Google Cloud Functions provides serverless CAPTCHA solving with automatic scaling, pay-per-use billing, and tight GCP ecosystem integration.
HTTP-Triggered Function
# main.py
import json
import time
import urllib.request
import urllib.parse
import functions_framework
@functions_framework.http
def solve_captcha(request):
"""HTTP Cloud Function for CAPTCHA solving."""
# Parse request
request_json = request.get_json(silent=True)
if not request_json:
return json.dumps({"error": "JSON body required"}), 400
method = request_json.get("method", "userrecaptcha")
params = request_json.get("params", {})
# Get API key from Secret Manager
api_key = _get_secret("captchaai-key")
try:
token = _solve(api_key, method, params)
return json.dumps({"token": token})
except Exception as e:
return json.dumps({"error": str(e)}), 500
def _get_secret(secret_id):
"""Get secret from GCP Secret Manager."""
from google.cloud import secretmanager
client = secretmanager.SecretManagerServiceClient()
name = f"projects/{_get_project_id()}/secrets/{secret_id}/versions/latest"
response = client.access_secret_version(request={"name": name})
return response.payload.data.decode("UTF-8")
def _get_project_id():
"""Get current GCP project ID."""
import urllib.request
req = urllib.request.Request(
"http://metadata.google.internal/computeMetadata/v1/project/project-id",
headers={"Metadata-Flavor": "Google"},
)
with urllib.request.urlopen(req) as resp:
return resp.read().decode()
def _solve(api_key, method, params, timeout=90):
"""Solve CAPTCHA via CaptchaAI API."""
# Submit
submit_data = urllib.parse.urlencode({
"key": api_key,
"method": method,
"json": 1,
**params,
}).encode()
req = urllib.request.Request(
"https://ocr.captchaai.com/in.php",
data=submit_data,
)
with urllib.request.urlopen(req, timeout=30) as resp:
result = json.loads(resp.read())
if result.get("status") != 1:
raise RuntimeError(f"Submit error: {result.get('request')}")
task_id = result["request"]
# Poll
start = time.time()
while time.time() - start < timeout:
time.sleep(5)
poll_url = (
f"https://ocr.captchaai.com/res.php"
f"?key={api_key}&action=get&id={task_id}&json=1"
)
with urllib.request.urlopen(poll_url, timeout=15) as resp:
data = json.loads(resp.read())
if data["request"] != "CAPCHA_NOT_READY":
if data.get("status") == 1:
return data["request"]
raise RuntimeError(f"Solve error: {data['request']}")
raise TimeoutError("Solve timeout")
Requirements
# requirements.txt
functions-framework==3.*
google-cloud-secret-manager==2.*
Deploy
# Create secret
echo -n "YOUR_API_KEY" | gcloud secrets create captchaai-key --data-file=-
# Deploy function
gcloud functions deploy solve-captcha \
--gen2 \
--runtime=python311 \
--region=us-central1 \
--source=. \
--entry-point=solve_captcha \
--trigger-http \
--allow-unauthenticated \
--timeout=120s \
--memory=256MB \
--max-instances=100
# Test
curl -X POST https://us-central1-PROJECT.cloudfunctions.net/solve-captcha \
-H "Content-Type: application/json" \
-d '{
"method": "userrecaptcha",
"params": {
"googlekey": "SITE_KEY",
"pageurl": "https://example.com"
}
}'
Pub/Sub-Triggered Batch Processing
Process CAPTCHA tasks from a Pub/Sub topic:
import base64
import json
import functions_framework
from google.cloud import pubsub_v1
@functions_framework.cloud_event
def process_captcha_task(cloud_event):
"""Process CAPTCHA task from Pub/Sub message."""
data = base64.b64decode(cloud_event.data["message"]["data"])
task = json.loads(data)
api_key = _get_secret("captchaai-key")
try:
token = _solve(api_key, task["method"], task["params"])
# Publish result
publisher = pubsub_v1.PublisherClient()
topic = f"projects/{_get_project_id()}/topics/captcha-results"
publisher.publish(topic, json.dumps({
"task_id": task["id"],
"status": "success",
"token": token,
}).encode())
except Exception as e:
print(f"Task {task.get('id')} failed: {e}")
Deploy for Pub/Sub:
gcloud functions deploy process-captcha-task \
--gen2 \
--runtime=python311 \
--trigger-topic=captcha-tasks \
--timeout=120s \
--memory=256MB
Submit Tasks to Pub/Sub
from google.cloud import pubsub_v1
import json
publisher = pubsub_v1.PublisherClient()
topic = "projects/YOUR_PROJECT/topics/captcha-tasks"
# Submit batch
urls = ["https://site1.com", "https://site2.com", "https://site3.com"]
for i, url in enumerate(urls):
task = {
"id": f"task-{i}",
"method": "userrecaptcha",
"params": {"googlekey": "SITE_KEY", "pageurl": url},
}
publisher.publish(topic, json.dumps(task).encode())
print(f"Published task-{i}")
Cost Comparison
| Factor | Cloud Functions | Always-On VM |
|---|---|---|
| 100 solves/day | ~$0.01/day | ~$1.00/day |
| 1,000 solves/day | ~$0.10/day | ~$1.00/day |
| 10,000 solves/day | ~$1.00/day | ~$1.00/day |
| Idle cost | $0 | Full VM cost |
| Cold start | ~300ms | None |
Troubleshooting
| Issue | Cause | Fix |
|---|---|---|
| Function times out | Timeout too short | Set --timeout=120s |
| Permission denied on secret | Missing IAM role | Grant secretmanager.secretAccessor |
| High cold start latency | Large dependencies | Use urllib instead of requests |
| Pub/Sub message retries | Function returning error | Return success for non-retryable errors |
FAQ
Gen1 or Gen2 Cloud Functions?
Use Gen2. It supports longer timeouts (up to 60 minutes), more memory, and concurrency — all useful for CAPTCHA solving.
How do I handle authentication?
For internal use, require authentication with --no-allow-unauthenticated. For external APIs, use API Gateway with API keys in front of the function.
Can I keep the function warm?
Use Cloud Scheduler to ping the function every 5 minutes. Or set --min-instances=1 to keep one instance warm (costs ~$7/month).
Related Guides
Serverless on GCP — get your CaptchaAI key today.
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