Stretch Cluster Data Replication Across Namespace Protocols
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Solution Overview
Problem
In virtualization environments, data replication is complicated by configuration differences and incompatibilities between source and destination clusters, making it difficult to implement desired data replication policies and granularities, especially across different namespace protocols.
Innovation Solution
A method and system for stretching datastores/clusters that allows data replication across multiple namespace protocols, controlling the granularity of replication, and dynamically adjusting between asynchronous and synchronous data replication policies to optimize resource utilization and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data replication is performed across clusters with different namespace protocols, then data replication capability is improved, but system complexity increases
Solution Approach 1:
The patent introduces a namespace protocol translator as an intermediary component that mediates between source and destination clusters with different namespace protocols. The translator converts namespace protocol requests from one protocol format to another, enabling data replication across heterogeneous clusters without requiring both clusters to use the same protocol. This resolves the contradiction by adding a specialized intermediary layer that handles protocol incompatibility.
Solution Approach 2:
The namespace protocol translator is designed with multi-functionality to handle multiple namespace protocols simultaneously. It can receive requests in one protocol format and translate them to different protocol formats for the destination cluster, making the replication system universally applicable across various namespace protocol combinations without requiring separate specialized translators for each protocol pair.
2Manufacturing precision
If granular control of data replication is implemented, then data replication precision is improved, but operation complexity increases
Solution Approach 1:
The patent segments data replication into fine-grained units, allowing administrators to specify which particular data objects, files, or blocks should be replicated rather than replicating entire datasets. This segmentation enables precise control over replication scope while the system handles the complexity of identifying and tracking individual data units automatically.
Solution Approach 2:
The replication system implements dynamic configuration capabilities that allow replication parameters such as granularity level, data selection criteria, and replication scope to be adjusted during operation. This dynamic control enables administrators to refine replication precision based on changing requirements without redesigning the entire replication architecture.
3Use of energy by moving object
If dynamic adjustment of replication policies is implemented, then resource utilization is improved, but control complexity increases
Solution Approach 1:
The patent implements feedback mechanisms that monitor system conditions such as network bandwidth availability, storage resource capacity, and replication progress. Based on this feedback, the replication system automatically adjusts policies like replication timing, data selection criteria, and replication speed to optimize resource utilization. The feedback loop closes by continuously adapting replication behavior to current system states.
Solution Approach 2:
The system dynamically changes replication parameters such as replication rate, data selection thresholds, and policy priorities based on monitored system conditions. When resources are abundant, the system increases replication speed; when resources are constrained, it adjusts to conserve bandwidth and storage capacity, thereby optimizing overall resource utilization through parameter adaptation.
Data Source
AI summary
Described is an approach for implementing stretching datastores/clusters in a virtualization environment. In this approach, data replication can be performed across multiple namespace protocols. In addition, control can be made of the granularity of the data replication such that different combinations of data subsets are replicated from one cluster to another.