Cloud Functions - Event-driven serverless Functions
- Google cloud compute engine - Scalable pay-as-you-go Function-as-a-service (FaaS) to run your code with zero server management. ⇒ Serverless
- Event-driven functions to handle events from google cloud.
- Run code in response to an event
- In many cases, events from
Pub/Sub “Function triggered” to Cloud Function : Google Cloud Pub/Sub Triggers
- e.g,
Cloud Functions triggered by messages published to Pub/Sub topics in the same Cloud project as the function.
Pub/Sub is a globally distributed message bus that automatically scales as you need it and provides a foundation for building your own robust, global services.
How does it work
USE CASES
USE CASES OF CLOUD FUNCTIONS |
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- Integration with 3rd-party services and APIs
- Iot processing
- Real-time data processing - Events streaming
- Real-time file processing
- Serverless mobile back-ends
- Virtual assistance
- Realtime ML
- Serverless mobile back end
| Real-time notifications workflow for Security Command Center |
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| Serverless "mobile" back ends workflow diagram |
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Cloud Functions directly from Firebase to extend the application functionality without spinning up a server. Run code in response to user actions, analytics, and authentication events to keep your users engaged with event-based notifications and offload CPU- and networking-intensive tasks to Google Cloud. |
Serverless IoT back ends : Cloud Functions allows you to apply custom logic to each event as it arrives. |
Cloud Functions with Cloud IoT Core & other fully managed services to build back ends for IoT device telemetry data collection, real-time processing, and analysis. |
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Sensor : temperature reached 80℉" label |
→ Cloud IoT Core |
→ Pub/Sub |
→ Cloud Functions : Trigger configuration change |
→ Cloud IoT Core |
| → Ceiling fan & turn on. |
Real-time file processing : Cloud Functions enable executing code in response to changes in data |
Cloud Functions can respond to events from Google Cloud services (Cloud Storage, Pub/Sub, Cloud Firestore) to process files immediately after upload and generate thumbnails from image uploads, process logs, validate content, transcode videos, validate, aggregate, and filter data in real time. |
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Storage |
→ Labeled Function triggered to Cloud Functions & Processes uploaded image |
→ Cloud Vision API : Detects offensive images |
→ Cloud Functions : Blurs images using ImageMagick. |
→ Storage. |
| Real-time stream processing |
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Use Cloud Functions to respond to pub/sub to process, transform, and enrich streaming data in transaction processing, click-stream analysis, application activity tracking, IoT device telemetry, social media analysis, and other types of applications. |
Use case with Cloud Ml API
| Virtual assistants and conversational experiences |
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Easily build artificial intelligence into your applications. Cloud Functions with Cloud Speech API and Dialogflow can extend your products and services with voice- and text-based natural conversational experiences that help users get things done. Connect with users on Google Assistant, Amazon Alexa, Facebook Messenger, and other popular platforms and devices. |
| Video and image analysis |
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Cloud Functions with Video Intelligence API & Vision API to retrieve relevant information from videos and images, enabling you to search, discover, and derive insight from your media content. |
| Sentiment analysis |
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Cloud Functions in combination with Cloud Natural Language API to reveal the structure and meaning of text and add powerful sentiment analysis and intent extraction capabilities to your applications |
Q 41.
Your team is building an application for a global bank that will be used by millions of customers. You built a forecasting model that predicts customers' account balances 3 days in the future. Your team will use the results in a new feature that will notify users when their account balance is likely to drop below $25. How should you serve your predictions?
- ❌ A. Create a Pub/Sub topic
for each user. 2. Deploy a Cloud Function that sends a notification when your model predicts that a users account balance will drop below the $25 threshold.
- ❌ B. Create a Pub/Sub topic
for each user. 2. Deploy an application on the App Engine standard environment that sends a notification when your model predicts that a users account balance will drop below the $25 threshold.
- ❌ C. Build a notification system on Firebase. 2. Register each user with a user ID on the Firebase Cloud Messaging server, which sends a notification when
the average of all account balance predictions drops below the $25 threshold.
- ⭕ D. Build a notification system on Firebase. 2. Register each user with a user ID on the Firebase Cloud Messaging server, which sends a notification when your model predicts that a users account balance will drop below the $25 threshold.
