Dynamic Storage Volume Adjustment for Application Instances
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Solution Overview
Problem
Current data storage systems face challenges in managing storage volume size for application instances, leading to storage volume exhaustion and inefficient use of infrastructure due to fixed storage capacities that do not adapt to changing data needs.
Innovation Solution
A method that adjusts storage volume size dynamically based on usage data, using a capacity calculation module that collects and analyzes time-series data, applies machine learning algorithms to predict optimal volume sizes, and reallocates space between application instances to optimize storage utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a fixed storage volume size is assigned to an application instance, then the storage capacity is simplified to manage, but the storage volume becomes exhausted when data growth exceeds the initial capacity
Solution Approach 1:
The patent implements dynamic storage volume adjustment by monitoring usage data over time and automatically modifying storage capacity based on actual demand. The system transitions from static fixed-size volumes to dynamic volumes that can expand or contract, resolving the contradiction between simple management and reliable availability.
Solution Approach 2:
The system collects usage data from storage volumes over a period of time and uses this feedback to determine when capacity adjustments are needed. This feedback mechanism enables automatic response to storage exhaustion conditions, maintaining reliability without complex manual intervention.
2Reliability
If storage capacity is enlarged multiple times or provisioned with excess capacity, then storage exhaustion is prevented, but infrastructure availability deteriorates due to wasted capacity
Solution Approach 1:
The system dynamically adjusts storage volumes based on actual usage patterns rather than maintaining fixed or excessively large capacities. This enables the infrastructure to adapt to changing storage needs, improving both availability and utilization efficiency.
Solution Approach 2:
The patent changes the storage capacity parameter automatically based on usage data analysis. By adjusting volume sizes according to actual demand rather than maintaining static or over-provisioned capacities, the system optimizes both reliability and infrastructure productivity.
3Quantity of substance
If manual enlargement or data deletion is required to resolve storage exhaustion, then storage capacity can be adjusted, but operational complexity and downtime increase
Solution Approach 1:
The system performs self-service by automatically monitoring storage usage and adjusting capacity without requiring manual administrator intervention. This eliminates the operational complexity and potential downtime associated with manual storage enlargement operations.
Solution Approach 2:
The system proactively adjusts storage capacity before complete exhaustion occurs by analyzing usage trends over time. This preliminary action prevents storage exhaustion events and eliminates the need for reactive manual intervention, improving ease of operation.
Data Source
AI summary
Disclosed herein are systems and method for adjusting storage volume size of an application instance. A method may include: identifying a first application instance running on a computing device, wherein the first application instance has an assigned first storage volume on a device storage of the computing device; collecting, over a period of time, usage data of the device storage; determining, based on the collected usage data, whether a usage capacity of the first storage volume of the first application instance is reaching a maximum capacity of the first storage volume; in response to determining that the usage capacity of the first storage volume is reaching the maximum capacity of the first storage volume, adjusting a size of the first storage volume by a first amount to accommodate usage of the first application instance.