Conduct periodic access reviews and certifications. Implement access governance and recertification workflows. Use when managing access compliance.
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Manage Compute Engine instances and instance templates. Configure managed instance groups and preemptible VMs. Use when deploying compute resources on GCP.
中文简介正在准备中。当前显示原文说明。
查看安装方法安装前可以查看交给 AI 代理的指令内容。
Deploy, manage, and scale Compute Engine virtual machines on Google Cloud Platform.
gcloud) installed and authenticatedroles/compute.admin or scoped roles for instance managementgcloud auth list
gcloud config set project $PROJECT_ID
gcloud services enable compute.googleapis.com
| Family | Example | vCPUs | Memory | Use Case |
|---|---|---|---|---|
| E2 | e2-micro | 0.25 | 1 GB | Dev/test, microservices |
| E2 | e2-medium | 1 | 4 GB | Light web servers |
| N2 | n2-standard-4 | 4 | 16 GB | General-purpose production |
| N2 | n2-highmem-8 | 8 | 64 GB | In-memory caches, databases |
| C2 | c2-standard-16 | 16 | 64 GB | Compute-intensive, HPC |
# List machine types available in a zone
gcloud compute machine-types list --zones=us-central1-a --filter="name~'e2-'"
# Create a custom machine type (6 vCPUs, 24 GB RAM)
gcloud compute instances create custom-vm \
--custom-cpu=6 --custom-memory=24GB \
--zone=us-central1-a \
--image-family=debian-12 --image-project=debian-cloud
# Production instance with shielded VM and startup script
gcloud compute instances create web-server \
--machine-type=e2-medium \
--zone=us-central1-a \
--image-family=debian-12 \
--image-project=debian-cloud \
--boot-disk-size=20GB \
--boot-disk-type=pd-balanced \
--tags=http-server,https-server \
--labels=env=production,team=backend \
--metadata=enable-oslogin=TRUE \
--shielded-secure-boot \
--shielded-vtpm \
--shielded-integrity-monitoring
# Instance with a startup script and service account
gcloud compute instances create app-server \
--machine-type=e2-standard-2 \
--zone=us-central1-a \
--image-family=ubuntu-2204-lts \
--image-project=ubuntu-os-cloud \
--boot-disk-size=50GB \
--metadata-from-file=startup-script=startup.sh \
--service-account=app-sa@${PROJECT_ID}.iam.gserviceaccount.com \
--scopes=cloud-platform
# Instance with an additional data disk
gcloud compute instances create db-server \
--machine-type=n2-highmem-4 \
--zone=us-central1-a \
--image-family=debian-12 --image-project=debian-cloud \
--boot-disk-size=20GB \
--create-disk=name=data-disk,size=200GB,type=pd-ssd,auto-delete=no
#!/bin/bash
# startup.sh - runs on first boot and every reboot
set -euo pipefail
apt-get update && apt-get install -y nginx
systemctl enable nginx && systemctl start nginx
curl -X PUT -H "Metadata-Flavor: Google" \
"http://metadata.google.internal/computeMetadata/v1/instance/guest-attributes/startup/status" \
-d "complete"
# Create an instance template
gcloud compute instance-templates create web-template \
--machine-type=e2-medium \
--image-family=debian-12 --image-project=debian-cloud \
--boot-disk-size=20GB --tags=http-server \
--metadata-from-file=startup-script=startup.sh
# Create a regional managed instance group (MIG) with health check
gcloud compute health-checks create http http-health-check \
--port=80 --request-path=/healthz \
--check-interval=10s --timeout=5s \
--healthy-threshold=2 --unhealthy-threshold=3
gcloud compute instance-groups managed create web-mig \
--template=web-template --size=3 \
--region=us-central1 \
--health-check=http-health-check --initial-delay=120
# Configure autoscaling
gcloud compute instance-groups managed set-autoscaling web-mig \
--region=us-central1 \
--min-num-replicas=2 --max-num-replicas=10 \
--target-cpu-utilization=0.65 --cool-down-period=90
# Rolling update to a new template
gcloud compute instance-groups managed rolling-action start-update web-mig \
--version=template=web-template-v2 \
--region=us-central1 --max-surge=3 --max-unavailable=0
# Spot VM (recommended over legacy preemptible)
gcloud compute instances create spot-worker \
--machine-type=n2-standard-8 \
--zone=us-central1-a \
--image-family=debian-12 --image-project=debian-cloud \
--provisioning-model=SPOT \
--instance-termination-action=STOP
# Spot instance template for batch MIG
gcloud compute instance-templates create batch-template \
--machine-type=n2-standard-4 \
--image-family=debian-12 --image-project=debian-cloud \
--provisioning-model=SPOT \
--instance-termination-action=DELETE
# Create a snapshot
gcloud compute disks snapshot web-server \
--zone=us-central1-a \
--snapshot-names=web-server-snap-$(date +%Y%m%d)
# Scheduled snapshot policy
gcloud compute resource-policies create snapshot-schedule daily-backup \
