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Orchestrating deployment pipelines

Skill jeremylongshore/claude-code-plugins-plus-skills/plugins/devops/deployment-pipeline-orchestrator/skills/orchestrating-deployment-pipelines

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Install
npx -y skills add jeremylongshore/claude-code-plugins-plus-skills --skill orchestrating-deployment-pipelines

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'Deploy use when you need to work with deployment and CI/CD.

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SKILL.md

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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

  1. Define the deployment topology: target environments, promotion flow (dev -> staging -> production), and approval gates
  2. Select deployment strategy per environment: rolling update for staging, canary or blue-green for production
  3. Generate deployment manifests (Kubernetes Deployments, Services, Ingress) or cloud service configurations
  4. Implement pre-deployment checks: database migration status, dependency health, configuration validation
  5. Configure canary analysis: route 5-10% of traffic to new version, monitor error rate and latency for 15 minutes before full rollout
  6. Add post-deployment verification: smoke tests, health check endpoints, synthetic monitoring
  7. Implement automated rollback triggers: revert if error rate exceeds 1% or P99 latency doubles during canary phase
  8. Set up deployment notifications: Slack messages with deployment status, version, environment, and commit link
  9. 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

ErrorCauseSolution
ImagePullBackOffImage tag not found in registry or auth failureVerify image exists with docker manifest inspect; check imagePullSecrets
CrashLoopBackOffApplication failing to start in new versionCheck pod logs with kubectl logs; verify environment variables and config maps
Canary analysis failedError rate or latency exceeded threshold during canaryAutomatic rollback triggered; investigate logs from canary pods before retrying
Deployment stuck in ProgressingInsufficient resources or pod scheduling failureCheck kubectl describe deployment for events; verify resource requests and node capacity
Database migration failedSchema conflict or lock timeoutRun migrations independently before deployment; add retry logic and connection timeout

Examples

  • "Create a deployment pipeline that builds on PR merge, deploys to staging automatically, runs integration tests, then requires manual approval for production with canary rollout."
  • "Set up Argo Rollouts for a Kubernetes deployment with 10% canary traffic, Prometheus-based analysis, and automatic rollback on error rate > 0.5%."
  • "Generate a blue-green deployment for an ECS service with ALB target group switching and automatic rollback on health check failure."

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