Dynamic I/O Throttling for Multi-Tenant Cloud Storage
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Solution Overview
Problem
Multi-tenant cloud computing environments face performance issues due to unpredictable workloads, where one tenant's high demand for computing resources can lead to pathological latency for others, and overprovisioning to handle spikes results in underutilization and economic inefficiencies.
Innovation Solution
A dynamic throttling system that monitors and manages requests based on utilization metrics and priority, using a throttling kernel to selectively delay I/O requests from tenants exceeding their fair share, ensuring fair access to computing resources while maintaining high performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If computing resources are overprovisioned to handle workload spikes, then service availability is improved, but resource utilization efficiency deteriorates
Solution Approach 1:
The patent implements dynamic throttling that adjusts request processing in real-time based on current system conditions. The throttling mechanism continuously monitors resource utilization and dynamically modifies the behavior of request processing, transitioning between different operational states (allowing requests through vs. throttling) based on current load conditions, thereby resolving the contradiction between maintaining availability and optimizing efficiency
2Productivity
If computing resources are allocated to handle peak demand, then maximum request handling capacity is improved, but average resource utilization deteriorates
Solution Approach 1:
The patent changes the operational parameters of request processing dynamically. Instead of maintaining fixed resource allocation, the system adjusts processing parameters (such as request acceptance rate, processing priority, and throttling intensity) based on current utilization metrics, allowing the system to adapt to varying demand levels and optimize the balance between peak capacity and average utilization
3Productivity
If one tenant generates high demand for computing resources, then that tenant's productivity is improved, but other tenants experience pathological latency
Solution Approach 1:
The patent applies differentiated quality of service to different tenants based on their current resource consumption patterns. The throttling mechanism identifies individual tenants generating excessive demand and applies localized control actions to their request streams, allowing high-productivity tenants to operate at full capacity while preventing any single tenant from degrading service for others, thus achieving local optimization that resolves the contradiction
Data Source
AI summary
Systems, methods, and media for method for managing requests for computing resources are provided herein. Methods may include dynamically throttling requests for computing resources generated by one or more tenants within a multi-tenant system, such as a cloud. In some embodiments, the present technology may dynamically throttle I/O operations for a physical storage media that is accessible by the tenants of the cloud. The present technology may dynamically throttle I/O operations to ensure fair access to the physical storage media for each tenant within the cloud.