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gcp-cloud-functions skill

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This skill helps you deploy and manage event-driven Google Cloud Functions with HTTP, Pub/Sub, and storage triggers, IAM roles, and monitoring.

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SKILL.md
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---
name: gcp-cloud-functions
description: Deploy serverless functions on Google Cloud Platform with triggers, IAM roles, environment variables, and monitoring. Use for event-driven computing on GCP.
---

# GCP Cloud Functions

## Overview

Google Cloud Functions enables event-driven serverless computing on Google Cloud Platform. Build functions with automatic scaling, integrated security, and seamless integration with Google Cloud services for rapid development.

## When to Use

- HTTP APIs and webhooks
- Pub/Sub message processing
- Storage bucket events
- Firestore database triggers
- Cloud Scheduler jobs
- Real-time data processing
- Image and video processing
- Data pipeline orchestration

## Implementation Examples

### 1. **Cloud Function Creation with gcloud CLI**

```bash
# Install Google Cloud SDK
curl https://sdk.cloud.google.com | bash
exec -l $SHELL

# Initialize and authenticate
gcloud init
gcloud auth application-default login

# Set project
gcloud config set project MY_PROJECT_ID

# Create service account
gcloud iam service-accounts create cloud-function-sa \
  --display-name "Cloud Function Service Account"

# Grant permissions
gcloud projects add-iam-policy-binding MY_PROJECT_ID \
  --member="serviceAccount:cloud-function-sa@MY_PROJECT_ID.iam.gserviceaccount.com" \
  --role="roles/cloudfunctions.invoker"

# Deploy HTTP function
gcloud functions deploy my-http-function \
  --gen2 \
  --runtime nodejs18 \
  --region us-central1 \
  --source ./src \
  --entry-point httpHandler \
  --trigger-http \
  --allow-unauthenticated \
  --timeout 60 \
  --memory 256MB \
  --max-instances 100 \
  --set-env-vars NODE_ENV=production,API_KEY=xxx \
  --service-account cloud-function-sa@MY_PROJECT_ID.iam.gserviceaccount.com

# Deploy Pub/Sub function
gcloud functions deploy my-pubsub-function \
  --gen2 \
  --runtime nodejs18 \
  --region us-central1 \
  --source ./src \
  --entry-point pubsubHandler \
  --trigger-topic my-topic \
  --memory 256MB \
  --timeout 300 \
  --service-account cloud-function-sa@MY_PROJECT_ID.iam.gserviceaccount.com

# Deploy Cloud Storage function
gcloud functions deploy my-storage-function \
  --gen2 \
  --runtime nodejs18 \
  --region us-central1 \
  --source ./src \
  --entry-point storageHandler \
  --trigger-bucket my-bucket \
  --trigger-location us-central1 \
  --timeout 60 \
  --service-account cloud-function-sa@MY_PROJECT_ID.iam.gserviceaccount.com

# List functions
gcloud functions list

# Get function details
gcloud functions describe my-http-function --gen2 --region us-central1

# Call function
gcloud functions call my-http-function \
  --region us-central1 \
  --data '{"name":"John"}'

# View logs
gcloud functions logs read my-http-function --limit 50 --gen2 --region us-central1

# Delete function
gcloud functions delete my-http-function --gen2 --region us-central1
```

