gcp-cloud-functions

# GCP Cloud Functions Build and deploy event-driven serverless applications with Google Cloud Functions (Gen1 and Gen2). ## When to Use - Processing webhooks, API endpoints, or lightweight HTTP backends - Reacting to events from Pub/Sub, Cloud Storage, Firestore, or Eventarc - Running scheduled tasks (cron) without maintaining a server - Building data-processing pipelines triggered by file uploads - Prototyping microservices before committing to Cloud Run or GKE ## Prerequisites - Google Cloud SDK (`gcloud`) installed and authenticated - APIs enabled: Cloud Functions, Cloud Build, Artifact Registry, Cloud Run (Gen2) - IAM role `roles/cloudfunctions.developer` (or `roles/run.developer` for Gen2) ```bash gcloud services enable cloudfunctions.googleapis.com cloudbuild.googleapis.com \ artifactregistry.googleapis.com run.googleapis.com eventarc.googleapis.com ``` ## Gen1 vs Gen2 Comparison | Feature | Gen1 | Gen2 (recommended) | |---------|------|---------------------| | Runtime | Cloud Functions infra | Built on Cloud Run | | Max timeout | 9 minutes | 60 minutes | | Max memory | 8 GB | 32 GB | | Concurrency | 1 request/instance | Up to 1000/instance | | Traffic splitting | No | Yes | | Eventarc triggers | No | Yes | ## Deploy an HTTP Function (Gen2) ```bash # Python HTTP function gcloud functions deploy hello-http \ --gen2 --region=us-central1 --runtime=python312 \ --trigger-http --allow-unauthenticated \ --entry-point=hello_http \ --memory=256Mi --timeout=60s \ --min-instances=0 --max-instances=100 \ --set-env-vars=APP_ENV=production --source=. # Node.js HTTP function gcloud functions deploy hello-node \ --gen2 --region=us-central1 --runtime=nodejs20 \ --trigger-http --allow-unauthenticated \ --entry-point=helloNode --memory=256Mi --source=. ``` ## Deploy a Pub/Sub Triggered Function ```bash gcloud pubsub topics create order-events gcloud functions deploy process-order \ --gen2 --region=us-central1 --runtime=python312 \ --trigger-topic=order-events \ --entry-point=process_order \ --memory=512Mi --timeout=120s --retry \ --service-account=order-processor@${PROJECT_ID}.iam.gserviceaccount.com \ --source=. ``` ## Deploy a Cloud Storage Triggered Function ```bash gcloud functions deploy process-upload \ --gen2 --region=us-central1 --runtime=python312 \ --trigger-event-filters="type=google.cloud.storage.object.v1.finalized" \ --trigger-event-filters="bucket=my-upload-bucket" \ --entry-point=process_upload \ --memory=1Gi --timeout=300s --source=. ``` ## Deploy a Scheduled Function ```bash gcloud functions deploy daily-cleanup \ --gen2 --region=us-central1 --runtime=python312 \ --trigger-http --no-allow-unauthenticated \ --entry-point=daily_cleanup --source=. gcloud scheduler jobs create http daily-cleanup-job \ --schedule="0 2 * * *" \ --uri="https://us-central1-${PROJECT_ID}.cloudfunctions.net/daily-cleanup" \ --http-method=POST \ --oidc-service-account-email=scheduler-sa@${PROJECT_ID}.iam.gserviceaccount.com \ --location=us-central1 ``` ## Python Function Examples ```python # main.py import functions_framework import base64, json from flask import jsonify from google.cloud import firestore @functions_framework.http def hello_http(request): """HTTP Cloud Function.""" name = request.args.get("name", "World") return jsonify({"message": f"Hello, {name}!", "status": "ok"}), 200 @functions_framework.cloud_event def process_order(cloud_event): """Triggered by a Pub/Sub message.""" data = base64.b64decode(cloud_event.data["message"]["data"]).decode("utf-8") order = json.loads(data) db = firestore.Client() db.collection("orders").document(order["id"]).set({ "status": "processing", "items": order["items"], "total": order["total"], }) @functions_framework.cloud_event def process_upload(cloud_event): """Triggered when a file is uploaded to Cloud Storage.""" data = cloud_event.data bucket_name, file_name = data["bucket"], data["name"] if not file_name.lower().endswith((".png", ".jpg", ".jpeg")): return from google.cloud import vision client = vision.ImageAnnotatorClient() image = vision.Image(source=vision.ImageSource( gcs_image_uri=f"gs://{bucket_name}/{file_name}")) labels = [l.description for l in client.label_detection(image=image).label_annotations] print(f"Labels for {file_name}: {labels}") ``` ``` # requirements.txt functions-framework==3.