GCP Series: Google Data Analytics Pipeline and Cloud Functions
How to Build a Scalable Data Analytics Pipeline with Google Cloud Platform
Overview: Google Cloud Functions
Scalable pay-as-you-go functions as a service (FaaS) to run your code with zero server management.
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No servers to provision, manage, or upgrade
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Automatically scale based on the load
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Integrated monitoring, logging, and debugging capability
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Built-in security at role and per function level based on the principle of least privilege
- Key networking capabilities for hybrid and multi-cloud scenarios
Key features
Simplified developer experience and increased developer velocity
Cloud Functions has a simple and intuitive developer experience. Just write your code and let Google Cloud handle the operational infrastructure. Develop faster by writing and running small code snippets that respond to events. Connect to Google Cloud or third-party cloud services via triggers to streamline challenging orchestration problems.
Pay only for what you use
You are only billed for your function’s execution time, metered to the nearest 100 milliseconds. You pay nothing when your function is idle. Cloud Functions automatically spins up and backs down in response to events.
Avoid lock-in with open technology
Use open source FaaS (function as a service) framework to run functions across multiple environments and prevent lock-in. Supported environments include Cloud Functions, local development environment, on-premises, Cloud Run, and other Knative-based serverless environments.
USE CASE #1:
Use Cloud Functions with Video Intelligence API and Cloud Vision API to retrieve relevant information from videos and images, enabling you to search, discover, and derive insight from your media content.
USE CASE #2:
Use 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.
Google Cloud Functions Documentation
https://cloud.google.com/functions/docs