### 2. **Cloud Functions Implementation (Node.js)**

```javascript
// HTTP Trigger Function
exports.httpHandler = async (req, res) => {
  try {
    // Enable CORS
    res.set('Access-Control-Allow-Origin', '*');
    res.set('Access-Control-Allow-Methods', 'GET, POST, OPTIONS');

    if (req.method === 'OPTIONS') {
      res.status(204).send('');
      return;
    }

    // Parse request
    const { name } = req.query;

    if (!name) {
      return res.status(400).json({ error: 'Name is required' });
    }

    // Log with Cloud Logging
    console.log(JSON.stringify({
      severity: 'INFO',
      message: 'Processing request',
      name: name,
      requestId: req.id
    }));

    // Business logic
    const response = {
      message: `Hello ${name}!`,
      timestamp: new Date().toISOString()
    };

    res.status(200).json(response);
  } catch (error) {
    console.error(JSON.stringify({
      severity: 'ERROR',
      message: error.message,
      stack: error.stack
    }));

    res.status(500).json({ error: 'Internal server error' });
  }
};

// Pub/Sub Trigger Function
exports.pubsubHandler = async (message, context) => {
  try {
    // Decode Pub/Sub message
    const pubsubMessage = message.data
      ? Buffer.from(message.data, 'base64').toString()
      : null;

    console.log('Received message:', pubsubMessage);

    // Parse message
    const data = JSON.parse(pubsubMessage);

    // Process message asynchronously
    await processMessage(data);

    console.log('Message processed successfully');
  } catch (error) {
    console.error('Error processing message:', error);
    throw error; // Function will retry
  }
};

// Cloud Storage Trigger Function
exports.storageHandler = async (file, context) => {
  try {
    const { name, bucket } = file;

    console.log(JSON.stringify({
      message: 'Processing storage event',
      bucket: bucket,
      file: name,
      eventId: context.eventId,
      eventType: context.eventType
    }));

    // Check file type
    if (!name.endsWith('.jpg') && !name.endsWith('.png')) {
      console.log('Skipping non-image file');
      return;
    }

    // Process image
    await processImage(bucket, name);

    console.log('Image processed successfully');
  } catch (error) {
    console.error('Error processing file:', error);
    throw error;
  }
};

// Cloud Scheduler (CRON) Function
exports.cronHandler = async (req, res) => {
  try {
    console.log('Scheduled job started');

    // Run batch processing
    await performBatchJob();

    res.status(200).json({ message: 'Batch job completed' });
  } catch (error) {
    console.error('Error in batch job:', error);
    res.status(500).json({ error: error.message });
  }
};

// Helper functions
async function processMessage(data) {
  // Business logic
  return new Promise(resolve => {
    setTimeout(() => resolve(), 1000);
  });
}

async function processImage(bucket, filename) {
  // Use Cloud Vision API or similar
  return true;
}

async function performBatchJob() {
  // Batch processing logic
  return true;
}
```

