actual dependencies (see Health Checks section above).

### Canary deployment never promotes to 100%

Argo Rollouts requires a valid `AnalysisTemplate` to auto-promote. If the Prometheus query returns no data (e.g., metric name changed), the analysis stays inconclusive and promotion stalls. Add `inconclusiveLimit` so the rollout fails fast rather than hanging:

```yaml
spec:
  metrics:
  - name: error-rate
    failureCondition: "result[0] > 0.05"
    inconclusiveLimit: 2   # fail after 2 inconclusive results, not hang indefinitely
    provider:
      prometheus:
        query: |
          sum(rate(http_requests_total{status=~"5.."}[2m]))
          / sum(rate(http_requests_total[2m]))
```

### Staging deploy succeeds but production job never starts

Check that production environment protection rules are configured — a missing reviewer assignment means the approval gate waits indefinitely with no notification. In GitHub Actions, ensure `Required reviewers` is set to an existing user or team in **Settings → Environments → production**.

### Docker layer cache busted on every run causing slow builds

If `COPY . .` appears before dependency installation, any source file change invalidates the dependency layer. Reorder to copy dependency manifests first:

```dockerfile
# Good: dependencies cached separately from source code
COPY package*.json ./
RUN npm ci
COPY . .
RUN npm run build
```

### Rollback leaves database migrations applied to old code

A service rollback without a migration rollback causes schema/code mismatch errors. Always make migrations backward-compatible (additive only) for at least one release cycle, and keep undo scripts versioned alongside the migration:

```bash
# migrations/V20240315__add_nullable_column.sql       (forward)
# migrations/V20240315__add_nullable_column.undo.sql  (backward)
```

Never run destructive migrations (DROP COLUMN, ALTER NOT NULL) until the old code version is fully retired from all environments.

## Advanced Topics

For platform-specific pipeline configurations, multi-region promotion workflows, and advanced Argo Rollouts patterns, see:

- [`references/advanced-strategies.md`](references/advanced-strategies.md) — Extended YAML examples, platform-specific configs (GitHub Actions, GitLab CI, Azure Pipelines), multi-region canary patterns, and database migration rollback strategies

## Related Skills

- `github-actions-templates` - For GitHub Actions implementation patterns and reusable workflows
- `gitlab-ci-patterns` - For GitLab CI/CD pipeline implementation
- `secrets-management` - For secrets handling in CI/CD pipelines

© Seth Hobson · MIT · wshobson/agents

See also

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