| name | orchestrating-deployment-pipelines |
| description | Deploy use when you need to work with deployment and CI/CD.
This skill provides deployment automation and orchestration with comprehensive guidance and automation.
Trigger with phrases like "deploy application", "create pipeline",
or "automate deployment".
|
| allowed-tools | Read, Write, Edit, Grep, Glob, Bash(git:*), Bash(docker:*), Bash(kubectl:*) |
| version | 1.28.0 |
| author | Jeremy Longshore <jeremy@intentsolutions.io> |
| license | MIT |
| tags | ["devops","deployment","ci-cd"] |
| compatibility | Designed for Claude Code |
Orchestrating Deployment Pipelines
Overview
Orchestrate multi-stage deployment pipelines that coordinate builds, tests, approvals, and releases across environments (dev, staging, production). Implement deployment strategies including blue-green, canary, rolling updates, and feature flags using Kubernetes, cloud-native services, and CI/CD platforms.
Prerequisites
- CI/CD platform configured (GitHub Actions, GitLab CI, Jenkins, ArgoCD)
- Kubernetes cluster with
kubectl access or cloud deployment target (ECS, Cloud Run, App Engine)
- Container registry with built and tagged images ready for deployment
- Environment-specific configuration (secrets, environment variables) stored securely
- Monitoring and alerting configured to detect deployment failures
Instructions
- Define the deployment topology: target environments, promotion flow (dev -> staging -> production), and approval gates
- Select deployment strategy per environment: rolling update for staging, canary or blue-green for production
- Generate deployment manifests (Kubernetes Deployments, Services, Ingress) or cloud service configurations
- Implement pre-deployment checks: database migration status, dependency health, configuration validation
- Configure canary analysis: route 5-10% of traffic to new version, monitor error rate and latency for 15 minutes before full rollout
- Add post-deployment verification: smoke tests, health check endpoints, synthetic monitoring
- Implement automated rollback triggers: revert if error rate exceeds 1% or P99 latency doubles during canary phase
- Set up deployment notifications: Slack messages with deployment status, version, environment, and commit link
- Document the deployment runbook with manual intervention procedures for edge cases
Output
- Deployment pipeline configurations (GitHub Actions workflows, ArgoCD Applications)
- Kubernetes manifests with deployment strategy annotations
- Canary analysis configuration (Flagger, Argo Rollouts)
- Pre/post-deployment hook scripts
- Deployment runbook with rollback procedures
Error Handling
| Error | Cause | Solution |
|---|
ImagePullBackOff | Image tag not found in registry or auth failure | Verify image exists with docker manifest inspect; check imagePullSecrets |
|
