Cloud Deployment Architecture for Residual Carbon Debt Reduction
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Solution Overview
Problem
Enterprises face challenges in estimating and reducing their carbon emission debt in cloud-based applications, as existing methods do not effectively account for the carbon footprint of cloud computing resources and the impact of solution architecture design on energy consumption.
Innovation Solution
A system and method for estimating and reducing carbon debt by evaluating cloud deployment architectures using a calculator that assesses energy consumption and quality attributes, allowing for adjustments to minimize carbon footprint while adhering to functional requirements, and leveraging cloud providers' carbon-free energy solutions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If compute utilization is reduced to lower carbon footprint, then energy consumption decreases, but quality attributes such as performance and availability may deteriorate
Solution Approach 1:
The system changes the parameters of cloud deployment architectures by evaluating multiple quality attributes (performance, availability, scalability) and their corresponding carbon emission impacts. It enables dynamic adjustment of architectural parameters to find optimal balance points where quality attributes are maintained while energy consumption is reduced.
Solution Approach 2:
The system introduces dynamic evaluation and adjustment mechanisms that allow cloud architectures to adapt their configuration based on real-time or periodic assessment of quality attributes and carbon debt. This enables the system to dynamically optimize the balance between performance requirements and energy consumption rather than using static configurations.
2Use of energy by moving object
If solution architecture is optimized for minimal carbon footprint, then energy consumption decreases, but architectural complexity increases
Solution Approach 1:
The system implements feedback mechanisms that evaluate cloud deployment architectures against multiple quality attributes and carbon emission metrics. The evaluation results feed back into the architecture selection and optimization process, enabling iterative improvement. This feedback loop helps manage complexity by providing structured guidance for optimization rather than requiring manual analysis of all architectural aspects.
Solution Approach 2:
The system enables cloud architectures to self-evaluate their carbon debt and quality attribute performance through automated calculation and assessment mechanisms. This self-service capability reduces the need for external complex analysis tools and methodologies, allowing the architecture to identify and implement its own optimization opportunities.
3Reliability
If quality attributes requirements are maintained at high levels, then performance is ensured, but carbon emission debt increases
Solution Approach 1:
The system applies partial optimization by identifying specific quality attributes that can be relaxed or adjusted to reduce carbon debt while maintaining overall system performance. Rather than uniformly reducing all quality requirements, it selectively adjusts specific attributes where relaxation has minimal impact on overall performance but significant impact on energy consumption, enabling partial action that balances both concerns.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for reducing carbon emission debt. A method includes actions of obtaining candidate cloud deployment architectures; obtaining a set of requirements for quality attributes, each requirement corresponding to a respective quality attribute of the candidate cloud deployment architectures; selecting, from the candidate cloud deployment architectures, a particular cloud deployment architecture for implementation based on the set of requirements for the quality attributes; determining a wasted carbon emission debt for the particular cloud deployment architecture; selecting a requirement corresponding to a particular quality attribute to adjust based on the wasted carbon emission debt; and providing, for output, an adjusted requirement corresponding to the particular quality attribute. The wasted carbon emission debt includes a difference between the actual carbon emission debt and the theoretical carbon emission debt.