gcp-compute
Manage Compute Engine instances and instance templates. Configure managed instance groups and preemptible VMs. Use when deploying compute resources on GCP.
What this skill does
# GCP Compute Engine
Deploy, manage, and scale Compute Engine virtual machines on Google Cloud Platform.
## When to Use
- Deploying web servers, application backends, or batch-processing workloads on GCP
- Running workloads that need full OS-level control (unlike Cloud Run or App Engine)
- Creating managed instance groups for auto-healing and auto-scaling behind a load balancer
- Provisioning GPU-attached VMs for ML training or rendering pipelines
- Cost-optimizing non-critical workloads with preemptible or spot VMs
## Prerequisites
- Google Cloud SDK (`gcloud`) installed and authenticated
- A GCP project with the Compute Engine API enabled
- IAM role `roles/compute.admin` or scoped roles for instance management
```bash
gcloud auth list
gcloud config set project $PROJECT_ID
gcloud services enable compute.googleapis.com
```
## Machine Types Reference
| Family | Example | vCPUs | Memory | Use Case |
|--------|---------|-------|--------|----------|
| E2 | e2-micro | 0.25 | 1 GB | Dev/test, microservices |
| E2 | e2-medium | 1 | 4 GB | Light web servers |
| N2 | n2-standard-4 | 4 | 16 GB | General-purpose production |
| N2 | n2-highmem-8 | 8 | 64 GB | In-memory caches, databases |
| C2 | c2-standard-16 | 16 | 64 GB | Compute-intensive, HPC |
```bash
# List machine types available in a zone
gcloud compute machine-types list --zones=us-central1-a --filter="name~'e2-'"
# Create a custom machine type (6 vCPUs, 24 GB RAM)
gcloud compute instances create custom-vm \
--custom-cpu=6 --custom-memory=24GB \
--zone=us-central1-a \
--image-family=debian-12 --image-project=debian-cloud
```
## Create an Instance
```bash
# Production instance with shielded VM and startup script
gcloud compute instances create web-server \
--machine-type=e2-medium \
--zone=us-central1-a \
--image-family=debian-12 \
--image-project=debian-cloud \
--boot-disk-size=20GB \
--boot-disk-type=pd-balanced \
--tags=http-server,https-server \
--labels=env=production,team=backend \
--metadata=enable-oslogin=TRUE \
--shielded-secure-boot \
--shielded-vtpm \
--shielded-integrity-monitoring
# Instance with a startup script and service account
gcloud compute instances create app-server \
--machine-type=e2-standard-2 \
--zone=us-central1-a \
--image-family=ubuntu-2204-lts \
--image-project=ubuntu-os-cloud \
--boot-disk-size=50GB \
--metadata-from-file=startup-script=startup.sh \
--service-account=app-sa@${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
```
## Startup Script Example
```bash
#!/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"
```
## Instance Templates and Managed Instance Groups
```bash
# 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
```
## Preemptible and Spot VMs
```bash
# 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
```
## Snapshots and Images
```bash
# Create a snapshot
gcloud compute disks snapshot web-server \
--zone=us-central1-a \
--snapshot-names=web-server-snap-$(date +%Y%m%d)
# Scheduled snapshot policy
gcloud compute resource-policies create snapshot-schedule daily-backup \
--region=us-central1 --max-retention-days=14 \
--daily-schedule --start-time=03:00
gcloud compute disks add-resource-policies web-server \
--zone=us-central1-a --resource-policies=daily-backup
# Create a custom image from an instance
gcloud compute instances stop web-server --zone=us-central1-a
gcloud compute images create web-golden-image \
--source-disk=web-server --source-disk-zone=us-central1-a \
--family=web-server --labels=version=v1
```
## Terraform Configuration
```hcl
resource "google_compute_instance" "web" {
name = "web-server"
machine_type = "e2-medium"
zone = "us-central1-a"
tags = ["http-server", "https-server"]
boot_disk {
initialize_params {
image = "debian-cloud/debian-12"
size = 20
type = "pd-balanced"
}
}
network_interface {
subnetwork = google_compute_subnetwork.main.id
access_config {}
}
metadata_startup_script = file("${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 }
}
}
```
## Common Operations
```bash
# 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 instanRelated in Cloud & DevOps
appbuilder-action-scaffolder
IncludedCreate, implement, deploy, and debug Adobe Runtime actions with consistent layout, validation, and error handling. Use this skill whenever the user needs to add actions to an App Builder project, understand action structure (params, response format, web/raw actions), configure actions in the manifest, use App Builder SDKs (State, Files, Events, database), deploy and invoke actions via CLI, debug action issues, or implement patterns such as webhook receivers, custom event providers, journaling consumers, large payload redirects, action sequence pipelines, and Asset Compute workers. Also trigger when users mention serverless functions in Adobe context, action logging, IMS authentication for actions, or cron-style scheduled actions.
