Instance Advisory Service for Dynamic Cloud Resource Rightsizing
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Solution Overview
Problem
The underutilization of instances provided by Infrastructure as a Service (IaaS) in terms of CPU, Memory, and Storage usage leads to costly resource allocation, as the full cost of instances must be paid regardless of usage levels.
Innovation Solution
An instance advisory service is implemented to monitor resource utilization and automatically resize instances to more cost-effective types, using metrics and heuristics to identify optimal instance types and perform canary experiments for evaluation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If instances are purchased on a per year basis to ensure availability, then reliability is improved, but cost increases due to full payment regardless of usage
Solution Approach 1:
The patent implements dynamic instance sizing that automatically adjusts instance resource allocation based on real-time utilization metrics. The system continuously monitors CPU, memory, storage, and network usage, and automatically rightsizes instances to match actual demand, transforming the static yearly purchase model into a dynamic adaptation model that maintains reliability while optimizing cost.
Solution Approach 2:
The system changes the parameters of instance configuration by analyzing utilization metrics across multiple dimensions (CPU, memory, storage, network) and automatically adjusting instance size and type. This parameter optimization allows the system to maintain necessary service levels while reducing over-provisioning and associated costs.
2Productivity
If instance size is increased to handle peak demand, then productivity is improved, but resource utilization efficiency deteriorates due to underutilization during low demand periods
Solution Approach 1:
The patent implements dynamic instance sizing that automatically adjusts instance resource allocation based on real-time utilization metrics. The system continuously monitors CPU, memory, storage, and network usage, and automatically rightsizes instances to match actual demand, transforming the static yearly purchase model into a dynamic adaptation model that maintains reliability while optimizing cost.
Solution Approach 2:
The system enables instances to self-rightsize by automatically monitoring their own utilization metrics and triggering resize operations when optimization opportunities are detected. The instance advisory service autonomously evaluates utilization patterns and initiates rightsizing without manual intervention, allowing the system to self-optimize resource allocation.
3Measurement precision
If manual monitoring and analysis of instance utilization is performed, then measurement precision is improved, but time consumption increases
Solution Approach 1:
The system enables instances to self-rightsize by automatically monitoring their own utilization metrics and triggering resize operations when optimization opportunities are detected. The instance advisory service autonomously evaluates utilization patterns and initiates rightsizing without manual intervention, allowing the system to self-optimize resource allocation.
Solution Approach 2:
The patent implements continuous feedback loops where utilization metrics are constantly collected, analyzed, and used to trigger automatic rightsizing actions. The system establishes feedback mechanisms that monitor instance performance and utilization, then feed this information back into the rightsizing decision process, enabling precise measurement and rapid response without manual time investment.
4Loss of energy
If automatic rightsizing is implemented, then cost is reduced, but device complexity increases due to monitoring and management systems
Solution Approach 1:
The patent implements a multi-functional instance advisory service that consolidates multiple functions into a single system: utilization monitoring, metric collection, rightsizing analysis, experiment coordination, and cost optimization. This universal service handles diverse tasks across the instance lifecycle, reducing the need for separate specialized systems and managing complexity through functional integration.
Solution Approach 2:
The system enables instances to self-rightsize by automatically monitoring their own utilization metrics and triggering resize operations when optimization opportunities are detected. The instance advisory service autonomously evaluates utilization patterns and initiates rightsizing without manual intervention, allowing the system to self-optimize resource allocation.
Data Source
AI summary
A system is disclosed. The system includes a resource monitor to monitor a resource utilization of a set of resources of one or more instances, the resource utilization corresponding to a first level of performance and cost and an instance type determiner to, based on the resource utilization, determine if there is an instance type for at least one of the one or more instances, with a resource profile, that will provide a second level of performance and cost that is closer to a default level of performance and cost than the first level of performance and cost. In addition, the system also includes an instance type recommender to, based on the determining, perform one of making and not making a recommendation to replace the instance type of the at least one of the one or more instances.