Control Plane Proxy Autoscaling for Idle Resource Hibernation
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Solution Overview
Problem
Existing container platforms face inefficiencies in power and resource utilization due to control plane components being continuously powered, regardless of actual workload demands, leading to improper resource allocation and increased costs.
Innovation Solution
Implementing a proxy system that intercepts requests to control plane components, determining resource needs based on context-aware heuristics, and adjusting resource allocation dynamically, including hibernation modes when idle, to optimize resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If control plane components are continuously powered to ensure service availability, then system reliability is improved, but energy consumption increases and resource utilization efficiency deteriorates
Solution Approach 1:
The patent implements dynamic resource allocation by transitioning control plane components between active and hibernation states based on real-time workload conditions. The system monitors request patterns and automatically adjusts component states, making the previously static power configuration dynamic and adaptive to actual usage patterns.
Solution Approach 2:
The system changes operational parameters by adjusting the power state of control plane components from a fixed continuous-power mode to a variable mode that switches between active and hibernation states. This parameter change enables the system to optimize between reliability and energy consumption based on workload conditions.
2Speed
If control plane components remain continuously active to handle sudden workload spikes, then response speed is improved, but resource allocation efficiency deteriorates
Solution Approach 1:
The system performs preliminary actions by pre-warming or pre-activating control plane components based on predicted workload patterns or scheduled tasks. This allows the system to maintain components in a ready state before actual workload arrives, ensuring fast response without keeping all components continuously active at full capacity.
Solution Approach 2:
The system dynamically adjusts the number and state of active control plane components based on real-time monitoring of workload patterns, request rates, and system load. This dynamic adjustment enables the system to optimize response speed by activating components only when needed while improving resource allocation efficiency by avoiding unnecessary continuous activation.
3Ease of operation
If pre-configured resource allocation is used to simplify management, then ease of operation is improved, but adaptability to actual workload demands deteriorates
Solution Approach 1:
The system implements self-service by enabling control plane components to automatically monitor their own workload conditions and autonomously transition between active and hibernation states. This self-managed resource allocation eliminates the need for complex manual configuration while maintaining high adaptability to actual workload demands through automated decision-making.
Solution Approach 2:
The system uses feedback mechanisms by continuously monitoring workload patterns, request rates, and component performance metrics. This feedback information is used to automatically adjust resource allocation decisions, enabling the system to adapt to actual workload demands without requiring complex manual pre-configuration while maintaining operational simplicity through automated control loops.
Data Source
AI summary
Embodiments relate to container resource autoscaling by a control plane. According to an aspect, a computer-implemented method includes receiving and intercepting a request from a software application by a proxy, the request for a service provided by a backend service of one or more control plane components. A processing device of the proxy determines, based on the intercepted request, an amount of resources to be assigned to or updated in the backend service. The processing device causes a control plane scaler coupled to the one or more control plane components to request the determined amount of resources for the backend service. Upon receiving a confirmation that the determined amount of resources is available in the backend service, the processing device forwards from the proxy, the intercepted request to the backend service.