Non-disruptive Data Migration in Active-Active Clusters
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Solution Overview
Problem
Data migration in a cluster environment is challenging due to the need for fine control over input/output operations, which requires significant communication and coordination among nodes, leading to inefficient use of system resources, especially during non-disruptive migration processes.
Innovation Solution
A method involving a kernel-level migration component that clones writes from a source LUN to a target LUN, with an agent coordinating the copying and write operations to ensure data consistency, allowing for non-disruptive switching of data access from the source to the target LUN, even during ongoing application access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If non-disruptive data migration is performed with ongoing application access, then data availability is maintained, but data consistency and integrity become more difficult to ensure
Solution Approach 1:
The system performs preliminary actions by creating a snapshot of the source LUN before migration begins, and pre-configures the target LUN with the same size and format. This preliminary preparation ensures that the target storage is ready to receive data without disruption to ongoing applications, while maintaining data consistency through the snapshot mechanism that captures the exact state before migration.
Solution Approach 2:
The patent introduces an intermediary migration management system that acts as a mediator between the source LUN, target LUN, and running applications. This intermediary coordinates the migration process by managing data block copying, handling I/O requests, and ensuring consistency without requiring applications to be aware of or involved in the migration process, thus maintaining both availability and consistency.
2Reliability
If fine control over I/O operations is implemented during migration, then data integrity is improved, but system resource efficiency deteriorates due to increased coordination overhead
Solution Approach 1:
The migration control functionality is extracted as a separate, dedicated migration management system that operates independently from the application I/O paths. This extracted control layer manages all coordination tasks for data integrity without interfering with application performance, as it operates at the storage management level rather than requiring application-level coordination overhead.
Solution Approach 2:
The system uses data copying with snapshot technology to maintain integrity during migration. By creating a point-in-time copy of the source LUN and copying data blocks from source to target while maintaining the snapshot reference, the system ensures data integrity without requiring complex real-time synchronization protocols that would reduce system efficiency.
3Loss of time
If migration is performed while applications are accessing data, then downtime is eliminated, but the complexity of coordinating multiple nodes increases
Solution Approach 1:
The patent merges the migration coordination functionality into a unified migration management system that handles all cluster nodes through a single interface. Rather than requiring separate coordination mechanisms at each node, the unified system consolidates control, managing snapshots, data copying, and I/O redirection across the entire cluster from a central point, thus reducing overall coordination complexity while enabling non-disruptive migration.
4Manufacturing precision
If source LUN writes are cloned to target LUN, then data consistency is maintained, but I/O performance deteriorates due to duplicate write operations
Solution Approach 1:
The system implements periodic action by cloning writes in batches or at scheduled intervals rather than synchronously for every single write operation. The migration management system can buffer and batch clone operations, or clone at periodic checkpoints, which maintains data consistency over time while avoiding the performance penalty of synchronous cloning for every I/O operation. This periodic approach allows the system to balance consistency requirements with performance considerations.
Data Source
AI summary
Data migration is performed in a cluster of host computers each using a mechanism associating data with a source LUN. During a synchronization operation the contents of the source LUN are copied to the target LUN while ongoing normal source LUN writes are cloned to the target LUN. A datapath component of an agent coordinates the writes at the target LUN to maintain data consistency. Upon completion of synchronization, each host stops the write cloning and disables access to the source LUN, in conjunction with a modification of the mechanism to newly associate the data with the target LUN. Depending on the type of mechanism and system, the modification may be done either disruptively or non-disruptively, i.e., with or without stopping normal operation of software of the host computers.