Serverless Function Deployment Using Multi-Cloud Sustainability Scoring
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Solution Overview
Problem
Existing serverless function deployment systems do not consider sustainability factors, leading to increased carbon footprints and a lack of alignment with corporate CO2E reduction targets, despite the growing importance of renewable energy sources and compliance with data regulations.
Innovation Solution
A system and method for deploying serverless functions across multiple cloud-based services that utilize sustainability data, including location, renewable energy sources, and carbon footprint, to select the most suitable provider based on a computed sustainability score.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If serverless functions are deployed to cloud-based services without considering sustainability factors, then deployment simplicity and speed are maintained, but carbon footprint increases and alignment with corporate CO2E reduction targets deteriorates
Solution Approach 1:
The system performs preliminary actions by pre-calculating and storing sustainability scores for multiple cloud providers before deployment decisions are made. The sustainability assessment module evaluates carbon intensity, renewable energy usage, and other environmental factors in advance, creating a ready-to-use sustainability profile that guides deployment decisions without adding complexity to the actual deployment process
Solution Approach 2:
The patent introduces a sustainability assessment module as an intermediary component that sits between the deployment system and cloud providers. This module acts as a mediator by evaluating sustainability metrics and translating them into actionable deployment recommendations, allowing the system to consider environmental factors without requiring complex integration with each cloud provider's infrastructure
2Reliability
If cloud-based services are selected based on sustainability data, then alignment with corporate sustainability goals is improved, but selection process complexity increases
Solution Approach 1:
The system applies parameter changes by transforming multiple sustainability metrics (carbon intensity, renewable energy percentage, location-based environmental factors) into a single composite sustainability score. This parameter transformation simplifies the selection process by providing a unified criterion that directly correlates with corporate sustainability goals, making the selection process more reliable without proportionally increasing complexity
Solution Approach 2:
The patent segments the sustainability evaluation into distinct modular components: data collection module, assessment module, and scoring module. Each component handles a specific aspect of sustainability evaluation independently, allowing the system to maintain high reliability in sustainability alignment while managing complexity through modular architecture that can be configured and adjusted separately
3Loss of information
If sustainability data is gathered and processed, then environmental awareness is improved, but data processing time and computational resources increase
Solution Approach 1:
The system performs preliminary data gathering and processing by continuously monitoring and pre-processing sustainability metrics from cloud providers. Sustainability data such as carbon intensity, renewable energy usage, and location-based environmental factors are collected and validated in advance, reducing the need for real-time data processing during deployment decisions and minimizing time loss
Solution Approach 2:
The patent extracts only the most critical sustainability parameters needed for deployment decisions, such as carbon intensity and renewable energy percentage, rather than processing all available data from cloud providers. This selective extraction approach maintains high environmental awareness by focusing on key impact factors while significantly reducing data processing time and computational resource requirements
Data Source
AI summary
Devices, systems, methods, and processes for sustainably deploying serverless functions across the globe are described herein. Often, when considering sustainability options for cloud-based service providers that can accept and operate serverless functions from various sources, the power source type can be considered. In many cases, solar-powered power sources can be desired, but is only available during the day. Thus, it may be desirable to consider where the location of a cloud-based service provider is located in relation to the daylight time. Thus, various data related to the power being utilized to power the cloud-based service provider location can be determined and utilized when comparing potential locations to deploy serverless functions. In some cases, a sustainability score can be generated based on this sustainability data and a sustainability profile that can be compared against other locations to determine the most suitable cloud-based service provider to deploy the serverless function onto.