Cloud Functions Serverless Fundamentals

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Core serverless concepts for Cloud Functions

• No server management
  Google Cloud manages provisioning, patching, and the runtime environment so you don’t have to.
• Automatic scaling
  Functions scale out automatically by creating instances to handle increased traffic.
• Pay-per-use billing
  You are charged only while your function is executing; idle time is not billed.
• Event-driven execution
  Functions execute in response to events: HTTP requests, Pub/Sub messages, storage events, Firestore changes, etc.
• Statelessness
  Each execution is independent and should not rely on local filesystem state. Use external services (Firestore, Cloud Storage, BigQuery) for persistence.

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Supported languages and runtimes

• Python
• Node.js
• Java
• Go
• .NET
• Ruby

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Triggers — how functions are invoked

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Minimal examples

// index.js
exports.helloHttp = (req, res) => {
  const name = req.query.name || req.body?.name || 'World';
  res.status(200).send(`Hello ${name}!`);
};

# main.py
def hello_http(request):
    name = request.args.get('name') or request.get_json(silent=True).get('name', 'World')
    return f'Hello {name}!', 200

gcloud functions deploy helloHttp \
  --runtime nodejs18 \
  --trigger-http \
  --allow-unauthenticated \
  --entry-point helloHttp

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Quick exam-style question

1. Pay for servers running 24/7.
2. Pay per use only when your code executes.
3. Monthly subscription, regardless of usage.

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Summary

• Performance characteristics and cold-start behavior
• Data-processing design patterns with Cloud Functions
• Rate limiting, batching, and retry strategies
• When to choose Cloud Functions vs. Cloud Run or Workflows

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Links and references

• Cloud Functions documentation
• Cloud Functions runtime support
• Google Cloud Storage events
• Pub/Sub documentation