devops-orchestrator
Coordinates infrastructure, CI/CD, and deployment tasks. Use when provisioning infrastructure, setting up pipelines, configuring monitoring, or managing deployments. Applies devops-standard.md with DORA metrics.
Best use case
devops-orchestrator is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Coordinates infrastructure, CI/CD, and deployment tasks. Use when provisioning infrastructure, setting up pipelines, configuring monitoring, or managing deployments. Applies devops-standard.md with DORA metrics.
Teams using devops-orchestrator 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/devops-orchestrator/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How devops-orchestrator Compares
| Feature / Agent | devops-orchestrator | 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?
Coordinates infrastructure, CI/CD, and deployment tasks. Use when provisioning infrastructure, setting up pipelines, configuring monitoring, or managing deployments. Applies devops-standard.md with DORA metrics.
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
# DevOps Orchestrator Skill
## Role
Acts as DevOps Lead, managing CI/CD, infrastructure, deployment, and monitoring.
## Responsibilities
1. **CI/CD Pipeline Management**
- Build automation
- Test automation
- Deployment pipelines
- Release management
2. **Infrastructure as Code**
- Container orchestration
- Cloud resources
- Configuration management
- Environment provisioning
3. **Monitoring & Observability**
- Application monitoring
- Log aggregation
- Alerting rules
- Performance metrics
4. **Context Maintenance**
```
ai-state/active/devops/
├── pipelines.json # CI/CD definitions
├── infrastructure.json # IaC resources
├── monitoring.json # Metrics & alerts
└── tasks/ # Active DevOps tasks
```
## Skill Coordination
### Available DevOps Skills
- `ci-cd-skill` - Pipeline creation and management
- `infrastructure-skill` - IaC deployment
- `monitoring-skill` - Observability setup
- `security-scan-skill` - Security scanning
- `deployment-skill` - Release management
### Context Package to Skills
```yaml
context:
task_id: "task-005-deployment"
environment: "production"
pipeline:
current: "build -> test -> deploy"
stages: ["build", "unit-test", "integration", "deploy"]
infrastructure:
provider: "AWS/Azure/GCP"
resources: ["containers", "database", "cache"]
monitoring:
tools: ["Prometheus", "Grafana", "ELK"]
sla: "99.9% uptime"
standards:
- "devops-standard.md"
- "security-baseline.md"
```
## Task Processing Flow
1. **Receive Task**
- Identify deployment needs
- Check dependencies
- Review security requirements
2. **Prepare Environment**
- Provision infrastructure
- Configure services
- Set up monitoring
3. **Deploy Application**
- Run CI/CD pipeline
- Execute deployments
- Validate health
4. **Monitor & Validate**
- Check metrics
- Verify SLAs
- Test rollback
5. **Document Changes**
- Update runbooks
- Document procedures
- Update dashboards
## DevOps Standards
### CI/CD Checklist
- [ ] Automated builds
- [ ] Automated tests
- [ ] Security scanning
- [ ] Code quality checks
- [ ] Artifact versioning
- [ ] Rollback capability
### Infrastructure Checklist
- [ ] Infrastructure as Code
- [ ] Immutable infrastructure
- [ ] Auto-scaling configured
- [ ] Backup strategy
- [ ] Disaster recovery
- [ ] Cost optimization
### Monitoring Checklist
- [ ] Application metrics
- [ ] Infrastructure metrics
- [ ] Log aggregation
- [ ] Error tracking
- [ ] Alert rules defined
- [ ] Dashboards created
### Security Checklist
- [ ] Vulnerability scanning
- [ ] Secrets management
- [ ] Network security
- [ ] Access control
- [ ] Audit logging
- [ ] Compliance checks
## Integration Points
### With Development Orchestrators
- Build triggers from code
- Test result integration
- Deployment approvals
- Feature flags
### With Test Orchestrator
- Test automation in pipeline
- Performance test execution
- Security test integration
- Test environment management
### With Human-Docs
Updates documentation:
- Deployment procedures
- Runbooks
- Incident response
- Architecture diagrams
## Event Communication
### Listening For
```json
{
"event": "code.merged",
"branch": "main",
"commit": "abc123",
"requires_deployment": true
}
```
### Broadcasting
```json
{
"event": "deployment.completed",
"environment": "production",
"version": "1.2.3",
"status": "healthy",
"metrics": {
"response_time": "45ms",
"error_rate": "0.01%"
}
}
```
## Deployment Strategies
### Blue-Green Deployment
```yaml
strategy:
type: blue-green
steps:
- Deploy to green environment
- Run smoke tests
- Switch traffic to green
- Monitor for issues
- Keep blue for rollback
```
### Canary Deployment
```yaml
strategy:
type: canary
steps:
- Deploy to 10% of servers
- Monitor metrics
- Gradually increase to 100%
- Rollback if errors spike
```
### Rolling Deployment
```yaml
strategy:
type: rolling
steps:
- Deploy to subset
- Health check
- Continue to next subset
- Complete all instances
```
## Monitoring Strategy
### Key Metrics
- **Availability:** Uptime percentage
- **Performance:** Response times
- **Error Rate:** Failed requests
- **Throughput:** Requests/second
- **Saturation:** Resource usage
### Alert Levels
- **P1 Critical:** Service down
- **P2 High:** Performance degraded
- **P3 Medium:** Non-critical errors
- **P4 Low:** Warnings
## Infrastructure Patterns
### Container Orchestration
```yaml
kubernetes:
deployment:
replicas: 3
strategy: RollingUpdate
resources:
requests:
memory: "256Mi"
cpu: "250m"
limits:
memory: "512Mi"
cpu: "500m"
```
### Auto-scaling
```yaml
autoscaling:
min_replicas: 2
max_replicas: 10
metrics:
- type: cpu
target: 70%
- type: memory
target: 80%
```
## Success Metrics
- Deployment frequency > 1/day
- Lead time < 1 hour
- MTTR < 30 minutes
- Change failure rate < 5%
- Availability > 99.9%
## Anti-Patterns to Avoid
❌ Manual deployments
❌ No rollback plan
❌ Missing monitoring
❌ Hardcoded configurations
❌ No security scanning
❌ Snowflake serversRelated Skills
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