--region=us-central1 --max-retention-days=14 \
--daily-schedule --start-time=03:00
gcloud compute disks add-resource-policies web-server \
--zone=us-central1-a --resource-policies=daily-backup
# Create a custom image from an instance
gcloud compute instances stop web-server --zone=us-central1-a
gcloud compute images create web-golden-image \
--source-disk=web-server --source-disk-zone=us-central1-a \
--family=web-server --labels=version=v1
resource "google_compute_instance" "web" {
name = "web-server"
machine_type = "e2-medium"
zone = "us-central1-a"
tags = ["http-server", "https-server"]
boot_disk {
initialize_params {
image = "debian-cloud/debian-12"
size = 20
type = "pd-balanced"
}
}
network_interface {
subnetwork = google_compute_subnetwork.main.id
access_config {}
}
metadata_startup_script = file("${path.module}/startup.sh")
service_account {
email = google_service_account.app.email
scopes = ["cloud-platform"]
}
shielded_instance_config {
enable_secure_boot = true
enable_vtpm = true
enable_integrity_monitoring = true
}
}
resource "google_compute_instance_template" "web" {
name_prefix = "web-"
machine_type = "e2-medium"
disk {
source_image = "debian-cloud/debian-12"
auto_delete = true
boot = true
disk_size_gb = 20
}
network_interface {
subnetwork = google_compute_subnetwork.main.id
}
lifecycle { create_before_destroy = true }
}
resource "google_compute_region_instance_group_manager" "web" {
name = "web-mig"
base_instance_name = "web"
region = "us-central1"
version {
instance_template = google_compute_instance_template.web.id
}
target_size = 3
named_port { name = "http"; port = 80 }
auto_healing_policies {
health_check = google_compute_health_check.http.id
initial_delay_sec = 120
}
}
resource "google_compute_region_autoscaler" "web" {
name = "web-autoscaler"
region = "us-central1"
target = google_compute_region_instance_group_manager.web.id
autoscaling_policy {
min_replicas = 2
max_replicas = 10
cooldown_period = 90
cpu_utilization { target = 0.65 }
}
}
# SSH into an instance
gcloud compute ssh web-server --zone=us-central1-a
# List all instances with status
gcloud compute instances list \
--format="table(name,zone,status,machineType.basename())"
# Stop / start / resize
gcloud compute instances stop web-server --zone=us-central1-a
gcloud compute instances set-machine-type web-server \
--machine-type=e2-standard-4 --zone=us-central1-a
gcloud compute instances start web-server --zone=us-central1-a
# View serial port output (debug startup scripts)
gcloud compute instances get-serial-port-output web-server --zone=us-central1-a
| Symptom | Cause | Fix |
|---|---|---|
| Instance stuck in STAGING | Quota exceeded or resource unavailable | Check quota with gcloud compute project-info describe; try another zone |
| Startup script not running | Syntax errors or wrong metadata key | Check serial output; ensure key is startup-script not startup_script |
| Cannot SSH | Firewall blocks port 22 or OS Login misconfigured | Add firewall rule for tcp:22; verify enable-oslogin metadata |
| Preempted too often | Zone resource pressure | Use Spot VM with STOP action; spread across zones in a MIG |
| Disk out of space | Boot disk too small | Use gcloud compute disks resize; enable --storage-auto-increase for data disks |
| MIG not healing | Health check misconfigured or initial delay too short | Verify health check path returns 200; increase --initial-delay |
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Conduct periodic access reviews and certifications. Implement access governance and recertification workflows. Use when managing access compliance.
中文简介正在准备中。当前显示原文说明。
Build automated evaluation suites for AI agents using golden datasets, rubrics, and regression gates. Use when shipping agent features, validating prompt changes, or gating deployments on quality.
中文简介正在准备中。当前显示原文说明。
Instrument AI agents with tracing, token metrics, latency, and cost visibility. Use for reliability and debugging.
中文简介正在准备中。当前显示原文说明。
Secure AI agents against prompt injection, tool abuse, and data exfiltration with defense-in-depth controls. Use when building, deploying, or hardening agentic AI systems that invoke tools, access data, or interact with production infrastructure.
中文简介正在准备中。当前显示原文说明。
Secure AI coding agents (Claude Code, Cursor, Codex, Copilot) with permission boundaries, secret protection, code review gates, and safe sandbox configurations for team environments.
中文简介正在准备中。当前显示原文说明。
Use service mesh patterns for AI inference traffic management, mTLS, canary releases, policy enforcement, and cross-cluster resilience.
中文简介正在准备中。当前显示原文说明。