Resource Allocation Advice for Web Service Cost Optimization
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Solution Overview
Problem
Users of web services often face inefficiencies in resource allocation, as they may use expensive storage devices with capabilities exceeding their needs, pay for unused options, and lack awareness of optimal configuration settings, leading to suboptimal resource usage and increased costs.
Innovation Solution
A system that provides resource allocation advice to web service users through a service provider, utilizing best practice checks and remediation plans to optimize resource usage, including recommendations for virtual machine instances, data storage, security, and backup frequencies, based on historical data and user settings, with automatic remediation options and third-party checks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If users store data in expensive, low-latency storage devices, then data access speed is improved, but storage cost increases
Solution Approach 1:
The patent segments storage into different tiers (e.g., high-performance storage and standard storage) and classifies data based on access patterns. Frequently accessed data is placed in expensive low-latency storage, while less frequently accessed data is placed in cheaper storage, resolving the contradiction between speed and cost.
Solution Approach 2:
The system dynamically adjusts storage allocation based on changing access patterns and workloads. Storage resources are reassigned over time based on actual usage metrics, allowing the system to optimize the balance between performance and cost adaptively rather than statically.
2Adaptability or versatility
If users pay for advanced storage options and configurations, then service capability is improved, but cost increases
Solution Approach 1:
The patent implements self-service mechanisms where the system automatically analyzes usage patterns and makes storage allocation decisions without requiring user intervention. Users benefit from optimized configurations and advanced capabilities through automatic resource management, eliminating the need to manually pay for features they may not need.
Solution Approach 2:
The system continuously monitors storage usage patterns, performance metrics, and cost data, then uses this feedback to automatically adjust storage allocations and configurations. This closed-loop approach ensures users receive appropriate service capabilities based on actual needs rather than maximum specifications.
3Productivity
If users configure resources manually to optimize performance, then resource efficiency is improved, but operational complexity increases
Solution Approach 1:
The patent enables resources to self-optimize by automatically analyzing their own usage patterns and adjusting configurations without manual intervention. The system performs self-diagnosis and self-adjustment to achieve optimal performance, eliminating the operational complexity associated with manual configuration while maintaining high resource efficiency.
Solution Approach 2:
The system automatically adjusts key performance parameters such as storage allocation, resource allocation, and configuration settings based on monitored metrics. By changing parameters automatically rather than requiring manual reconfiguration, the system maintains optimal resource efficiency while significantly reducing operational complexity.
Data Source
AI summary
Embodiments of the present disclosure are directed to, among other things, providing resource allocation advice, configuration recommendations, and/or migration advice regarding data storage, access, placement, and/or related web services. In some examples, a web service may utilize or otherwise control a client instance to control, access, or otherwise manage resources of a distributed system. Based at least in part on one or more resource usage checks and/or configuration checks, resource usage information and/or configuration information of an account utilizing a web service, and/or user preferences and/or settings, resource allocation advice, system configuration recommendations, and/or migration advice may be provided to a user of an account. Additionally, in some examples, one or more remediation operations may be performed automatically.