Dynamic Database Resource Allocation via Director Hierarchy
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Solution Overview
Problem
In multi-node computer systems, efficiently managing resource allocation across databases to meet performance and availability requirements is challenging, especially when resources are already allocated to other databases, leading to potential de-allocation impacts on existing services.
Innovation Solution
A method and apparatus for dynamically allocating and de-allocating database instances and nodes between databases, using a hierarchy of directors to monitor performance metrics, adjust resource allocation, and implement remedies such as session balancing and service expansion to ensure service-level agreements are met, while minimizing disruptive resource re-allocations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If resources are allocated to meet peak load requirements for each application, then service availability is improved, but resource utilization efficiency deteriorates due to unutilized capacity
Solution Approach 1:
The patent implements dynamic resource allocation where the resource allocation manager continuously monitors workload demands and adjusts resource allocation in real-time. Resources are allocated to database instances based on current demand rather than static peak load requirements, enabling the system to adapt to varying workload conditions and improve overall resource utilization while maintaining service availability.
Solution Approach 2:
The patent creates a shared resource pool that serves multiple database instances and applications. Instead of dedicating resources to individual applications, the same physical resources (processors, memory, storage) are dynamically shared across multiple database instances, allowing one resource to serve multiple functions and reducing unutilized capacity.
2Loss of energy
If resources are dynamically reallocated from one database to another, then resource utilization is improved, but service performance of existing databases may deteriorate due to de-allocation impacts
Solution Approach 1:
The resource allocation manager implements continuous monitoring of workload demands, service-level agreement compliance, and performance metrics. When resources are reallocated, the system monitors the impact on affected database instances and can trigger remediation actions if performance degradation is detected, ensuring that resource utilization improvements do not compromise service performance.
Solution Approach 2:
The system monitors compliance with service-level agreements before initiating resource reallocation. By maintaining buffers and monitoring thresholds, the system ensures that resource de-allocation from existing database instances does not immediately violate service-level agreements, providing a cushion against performance deterioration while enabling resource utilization improvements.
3Adaptability or versatility
If a hierarchy of directors is implemented to manage resource allocation, then resource management capability is improved, but system complexity increases
Solution Approach 1:
The patent divides the resource management function into a hierarchy of directors with specific responsibilities. The resource allocation manager handles high-level resource allocation decisions, while database instance directors manage individual database instances. This segmentation allows complex resource management capabilities to be achieved through modular, specialized components rather than a monolithic complex system.
Solution Approach 2:
The hierarchy of directors acts as an intermediary layer between the physical resources and the database instances. Rather than direct complex interactions between resource management and individual databases, the directors mediate these interactions, simplifying the overall system architecture while maintaining advanced resource management capabilities.
Data Source
AI summary
An approach efficiently and dynamically allocates and de-allocates database instances and nodes between databases. The approach performs this function in a way that accounts for the users of and services hosted by multiple databases.