Cloud Database Instance Migration for Dynamic Resource Allocation
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Solution Overview
Problem
Cloud database instances often suffer from underutilization or overutilization of computing resources, leading to inefficiencies and increased costs, as organizations may reserve more resources than needed or fail to allocate resources effectively, impacting productivity and operational efficiency.
Innovation Solution
Implementing automated techniques to monitor and analyze operational data of cloud database instances, migrating underutilized dedicated instances to shared instances and overutilized shared instances to dedicated instances, thereby reallocating resources efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If organizations reserve more computing resources for cloud database instances, then reliability and performance are improved, but resource waste and cost increase
Solution Approach 1:
The patent implements dynamic resource allocation by continuously monitoring database workload and automatically adjusting resource reservations. The system transitions from static pre-provisioned resources to dynamic resources that scale up or down based on actual demand, resolving the contradiction between ensuring reliability and avoiding resource waste.
Solution Approach 2:
The system employs feedback mechanisms where operational data from database instances is continuously collected and analyzed. Based on this feedback, the system makes informed decisions about resource allocation, migrating instances between shared and dedicated configurations to optimize the balance between reliability and resource efficiency.
2Reliability
If dedicated cloud database instances are provisioned for each organization, then performance and security are improved, but resource utilization efficiency deteriorates
Solution Approach 1:
The patent segments database instances into different types (shared vs. dedicated) based on organizational needs and workload characteristics. This segmentation allows the system to provide dedicated instances for performance-critical workloads while using shared instances for less demanding workloads, optimizing overall resource utilization efficiency.
Solution Approach 2:
The system dynamically changes the resource allocation parameters of database instances based on monitored operational data. When an instance shows patterns of underutilization, its resource parameters are adjusted by migrating it to a shared configuration, thereby improving resource utilization efficiency while maintaining performance through parameter optimization.
3Productivity
If automated migration between shared and dedicated instances is implemented, then resource allocation efficiency is improved, but system complexity increases
Solution Approach 1:
The patent implements self-service automation where the system autonomously monitors, analyzes, and migrates database instances without manual intervention. The automated migration process handles the complexity of data transfer, configuration updates, and resource reallocation internally, improving resource allocation efficiency while managing system complexity through encapsulated automation logic.
Data Source
AI summary
The present disclosure provides techniques and solutions for more efficiently managing computing resources used for cloud database instances. Operational data for shared cloud database instances and dedicated database instances can be monitored, including on a continuous basis. The operational data can be compared with one or more thresholds. If the operational data indicates that an entity assigned to a dedicated cloud database instance is underutilizing its assigned resources, it can be migrated to become a tenant of a shared cloud database instance. If the resources of a shared cloud database instance are overutilized, a tenant can be migrated to a dedicated cloud database instance. Migration can include copying data from the original cloud database instance to a migration target cloud database instance. After migration, computing resources can be released that were assigned to the dedicated cloud database instance or to a particular tenant of the shared cloud database instance.