Data Center Resiliency Platform for Automated Disaster Recovery
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Solution Overview
Problem
Current disaster recovery methods for data centers are cumbersome and time-consuming, especially after catastrophic failures where manual reconfiguration of hardware and software resources is required, and existing solutions do not automatically identify and map new assets to old configurations.
Innovation Solution
A resiliency platform software application dynamically identifies the correlation between software resources based on replication properties, enabling automatic reconfiguration of data centers by recreating software resources on new hardware without manual mapping, using a graphical user interface to facilitate the setup of newly configured assets and leveraging stored mapping information from a replicated database.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual mapping of hardware and software assets is performed after failure, then configuration accuracy is maintained, but recovery time and operational complexity increase significantly
Solution Approach 1:
The system performs preliminary actions by automatically discovering and mapping software-to-storage relationships before failure occurs. The software resource discovery mechanism pre-establishes the correlation data structure that links software assets to their underlying storage resources, so that when failure occurs, this pre-discovered information can be immediately used for recovery without requiring manual remapping.
Solution Approach 2:
The system enables self-service by implementing automatic software resource discovery that autonomously identifies and maps software assets to storage resources without human intervention. The discovery mechanism automatically traverses the software stack, detects software binaries and their dependencies, and establishes the correlation data structure independently, eliminating the need for manual configuration while maintaining accuracy.
2Productivity
If automatic resource identification is implemented, then recovery speed increases, but system complexity and detection difficulty increase
Solution Approach 1:
The system applies segmentation by dividing the complex software resource discovery process into distinct functional modules: software binary detection, dependency analysis, correlation data structure generation, and mapping to storage resources. Each module handles a specific aspect of the discovery process, making the overall complex system manageable through modular design while maintaining high recovery speed.
Solution Approach 2:
The system introduces an intermediary correlation data structure that mediates between software resources and storage resources. This intermediate layer automatically captures and maintains the relationships without requiring direct manual mapping, thereby increasing recovery speed while managing system complexity through automated relationship tracking rather than direct complex mappings.
3Measurement precision
If comprehensive software resource discovery is performed, then mapping accuracy improves, but computational resources and processing time increase
Solution Approach 1:
The system applies partial action by performing software resource discovery selectively based on failure context. Rather than continuously discovering all possible software resources in the entire data center, the system discovers and maps only the software resources relevant to the failed components, thereby maintaining high mapping accuracy for critical resources while reducing unnecessary computational expenditure on unrelated resources.
Data Source
AI summary
Systems, apparatuses, methods, and computer readable mediums for seamlessly reconfiguring a data center after a failure are disclosed. In one embodiment, a system includes at least a primary data center and a secondary data center. When a failure occurs at the primary data center, software executing on the secondary data center dynamically identifies the storage resources correlation that is setup for disaster recovery. The software executing on the secondary data center will automatically identify the resources correlation based on the replication properties of the storage configuration. The resources will then be configured with the new parameters when new hardware and software is added to the primary data center after the failure.