Bi-directional Cloud Tiered Data Replication Across Incompatible Clusters
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Solution Overview
Problem
Managing bi-directional replication of cloud tiered data across incompatible clusters is complicated due to differences in supported file versions and metadata, leading to incomplete or unusable data copies.
Innovation Solution
A system and method that determine compatibility data for stub files between source and target clusters, facilitating appropriate synchronization operations such as deep-copy or stub synchronization based on version data, ensuring seamless replication across clusters with different versions of file support.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional replication processes are used between incompatible clusters, then replication simplicity is maintained, but data completeness and usability deteriorate
Solution Approach 1:
The patent introduces a cloud storage system as an intermediary between incompatible clusters. The cloud storage receives data from the source cluster, stores it in a universal format, and provides it to the target cluster. This mediator resolves version incompatibility without requiring direct compatibility between clusters, maintaining operational simplicity while ensuring data completeness.
Solution Approach 2:
The patent changes the storage parameter from local cluster storage to cloud-based storage. By moving data to cloud storage with universal access protocols, the system transforms incompatible local formats into compatible cloud-accessible formats, enabling complete data replication across version-differentiated clusters.
2Quantity of substance
If cloud tiering is implemented to reduce costs, then storage cost is reduced, but replication compatibility deteriorates
Solution Approach 1:
The patent makes the cloud storage system universal by implementing standard protocols that work with multiple cluster versions. The cloud storage acts as a universal interface that can receive data from any cluster version and serve any target cluster version, enabling replication compatibility while maintaining cost-effective cloud tiering.
Solution Approach 2:
The cloud storage serves as a mediator between clusters of different versions. It receives tiered data from source clusters in various versions, normalizes the data format, and provides compatible data to target clusters, thus maintaining replication compatibility while preserving the cost benefits of cloud tiering.
3Manufacturing precision
If version-specific replication is performed, then data accuracy is improved, but replication complexity increases
Solution Approach 1:
The cloud storage system acts as an intermediary that handles version-specific data accuracy requirements. It receives data in source cluster versions, maintains accurate representations, and serves data in formats compatible with target cluster versions. This mediator approach ensures data accuracy without requiring the source and target clusters to directly manage version compatibility, thus reducing replication complexity.
Data Source
AI summary
Data sets are synchronized between two or more clusters of nodes that support different versions of files (e.g., stub files) within a distributed file storage system. Moreover, the distributed file storage system employs a tiered cloud storage architecture. In one aspect, for stub files having versions that are not commonly supported by the two or more clusters, an application protocol interface (API) is utilized that employs a deep-copy process wherein cloud-backed data referenced by a stub file is retrieved from a cloud storage (e.g., public cloud) and sent by a primary cluster to one or more secondary clusters. Moreover, the API can determine an optimal synchronization process on a per-file basis.