On-Demand Storage Pool With Asynchronous Replication
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Solution Overview
Problem
Current cloud storage solutions for enterprise environments are costly, error-prone, and time-consuming due to the need for independent management of multiple software and hardware components, often resulting in suboptimal resource utilization and inefficient backup and replication processes.
Innovation Solution
The system provides on-demand data storage by creating an unpartitioned storage pool, utilizing a distributed metadata store, and implementing asynchronous replication with local change detection and correction, minimizing network bandwidth through efficient data transfer and compression, and enabling automatic provisioning and real-time billing and metrics reporting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional cloud storage solutions are implemented with multiple software and hardware components, then data storage capability is provided, but the system becomes costly, error-prone, and time-consuming to manage due to independent management requirements
Solution Approach 1:
The patent combines multiple independent storage components (storage nodes, interface nodes, file systems) into a unified cloud storage pool managed by a single controller. This merging eliminates the need for independent management of each component, reducing errors and simplifying operations while maintaining data storage capability.
Solution Approach 2:
The storage pool is designed to provide universal data storage services to multiple users and applications simultaneously. The system can dynamically allocate storage resources to different users based on their needs, making the infrastructure more efficient and reducing the complexity of managing separate storage systems for different purposes.
2Ease of operation
If independent management of storage components is performed manually, then configuration control is maintained, but the process becomes costly and time-consuming
Solution Approach 1:
The system implements automated self-service provisioning where the controller automatically allocates storage resources from the pool to users based on their requirements. This eliminates manual configuration tasks, reducing both the time required for provisioning and the operational complexity, while maintaining proper resource allocation and control.
3Productivity
If storage resources are pre-configured for each user, then resource availability is ensured, but resource utilization becomes suboptimal
Solution Approach 1:
The system implements dynamic resource allocation where storage capacity is not statically assigned but dynamically allocated from a shared pool based on real-time user needs. This allows the system to optimize resource utilization by allocating storage to users who need it most at any given time, rather than maintaining fixed allocations that may go unused.
4Reliability
If traditional backup and replication processes are used, then data protection is provided, but network bandwidth consumption increases
Solution Approach 1:
The system implements local change detection that identifies only the specific portions of data that have changed since the last backup. Instead of replicating entire datasets, the system detects and transmits only the modified blocks or files, significantly reducing network bandwidth consumption while maintaining complete data protection and replication integrity.
Data Source
AI summary
Systems and methods provide on demand data storage by creating an unpartitioned storage pool; generating a unique volume identifier for a data storage volume at a predetermined location; pre-provisioning the data storage volume in a volume queue ready for use on-demand; and storing data on the data storage volume at the predetermined location on-demand.