// 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.
| name | devops-orchestrator |
| description | 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. |
Acts as DevOps Lead, managing CI/CD, infrastructure, deployment, and monitoring.
CI/CD Pipeline Management
Infrastructure as Code
Monitoring & Observability
Context Maintenance
ai-state/active/devops/
โโโ pipelines.json # CI/CD definitions
โโโ infrastructure.json # IaC resources
โโโ monitoring.json # Metrics & alerts
โโโ tasks/ # Active DevOps tasks
ci-cd-skill - Pipeline creation and managementinfrastructure-skill - IaC deploymentmonitoring-skill - Observability setupsecurity-scan-skill - Security scanningdeployment-skill - Release managementcontext:
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"
Receive Task
Prepare Environment
Deploy Application
Monitor & Validate
Document Changes
Updates documentation:
{
"event": "code.merged",
"branch": "main",
"commit": "abc123",
"requires_deployment": true
}
{
"event": "deployment.completed",
"environment": "production",
"version": "1.2.3",
"status": "healthy",
"metrics": {
"response_time": "45ms",
"error_rate": "0.01%"
}
}
strategy:
type: blue-green
steps:
- Deploy to green environment
- Run smoke tests
- Switch traffic to green
- Monitor for issues
- Keep blue for rollback
strategy:
type: canary
steps:
- Deploy to 10% of servers
- Monitor metrics
- Gradually increase to 100%
- Rollback if errors spike
strategy:
type: rolling
steps:
- Deploy to subset
- Health check
- Continue to next subset
- Complete all instances
kubernetes:
deployment:
replicas: 3
strategy: RollingUpdate
resources:
requests:
memory: "256Mi"
cpu: "250m"
limits:
memory: "512Mi"
cpu: "500m"
autoscaling:
min_replicas: 2
max_replicas: 10
metrics:
- type: cpu
target: 70%
- type: memory
target: 80%
โ Manual deployments โ No rollback plan โ Missing monitoring โ Hardcoded configurations โ No security scanning โ Snowflake servers