Simulation Hypervisor for Disaster Recovery Capacity Planning
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current disaster recovery planning faces challenges in accurately projecting workload forecasts onto disaster recovery servers, leading to potential misallocation of resources, either resulting in under or over-commitment, which can impact the timely availability of resources during a disaster event.
Innovation Solution
A simulation hypervisor receives streaming metric data from a primary site and combines it with production data from a backup site to simulate a recovery event, enabling accurate disaster recovery capacity planning and resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If resources are allocated to the DR site based on abstract workload forecasts, then disaster recovery capacity can be prepared, but misallocation of resources occurs leading to under or over-commitment
Solution Approach 1:
The patent performs preliminary actions by simulating recovery events before actual disasters occur. The simulation hypervisor runs tests that combine metric data with production data to predict resource requirements, allowing organizations to prepare accurate capacity plans in advance without facing the uncertainty of abstract workload forecasts during actual emergencies.
Solution Approach 2:
The system uses feedback from simulation results to continuously improve disaster recovery planning. By comparing simulated recovery outcomes with actual resource allocation, the system provides feedback that refines future capacity planning, enabling organizations to adjust their DR resources based on empirical simulation data rather than theoretical estimates.
2Quantity of substance
If too little DR-based workload is allocated to a backup site, then hardware installation cost is reduced, but resources are not accessible in a timely manner during a DR event
Solution Approach 1:
The simulation hypervisor performs preliminary recovery simulations to determine the minimum necessary hardware resources required for timely disaster recovery. By testing recovery scenarios in advance, the system identifies the optimal hardware allocation that ensures resources will be accessible within acceptable timeframes without over-provisioning equipment.
Solution Approach 2:
The system changes parameters by adjusting hardware resource allocation based on simulation results. The simulation hypervisor varies resource levels in simulated environments to identify the threshold at which recovery time objectives are met, allowing organizations to optimize hardware quantity while maintaining acceptable recovery performance.
3Reliability
If too much DR-based workload is allocated to a backup site, then resource accessibility during DR event is ensured, but hardware installation cost increases and resources may not be accessible in a timely manner
Solution Approach 1:
The simulation approach enables partial action by allocating only the necessary portion of hardware resources required for effective disaster recovery. Rather than provisioning excessive resources, the system uses simulations to identify the minimum viable hardware allocation that achieves recovery objectives, avoiding the waste of over-provisioning while ensuring adequate resource availability.
Solution Approach 2:
The system optimizes hardware resource parameters by adjusting allocation levels based on simulation feedback. The simulation hypervisor tests different hardware configuration parameters to find the optimal balance between resource quantity and recovery performance, eliminating the need for excessive hardware installation while maintaining reliable resource accessibility during disasters.
4Productivity
If virtualization logic is applied to collapse and reinflate workload in a virtualized capacity solution, then resource efficiency is improved, but the effect on the virtualization hypervisor in the DR site becomes unpredictable
Solution Approach 1:
The simulation hypervisor acts as an intermediary that mediates between the primary site's virtualization workload and the DR site's hypervisor. It runs simulations that safely test the interaction between virtualization logic and the DR hypervisor, allowing organizations to observe and measure the actual effects without risking production system stability or facing unpredictable outcomes.
Solution Approach 2:
The system performs preliminary testing of virtualization logic effects on the DR hypervisor through simulations before deploying to production. By pre-testing workload collapse and reinflation scenarios in the simulation environment, organizations can predict the actual impact on DR hypervisor performance and adjust their virtualization strategies accordingly, eliminating the uncertainty of unpredictable hypervisor behavior.
Data Source
AI summary
An approach is provided for determining disaster recovery capacity. A simulation hypervisor receives streaming metric data, which represents the current production workload of a primary site, from the primary site. The metric data is combined with production data of the backup site by the simulation hypervisor to simulate a recovery event. Using data from the simulating, disaster recovery planning can be performed.