Storage QoS Control in Distributed Virtual Infrastructure
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Solution Overview
Problem
In distributed virtual infrastructures, ensuring quality-of-service (QoS) delivery from storage arrays to virtual machines is challenging due to issues like VM over-subscription, abstraction, and rapid instantiation, which complicates performance contention diagnosis.
Innovation Solution
A controller is implemented to manage I/O requests across processing units, switches, and storage units based on collected quality-of-service data, using software-defined networking and modules like integrated QoS array control, network QoS control, and QoS measurement and analysis to deliver and measure storage QoS.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If virtual machines are rapidly instantiated and over-subscribed to maximize resource utilization, then productivity increases, but quality-of-service delivery and performance diagnosis become unreliable
Solution Approach 1:
The patent implements a feedback mechanism where the controller continuously collects quality-of-service data from storage units, processing units, and switches along the I/O path. This feedback loop enables the controller to monitor actual performance metrics and adjust resource allocation dynamically, ensuring QoS delivery even in over-subscribed virtualized environments where multiple VMs share physical resources.
Solution Approach 2:
The controller acts as an intermediary between storage units and virtual machines, managing I/O requests and enforcing QoS policies. By introducing this intermediary layer, the system can abstract the complexity of resource sharing from individual VMs while maintaining reliable QoS delivery through centralized control and coordination across the distributed infrastructure.
2Ease of operation
If virtual machine abstraction is implemented to simplify resource management, then ease of operation improves, but difficulty of detecting and measuring performance contention increases
Solution Approach 1:
The patent segments the I/O path into distinct components (storage units, processing units, switches) and collects QoS data from each segment independently. This segmentation enables the controller to identify exactly where performance contention occurs in the abstracted virtualized environment, maintaining ease of operation while improving detectability of performance issues through granular monitoring points.
3Reliability
If end-to-end quality-of-service control is implemented across the I/O path, then quality-of-service delivery improves, but device complexity increases
Solution Approach 1:
The controller is designed as a universal multi-functional component that performs multiple roles: collecting QoS data from various sources, managing I/O requests, enforcing QoS policies, and diagnosing performance issues. By consolidating these functions into a single universal controller, the system achieves reliable end-to-end QoS control while minimizing the increase in device complexity through functional integration rather than proliferation of separate components.
Data Source
AI summary
Techniques for delivering and measuring storage quality-of-service to virtual machines in a distributed virtual infrastructure. In one example, a method comprises the following steps. A controller obtains quality-of-service data from at least a portion of components of a distributed virtual infrastructure, wherein the components of the distributed virtual infrastructure comprise one or more storage units, one or more processing units, and one or more switches operatively coupled to form the distributed virtual infrastructure. The controller manages at least one input/output request throughout a path defined by at least one of the one or more processing units, at least one of the one or more switches, and at least one of the one or more storage units, based on at least a portion of the collected quality-of-service data.