cloud-devops
Cloud infrastructure and DevOps workflow covering AWS, Azure, GCP, Kubernetes, Terraform, CI/CD, monitoring, and cloud-native development.
Best use case
cloud-devops is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Cloud infrastructure and DevOps workflow covering AWS, Azure, GCP, Kubernetes, Terraform, CI/CD, monitoring, and cloud-native development.
Teams using cloud-devops should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/cloud-devops/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How cloud-devops Compares
| Feature / Agent | cloud-devops | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Cloud infrastructure and DevOps workflow covering AWS, Azure, GCP, Kubernetes, Terraform, CI/CD, monitoring, and cloud-native development.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Cloud/DevOps Workflow Bundle ## Overview Comprehensive cloud and DevOps workflow for infrastructure provisioning, container orchestration, CI/CD pipelines, monitoring, and cloud-native application development. ## When to Use This Workflow Use this workflow when: - Setting up cloud infrastructure - Implementing CI/CD pipelines - Deploying Kubernetes applications - Configuring monitoring and observability - Managing cloud costs - Implementing DevOps practices ## Workflow Phases ### Phase 1: Cloud Infrastructure Setup #### Skills to Invoke - `cloud-architect` - Cloud architecture - `aws-skills` - AWS development - `azure-functions` - Azure development - `gcp-cloud-run` - GCP development - `terraform-skill` - Terraform IaC - `terraform-specialist` - Advanced Terraform #### Actions 1. Design cloud architecture 2. Set up accounts and billing 3. Configure networking 4. Provision resources 5. Set up IAM #### Copy-Paste Prompts ``` Use @cloud-architect to design multi-cloud architecture ``` ``` Use @terraform-skill to provision AWS infrastructure ``` ### Phase 2: Container Orchestration #### Skills to Invoke - `kubernetes-architect` - Kubernetes architecture - `docker-expert` - Docker containerization - `helm-chart-scaffolding` - Helm charts - `k8s-manifest-generator` - K8s manifests - `k8s-security-policies` - K8s security #### Actions 1. Design container architecture 2. Create Dockerfiles 3. Build container images 4. Write K8s manifests 5. Deploy to cluster 6. Configure networking #### Copy-Paste Prompts ``` Use @kubernetes-architect to design K8s architecture ``` ``` Use @docker-expert to containerize application ``` ``` Use @helm-chart-scaffolding to create Helm chart ``` ### Phase 3: CI/CD Implementation #### Skills to Invoke - `deployment-engineer` - Deployment engineering - `cicd-automation-workflow-automate` - CI/CD automation - `github-actions-templates` - GitHub Actions - `gitlab-ci-patterns` - GitLab CI - `deployment-pipeline-design` - Pipeline design #### Actions 1. Design deployment pipeline 2. Configure build automation 3. Set up test automation 4. Configure deployment stages 5. Implement rollback strategies 6. Set up notifications #### Copy-Paste Prompts ``` Use @cicd-automation-workflow-automate to set up CI/CD pipeline ``` ``` Use @github-actions-templates to create GitHub Actions workflow ``` ### Phase 4: Monitoring and Observability #### Skills to Invoke - `observability-engineer` - Observability engineering - `grafana-dashboards` - Grafana dashboards - `prometheus-configuration` - Prometheus setup - `datadog-automation` - Datadog integration - `sentry-automation` - Sentry error tracking #### Actions 1. Design monitoring strategy 2. Set up metrics collection 3. Configure log aggregation 4. Implement distributed tracing 5. Create dashboards 6. Set up alerts #### Copy-Paste Prompts ``` Use @observability-engineer to set up observability stack ``` ``` Use @grafana-dashboards to create monitoring dashboards ``` ### Phase 5: Cloud Security #### Skills to Invoke - `cloud-penetration-testing` - Cloud pentesting - `aws-penetration-testing` - AWS security - `k8s-security-policies` - K8s security - `secrets-management` - Secrets management - `mtls-configuration` - mTLS setup #### Actions 1. Assess cloud security 2. Configure security groups 3. Set up secrets management 4. Implement network policies 5. Configure encryption 6. Set up audit logging #### Copy-Paste Prompts ``` Use @cloud-penetration-testing to assess cloud security ``` ``` Use @secrets-management to configure secrets ``` ### Phase 6: Cost Optimization #### Skills to Invoke - `cost-optimization` - Cloud cost optimization - `database-cloud-optimization-cost-optimize` - Database cost optimization #### Actions 1. Analyze cloud spending 2. Identify optimization opportunities 3. Right-size resources 4. Implement auto-scaling 5. Use reserved instances 6. Set up cost alerts #### Copy-Paste Prompts ``` Use @cost-optimization to reduce cloud costs ``` ### Phase 7: Disaster Recovery #### Skills to Invoke - `incident-responder` - Incident response - `incident-runbook-templates` - Runbook creation - `postmortem-writing` - Postmortem documentation #### Actions 1. Design DR strategy 2. Set up backups 3. Create runbooks 4. Test failover 5. Document procedures 6. Train team #### Copy-Paste Prompts ``` Use @incident-runbook-templates to create runbooks ``` ## Cloud Provider Workflows ### AWS ``` Skills: aws-skills, aws-serverless, aws-penetration-testing Services: EC2, Lambda, S3, RDS, ECS, EKS ``` ### Azure ``` Skills: azure-functions, azure-ai-projects-py, azure-monitor-opentelemetry-py Services: Functions, App Service, AKS, Cosmos DB ``` ### GCP ``` Skills: gcp-cloud-run Services: Cloud Run, GKE, Cloud Functions, BigQuery ``` ## Quality Gates - [ ] Infrastructure provisioned - [ ] CI/CD pipeline working - [ ] Monitoring configured - [ ] Security measures in place - [ ] Cost optimization applied - [ ] DR procedures documented ## Related Workflow Bundles - `development` - Application development - `security-audit` - Security testing - `database` - Database operations - `testing-qa` - Testing workflows ## Limitations - Use this skill only when the task clearly matches the scope described above. - Do not treat the output as a substitute for environment-specific validation, testing, or expert review. - Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
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