### 3. **Terraform Cloud Functions Configuration**

```hcl
# cloud-functions.tf
terraform {
  required_providers {
    google = {
      source  = "hashicorp/google"
      version = "~> 5.0"
    }
  }
}

provider "google" {
  project = var.project_id
  region  = var.region
}

variable "project_id" {
  description = "GCP Project ID"
}

variable "region" {
  default = "us-central1"
}

# Service account for functions
resource "google_service_account" "function_sa" {
  account_id   = "cloud-function-sa"
  display_name = "Cloud Function Service Account"
}

# Grant invoker role
resource "google_project_iam_member" "function_invoker" {
  project = var.project_id
  role    = "roles/cloudfunctions.invoker"
  member  = "serviceAccount:${google_service_account.function_sa.email}"
}

# Grant Cloud Logging role
resource "google_project_iam_member" "function_logs" {
  project = var.project_id
  role    = "roles/logging.logWriter"
  member  = "serviceAccount:${google_service_account.function_sa.email}"
}

# Source archive bucket
resource "google_storage_bucket" "function_source" {
  name     = "${var.project_id}-function-source"
  location = var.region
}

# Upload function code
resource "google_storage_bucket_object" "function_zip" {
  name   = "function-${data.archive_file.function.output_md5}.zip"
  bucket = google_storage_bucket.function_source.name
  source = data.archive_file.function.output_path
}

# Archive function code
data "archive_file" "function" {
  type        = "zip"
  source_dir  = "${path.module}/src"
  output_path = "${path.module}/function.zip"
}

# HTTP Cloud Function
resource "google_cloudfunctions2_function" "http_function" {
  name        = "my-http-function"
  location    = var.region
  description = "HTTP trigger function"

  build_config {
    runtime           = "nodejs18"
    entry_point       = "httpHandler"
    source {
      storage_source {
        bucket = google_storage_bucket.function_source.name
        object = google_storage_bucket_object.function_zip.name
      }
    }
  }

  service_config {
    max_instance_count = 100
    available_memory_mb = 256
    timeout_seconds = 60
    service_account_email = google_service_account.function_sa.email

    environment_variables = {
      NODE_ENV = "production"
      API_KEY  = "your-api-key"
    }
  }

  labels = {
    env = "production"
  }
}

# Allow public HTTP access
resource "google_cloudfunctions2_function_iam_member" "http_public" {
  cloud_function = google_cloudfunctions2_function.http_function.name
  role           = "roles/cloudfunctions.invoker"
  member         = "allUsers"
}

# Pub/Sub topic
resource "google_pubsub_topic" "messages" {
  name = "message-topic"
}

# Pub/Sub Cloud Function
resource "google_cloudfunctions2_function" "pubsub_function" {
  name        = "my-pubsub-function"
  location    = var.region
  description = "Pub/Sub trigger function"

  build_config {
    runtime           = "nodejs18"
    entry_point       = "pubsubHandler"
    source {
      storage_source {
        bucket = google_storage_bucket.function_source.name
        object = google_storage_bucket_object.function_zip.name
      }
    }
  }

  service_config {
    max_instance_count = 100
    available_memory_mb = 256
    timeout_seconds = 300
    service_account_email = google_service_account.function_sa.email
  }

  event_trigger {
    trigger_region = var.region
    event_type     = "google.cloud.pubsub.topic.publish"
    pubsub_topic   = google_pubsub_topic.messages.id
  }
}

# Cloud Storage bucket
resource "google_storage_bucket" "uploads" {
  name     = "${var.project_id}-uploads"
  location = var.region
}

# Cloud Storage trigger function
resource "google_cloudfunctions2_function" "storage_function" {
  name        = "my-storage-function"
  location    = var.region
  description = "Cloud Storage trigger function"

  build_config {
    runtime           = "nodejs18"
    entry_point       = "storageHandler"
    source {
      storage_source {
        bucket = google_storage_bucket.function_source.name
        object = google_storage_bucket_object.function_zip.name
      }
    }
  }

  service_config {
    max_instance_count = 50
    available_memory_mb = 256
    timeout_seconds = 60
    service_account_email = google_service_account.function_sa.email
  }

  event_trigger {
    trigger_region = var.region
    event_type     = "google.storage.object.finalize"
    resource       = google_storage_bucket.uploads.name
  }
}

# Cloud Scheduler job (CRON)
resource "google_cloud_scheduler_job" "batch_job" {
  name             = "batch-job-scheduler"
  description      = "Scheduled batch job"
  schedule         = "0 2 * * *" # Daily at 2 AM
  time_zone        = "UTC"
  attempt_deadline = "320s"
  region           = var.region

  retry_config {
    retry_count = 1
  }

  http_target {
    uri        = google_cloudfunctions2_function.http_function.service_config[0].uri
    http_method = "POST"

    headers = {
      "Content-Type" = "application/json"
    }

    body = base64encode(jsonencode({
      job_type = "batch"
    }))

    oidc_token {
      service_account_email = google_service_account.function_sa.email
    }
  }
}

# Cloud Logging sink
resource "google_logging_project_sink" "function_logs" {
  name        = "cloud-function-logs"
  destination = "logging.googleapis.com/projects/${var.project_id}/logs/my-http-function"

  filter = "resource.type=\"cloud_function\" AND resource.labels.function_name=\"my-http-function\""
}

# Monitoring alert
resource "google_monitoring_alert_policy" "function_errors" {
  display_name = "Cloud Function Error Rate"
  combiner     = "OR"

  conditions {
    display_name = "Error rate threshold"

    condition_threshold {
      filter          = "metric.type=\"cloudfunctions.googleapis.com/function/error_count\" AND resource.type=\"cloud_function\""
      duration        = "60s"
      comparison      = "COMPARISON_GT"
      threshold_value = 10
      aggregations {
        alignment_period    = "60s"
        per_series_aligner  = "ALIGN_RATE"
      }
    }
  }
}

output "http_function_url" {
  value = google_cloudfunctions2_function.http_function.service_config[0].uri
}
```

