Cloud Resource Set Recommendation for Performance-Matched Allocation
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Solution Overview
Problem
Cloud systems provide resource sets with fixed configurations that often fail to meet tenant requirements, leading to resource wastage and high costs, as they typically support only limited concurrencies and do not allow for flexible selection based on specific performance needs.
Innovation Solution
A cloud system resource set recommendation method and apparatus that allows users to specify target cloud services and performance requirements, using system and component load models to select a suitable resource set from existing configurations, enabling more accurate and efficient resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If fixed configuration resource sets are provided, then device complexity is reduced and ease of operation is improved, but adaptability to diverse tenant requirements deteriorates
Solution Approach 1:
The patent transforms fixed static resource configurations into dynamic configurable resource sets. Users can dynamically adjust resource parameters (CPU, memory, storage, network) according to their specific needs, and the system automatically generates appropriate resource set configurations based on user inputs and historical data.
Solution Approach 2:
The patent enables parameter changes by allowing users to specify custom resource requirements (concurrency, CPU utilization, memory, storage, network bandwidth) and automatically generating resource set configurations that match these parameters. The system stores and manages multiple parameter configurations for different resource sets.
2Reliability
If large quantity of resources are configured to meet high concurrency requirements, then reliability and performance are improved, but resource utilization efficiency deteriorates and costs increase
Solution Approach 1:
The patent applies partial action by allocating resources based on actual needs rather than providing maximum capacity. The system calculates appropriate resource quantities (CPU cores, memory, storage) based on concurrency requirements and performance thresholds, avoiding excessive resource allocation while ensuring reliability.
Solution Approach 2:
The system performs self-service by automatically generating optimized resource set configurations based on user requirements and historical performance data. The recommendation apparatus autonomously determines appropriate resource allocations without manual intervention, improving both efficiency and accuracy.
3Device complexity
If limited fixed resource sets are provided, then device complexity is reduced, but productivity and user satisfaction deteriorate due to inability to meet diverse requirements
Solution Approach 1:
The patent implements universality by creating a multi-functional resource management system that can handle various types of cloud services (web, mobile backend, big data, AI) with different resource requirements. The same recommendation apparatus serves multiple functions: analyzing requirements, generating configurations, optimizing resources, and managing diverse service types.
Solution Approach 2:
The recommendation apparatus acts as an intermediary between user requirements and cloud resource allocation. It translates user needs into optimized resource configurations, mediating between diverse tenant requirements and the cloud system's resource management capabilities.
Data Source
AI summary
A cloud system resource set recommendation method includes after receiving a cloud system resource set recommendation request triggered by a user and used to request to obtain cloud system resource sets that can support a target cloud service and meet a performance requirement, the recommendation apparatus selects, based on the cloud system resource set recommendation request, from the existing cloud system resource sets supporting the target cloud service, a target cloud system resource set meeting the performance requirement, and feeds back the target cloud system resource set to the user. The user does not need to select a required cloud system resource set from several limited resource sets with fixed configurations, but only needs to notify the recommendation apparatus of a target cloud service and a performance requirement that need to be supported by the cloud system resource set.