genkit-infra-expert
Use when deploying Genkit applications to production with Terraform. Trigger with phrases like "deploy genkit terraform", "provision genkit infrastructure", "firebase functions terraform", "cloud run deployment", or "genkit production infrastructure". Provisions Firebase Functions, Cloud Run services, GKE clusters, monitoring dashboards, and CI/CD for AI workflows.
- License 许可
- MIT
- 最近更新
- 2026-08-29
- Stars
- ★ 2
- Forks
- 0
01 前言 Front Matter
- name
- genkit-infra-expert
- license
- MIT
- version
- 1.0.0
- description
- Use when deploying Genkit applications to production with Terraform. Trigger with phrases like "deploy genkit terraform", "provision genkit infrastructure", "firebase functions terraform", "cloud run deployment", or "genkit production infrastructure". Provisions Firebase Functions, Cloud Run services, GKE clusters, monitoring dashboards, and CI/CD for AI workflows.
- allowed-tools
- [ "Read", "Write", "Edit", "Grep", "Glob", "Bash(terraform:*)", "Bash(gcloud:*)" ]
02 资源文件 1
- 脚本scripts/init-terraform.sh888 B
03 SKILL.md 正文
Prerequisites
Before using this skill, ensure:
- Google Cloud project with Firebase enabled
- Terraform 1.0+ installed
- gcloud and firebase CLI authenticated
- Genkit application built and containerized
- API keys for Gemini or other AI models
- Understanding of Genkit flows and deployment options
Instructions
- Choose Deployment Target: Firebase Functions, Cloud Run, or GKE
- Configure Terraform Backend: Set up remote state in GCS
- Define Variables: Project ID, region, Genkit app configuration
- Provision Compute: Deploy functions or containers
- Configure Secrets: Store API keys in Secret Manager
- Set Up Monitoring: Create dashboards for token usage and latency
- Enable Auto-scaling: Configure min/max instances
- Validate Deployment: Test Genkit flows via HTTP endpoints
Output
Firebase Functions:
# {baseDir}/terraform/functions.tf
resource "google_cloudfunctions2_function" "genkit_function" {
name = "genkit-ai-flow"
location = var.region
build_config {
runtime = "nodejs20"
entry_point = "genkitFlow"
}
service_config {
max_instance_count = 100
available_memory = "512Mi"
timeout_seconds = 300
}
}
Cloud Run Service:
resource "google_cloud_run_v2_service" "genkit_service" {
name = "genkit-api"
location = var.region
template {
scaling {
min_instance_count = 1
max_instance_count = 10
}
containers {
image = "gcr.io/${var.project_id}/genkit-app:latest"
resources {
limits = {
cpu = "2"
memory = "1Gi"
}
}
}
}
}
Error Handling
Build Failures
- Error: "Cloud Function build failed"
- Solution: Check package.json dependencies and Node.js runtime version
Cold Start Latency
- Warning: "High latency on first request"
- Solution: Set min_instance_count >= 1 to keep warm instances
Secret Access Denied
- Error: "Permission denied accessing secret"
- Solution: Grant secretAccessor role to Cloud Run/Functions service account
Memory Exceeded
- Error: "Container killed: out of memory"
- Solution: Increase available_memory or optimize Genkit flow memory usage
Resources
- Genkit Deployment: https://genkit.dev/docs/deployment
- Firebase Terraform: https://registry.terraform.io/providers/hashicorp/google/latest
- Genkit examples in {baseDir}/genkit-examples/
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