Real-time data processing systems
Execute your code in response to changes in data. Cloud Functions can respond to events from GCP services such as Cloud Storage, Cloud Pub/Sub, and Stackdriver Logging, allowing you to power a variety of serverless real-time data processing systems.
Real-time file processing
Use Cloud Functions to respond to events from Cloud Storage or Firebase Storage to process files immediately after upload to generate thumbnails from image uploads, process logs, validate content, transcode videos, validate, aggregate and filter data in real-time.
Example: image processing
Incentro implemented a serverless file processing solution for real-time tagging and indexing of digital media assets for one of their customers.
gcp console quickstart
Create and deploy a Cloud Function using the GCP Console
Set up a Cloud Storage triggered Cloud Function using Firebase SDK
Extract metadata from images uploaded to Firebase Storage bucket using ImageMagick
Detect and blur offensive images uploaded to a Cloud Storage bucket using ImageMagick
Real-time stream processing
Use Cloud Functions to respond to events from Cloud 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.
Example: quality-of-service tracking application
Semios uses Google Cloud Functions as a critical part of their data ingestion pipeline, to asynchronously aggregate microclimate telemetry data from in-field sensors.
Learn about Pub/Sub features via an interactive tutorial in GCP Console
weather station app
Build a weather station using Cloud IoT Core, Pub/Sub, and Cloud Functions for Firebase
Set up a Pub/Sub triggered Cloud Function using the Firebase SDK
Developer’s guide into building real-time data analytics pipelines presented at Google Cloud Next 2017