## Best Practices

### ✅ DO
- Use service accounts with least privilege
- Store secrets in Secret Manager
- Implement proper error handling
- Use environment variables for configuration
- Monitor with Cloud Logging and Cloud Monitoring
- Set appropriate memory and timeout
- Use event filters to reduce invocations
- Implement idempotent functions

### ❌ DON'T
- Store secrets in code
- Use default service account
- Create long-running functions
- Ignore error handling
- Deploy without testing
- Use unauthenticated access for sensitive functions

## Monitoring

- Cloud Logging for application logs
- Cloud Monitoring for metrics
- Error Reporting for error tracking
- Cloud Trace for distributed tracing
- Cloud Profiler for performance analysis

## Resources

- [Google Cloud Functions Documentation](https://cloud.google.com/functions/docs)
- [Cloud Functions Best Practices](https://cloud.google.com/functions/docs/bestpractices/retries)
- [Cloud Functions Terraform Provider](https://registry.terraform.io/providers/hashicorp/google/latest/docs/resources/cloudfunctions2_function)

Overview

This skill helps you deploy and manage Google Cloud Functions for event-driven, serverless workloads on GCP. It covers HTTP, Pub/Sub, Cloud Storage, and scheduled triggers, plus IAM, environment variables, and monitoring. Use it to build scalable functions with Terraform or gcloud and idiomatic Node.js handlers.

How this skill works

It automates function creation, configuration, and lifecycle tasks: creating service accounts, assigning IAM roles, packaging and uploading source, and deploying Cloud Functions (Gen2) with specific triggers. It also configures logging, monitoring, alerting, and scheduler integrations so you can observe and secure production functions. Example implementations include gcloud CLI commands, Node.js function templates, and Terraform resources.

When to use it

  • Expose lightweight HTTP APIs or webhooks without managing servers
  • Process Pub/Sub messages for asynchronous pipelines
  • React to Cloud Storage object events (uploads, deletes)
  • Run scheduled jobs via Cloud Scheduler and HTTP triggers
  • Handle Firestore or other managed-service event triggers
  • Prototype or scale event-driven image, video, or data processing

Best practices

  • Use least-privilege service accounts and avoid the default account
  • Store secrets in Secret Manager and reference via environment variables
  • Set appropriate memory and timeout to control cost and performance
  • Implement idempotent handlers and robust error handling with retries
  • Monitor with Cloud Logging, Monitoring, and set alerting for error rates
  • Use event filters and max-instance limits to reduce noisy invocations

Example use cases

  • Deploy an HTTP function as a public webhook receiver for a SaaS integration
  • Create a Pub/Sub consumer to process analytics events and update downstream systems
  • Trigger image resizing and thumbnail generation when files land in a storage bucket
  • Schedule nightly batch jobs via Cloud Scheduler calling a secured HTTP function
  • Use Terraform to manage function infrastructure, IAM bindings, and monitoring as code

FAQ

How do I secure an HTTP Cloud Function?

Use a dedicated service account, require IAM invoker role, and avoid allUsers; for scheduled calls use OIDC tokens from Cloud Scheduler.

Where should I store API keys and secrets?

Store secrets in Secret Manager and inject them into functions via environment variables or runtime access.

When should I use Cloud Functions Gen2?

Use Gen2 for better scaling controls, VPC connector support, and tighter integration with Cloud Run features; Gen2 is recommended for new deployments.