Network Storage Volume Parameter Modification via Dynamic Provisioning
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Solution Overview
Problem
In data center environments, modifying operational parameters of shared network-hosted resources, such as storage capacity or performance, can lead to increased complexity and latency due to the need for additional data volumes, which complicates user application logic and request processing.
Innovation Solution
A method where a data center provisions a new data volume with characteristics that satisfy the requested operational parameter modifications, allowing the new volume to handle read and write requests while the old volume migrates data to it, then deallocates the old volume's resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If additional data volumes are provisioned to modify operational parameters, then storage capacity or performance can be increased, but device complexity and processing latency increase
Solution Approach 1:
The patent creates a copy of the existing data volume rather than modifying it directly. A new data volume is provisioned with the desired operational parameters, and data is copied from the old volume to the new volume. This allows the system to achieve increased storage capacity or performance without directly altering the original volume structure, thereby avoiding the complexity that would arise from in-place modifications.
Solution Approach 2:
The new data volume is provisioned with all necessary characteristics and capacity before the migration process begins. By preparing the destination volume in advance with the correct operational parameters, the system avoids the need for complex post-provisioning configurations and reduces the overall complexity of the modification process.
2Quantity of substance
If additional data volumes are provisioned to modify operational parameters, then storage capacity or performance can be increased, but processing latency increases
Solution Approach 1:
The patent enables the new data volume to begin handling read and write requests while data migration is still in progress. This continuous operation approach allows the system to utilize the new volume immediately for active workloads, reducing the effective latency of the modification process while maintaining data availability and system performance throughout the transition.
Solution Approach 2:
The system employs an intermediary migration process that allows both the old and new volumes to coexist and operate simultaneously. The new volume serves as an intermediary that gradually takes over workload while the old volume continues to serve remaining data, thereby minimizing processing latency and maintaining continuous system operation throughout the modification.
3Reliability
If seamless transition is implemented without disrupting operations, then service availability is maintained, but resource allocation complexity increases
Solution Approach 1:
The patent implements a dynamic resource allocation strategy where the system can flexibly switch between old and new data volumes based on real-time needs. The new volume can begin handling requests dynamically during migration, and the system can adaptively manage the transition process. This dynamic approach maintains service availability while distributing the allocation complexity across multiple operational phases rather than requiring a single complex atomic operation.
Data Source
AI summary
A user can set or modify operational parameters of a data volume stored on a network-accessible storage device in a data center. For example, the user may be provided access to a data volume and may request a modification to the operational parameters of the data volume. Instead of modifying the existing data volume, the data center can provision a new data volume and migrate data stored on the existing data volume to the new data volume. While the data migration takes place, the existing data volume may block input/output (I/O) requests and the new data volume may handle such requests instead. If a request is received for data not yet migrated to the new data volume, then the new data volume prioritizes a migration of the requested data.