* google-cloud-firestore==2.* google-cloud-storage==2.* google-cloud-vision==3.* flask>=2.0 ``` ## Node.js Function Examples ```javascript // index.js const functions = require("@google-cloud/functions-framework"); functions.http("helloNode", (req, res) => { const name = req.query.name || "World"; res.json({ message: `Hello, ${name}!`, status: "ok" }); }); functions.cloudEvent("processMessage", (cloudEvent) => { const data = Buffer.from(cloudEvent.data.message.data, "base64").toString(); console.log(`Processing: ${JSON.parse(data)}`); }); ``` ## Managing Deployed Functions ```bash gcloud functions list --gen2 --region=us-central1 gcloud functions describe hello-http --gen2 --region=us-central1 gcloud functions logs read hello-http --gen2 --region=us-central1 --limit=50 gcloud functions delete hello-http --gen2 --region=us-central1 --quiet # Update env vars without redeploying code gcloud functions deploy hello-http --gen2 --region=us-central1 \ --update-env-vars=APP_ENV=staging # Test locally before deploying functions-framework --target=hello_http --port=8080 ``` ## Terraform Configuration ```hcl resource "google_cloudfunctions2_function" "api" { name = "hello-http" location = "us-central1" build_config { runtime = "python312" entry_point = "hello_http" source { storage_source { bucket = google_storage_bucket.source.name object = google_storage_bucket_object.source.name } } } service_config { min_instance_count = 0 max_instance_count = 100 available_memory = "256Mi" timeout_seconds = 60 service_account_email = google_service_account.fn.email environment_variables = { APP_ENV = "production" } } } resource "google_cloud_run_service_iam_member" "invoker" { location = google_cloudfunctions2_function.api.location service = google_cloudfunctions2_function.api.name role = "roles/run.invoker" member = "allUsers" } resource "google_cloudfunctions2_function" "processor" { name = "process-order" location = "us-central1" build_config { runtime = "python312" entry_point = "process_order" source { storage_source { bucket = google_storage_bucket.source.name object = google_storage_bucket_object.source.name } } } service_config { max_instance_count = 50 available_memory = "512Mi" timeout_seconds = 120 service_account_email = google_service_account.fn.email } event_trigger { trigger_region = "us-central1" event_type = "google.cloud.pubsub.topic.v1.messagePublished" pubsub_topic = google_pubsub_topic.orders.id retry_policy = "RETRY_POLICY_RETRY" } } ``` ## Troubleshooting | Symptom | Cause | Fix | |---------|-------|-----| | `PERMISSION_DENIED` on deploy | Missing Cloud Build or Artifact Registry perms | Grant `roles/cloudbuild.builds.builder` to Cloud Build SA | | Function deploys but returns 403 | Missing `roles/run.invoker` for Gen2 | Add `--allow-unauthenticated` or grant invoker role | | Cold start latency > 5s | Large dependencies or no min instances | Set `--min-instances=1`; reduce deps; use lazy imports | | Pub/Sub messages redelivered | Function errors or times out | Increase `--timeout`; fix error handling; add dead-letter topic | | `Build failed` during deploy | Syntax error or missing dependency | Check `gcloud builds log`; verify requirements.txt | | Cannot connect to VPC resource | Function not on VPC connector | Add `--vpc-connector=my-connector` to deploy | ## Related Skills - **gcp-networking** - VPC connectors for accessing private resources from functions - **gcp-cloud-sql** - Connecting Cloud Functions to managed databases - **terraform-gcp** - Deploy Cloud Functions with Infrastructure as Code - **gcp-gke** - When workloads outgrow serverless and need Kubernetes