Hybrid Cloud Degradation Planning with Cost-Aware Interaction Graphs
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Solution Overview
Problem
Enterprises face challenges in managing hybrid cloud environments due to limited insight into suitable third-party public cloud provider offerings, leading to inefficiencies in resource allocation and cost management, especially in scenarios requiring self-adaptive application degradation.
Innovation Solution
Constructing an interaction graph based on a distributed application, extracting sub-graphs using feasibility validation tests, estimating resource pressure metrics, and creating a degradation plan for a least-cost sub-graph to adapt to changing resource availability and costs in hybrid cloud platforms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If enterprises leverage public clouds in hybrid cloud environments, then elasticity and on-demand computing resources are improved, but insight into suitable third-party public cloud provider offerings and cost management deteriorate
Solution Approach 1:
The patent introduces an interaction graph as an intermediary structure that models the relationships between distributed application services and cloud platform services. This graph serves as a mediator that provides visibility and insight into the hybrid cloud environment, allowing enterprises to understand which third-party public cloud provider offerings are suitable for their specific workloads while maintaining the elasticity benefits of public clouds.
2Quantity of substance
If enterprises leverage public clouds in hybrid cloud environments, then on-demand computing resources are improved, but cost management deteriorates
Solution Approach 1:
The patent implements feedback mechanisms through resource pressure metrics that continuously monitor and evaluate the state of services in the hybrid cloud environment. By estimating resource pressure metrics associated with each service on dependent services, the system provides feedback that enables cost-aware degradation planning, allowing enterprises to manage costs effectively while maintaining access to on-demand computing resources.
Solution Approach 2:
The patent changes the parameter of cost management by introducing cost-aware degradation plans that consider resource pressure metrics. Instead of static cost management, the system dynamically adjusts resource allocation and service degradation strategies based on estimated resource pressure, enabling enterprises to optimize costs while maintaining necessary service levels in hybrid cloud environments.
3Reliability
If self-adaptive application degradation is implemented, then service delivery during resource fluctuations is improved, but system complexity increases
Solution Approach 1:
The patent segments the complex hybrid cloud system into manageable components by constructing an interaction graph that divides the system into services, sub-graphs, and dependent relationships. This segmentation allows self-adaptive application degradation to be implemented in a structured manner, where degradation plans can be developed for specific sub-graphs rather than the entire system, reducing the perceived complexity while maintaining reliability during resource fluctuations.
Data Source
AI summary
A computer program product comprises a computer readable storage medium having program instructions embodied therewith. The program instructions are executable by one or more processors to cause the one or more processors to construct an interaction graph based in part on a distributed application of a cloud platform comprised of a plurality of services; extract one or more sub-graphs from the interaction graph by mining the interaction graph using one or more feasibility validation tests; estimate a resource pressure metric for the one or more sub-graphs, wherein the resource pressure metric is at least one of a prospective resource pressure metric and a retrospective resource pressure metric, the resource pressure metric being associated with each service on one or more respective dependent services; construct a degradation plan for a least-cost sub-graph in accordance with the estimated resource pressure metric; and apply the degradation plan to the distributed application and the cloud platform.