orchestrating-datacloud
IncludedSalesforce Data Cloud product orchestrator for connect→prepare→harmonize→segment→act workflows. Use this skill when the user needs a multi-step Data Cloud pipeline, cross-phase troubleshooting, or data space and data kit management. TRIGGER when: user needs a multi-step Data Cloud pipeline, asks to set up or troubleshoot Data Cloud across phases, manages data spaces or data kits, or wants a cross-phase sf data360 workflow. DO NOT TRIGGER when: work is isolated to a single phase (use the matching phase-specific skill), the task is STDM/session tracing/parquet telemetry (use observing-agentforce), standard CRM SOQL (use querying-soql), or Apex implementation (use generating-apex).
github-project-automation
IncludedAutomate GitHub repository setup with CI/CD workflows, issue templates, Dependabot, and CodeQL security scanning. Includes 12 production-tested workflows and prevents 18 errors: YAML syntax, action pinning, and configuration. Use when: setting up GitHub Actions CI/CD, creating issue/PR templates, enabling Dependabot or CodeQL scanning, deploying to Cloudflare Workers, implementing matrix testing, or troubleshooting YAML indentation, action version pinning, secrets syntax, runner versions, or CodeQL configuration. Keywords: github actions, github workflow, ci/cd, issue templates, pull request templates, dependabot, codeql, security scanning, yaml syntax, github automation, repository setup, workflow templates, github actions matrix, secrets management, branch protection, codeowners, github projects, continuous integration, continuous deployment, workflow syntax error, action version pinning, runner version, github context, yaml indentation error
sf-datacloud
IncludedSalesforce Data Cloud product orchestrator for connect→prepare→harmonize→segment→act workflows. TRIGGER when: user needs a multi-step Data Cloud pipeline, asks to set up or troubleshoot Data Cloud across phases, manages data spaces or data kits, or wants a cross-phase `sf data360` workflow. DO NOT TRIGGER when: work is isolated to a single phase (use the matching sf-datacloud-* skill), the task is STDM/session tracing/parquet telemetry (use sf-ai-agentforce-observability), standard CRM SOQL (use sf-soql), or Apex implementation (use sf-apex).
fabric-cli
IncludedUse this skill for Fabric.so CLI workflows with the `fabric` terminal command: diagnose/install/login, search or browse a Fabric library, save notes/links/files, create folders, ask the Fabric AI assistant, manage tasks/workspaces, generate shell completion, check subscription usage, produce JSON output, and use Fabric as persistent agent memory. Do not use for Microsoft Fabric/Azure/Power BI `fab`, Daniel Miessler's Fabric framework, Python Fabric SSH, Fabric.js, or textile/fashion fabric.
lark
IncludedLark/Feishu CLI skills: lark-cli operations for docs, markdown, sheets, base, calendar, im, mail, task, okr, drive, wiki, slides, whiteboard, apps, approval, attendance, contact, vc, minutes, event. Use when the user needs to operate Lark/Feishu resources via lark-cli, send messages, manage documents, spreadsheets, calendars, tasks, OKRs, deploy web pages, or any Feishu/Lark workspace operations.