Kubernetes Control Plane Node Management via Segmentation
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Solution Overview
Problem
Cloud providers' management of Kubernetes clusters can lead to unexpected deprovisioning of control plane nodes, causing instability and volatility, as they adjust resources based on usage without considering the long-term requirements of the orchestration system.
Innovation Solution
A system that manages containerized workloads independently of cloud providers by configuring and provisioning control plane and worker nodes based on workload demands, allowing internal management of resources and avoiding cloud provider intervention, thus ensuring consistent and efficient operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If cloud providers manage Kubernetes clusters by adjusting resources based on usage, then resource efficiency is improved, but cluster stability deteriorates due to unexpected deprovisioning of control plane nodes
Solution Approach 1:
The patent segments cluster management into two distinct parts: cloud provider manages worker nodes (compute resources) while the Kubernetes control plane independently manages control plane nodes. This segmentation prevents cloud provider actions from affecting control plane node stability, resolving the contradiction between resource efficiency and cluster stability.
Solution Approach 2:
The Kubernetes control plane acts as an intermediary between the cloud provider and the cluster nodes. It receives resource requests from workloads and translates them into appropriate node provisioning decisions, filtering out unwanted cloud provider interventions and maintaining control plane stability while enabling efficient resource utilization.
2Adaptability or versatility
If cloud providers provision and deprovision nodes dynamically, then adaptability to workload changes is improved, but system reliability deteriorates due to unexpected node removals
Solution Approach 1:
The patent divides node management responsibilities: cloud provider handles worker node provisioning for workload elasticity, while Kubernetes control plane independently manages control plane node lifecycle. This ensures adaptability to workload changes through dynamic worker node provisioning without compromising control plane reliability.
Solution Approach 2:
The patent extracts control plane node management from cloud provider control and places it within the Kubernetes control plane itself. This extraction eliminates the harmful effect of cloud provider deprovisioning actions on control plane nodes while preserving the ability to dynamically provision worker nodes for workload adaptability.
3Ease of operation
If Kubernetes relies on cloud provider infrastructure, then ease of deployment is improved, but independence and portability deteriorate
Solution Approach 1:
The patent implements self-service by enabling the Kubernetes control plane to autonomously manage control plane nodes without cloud provider intervention. The control plane independently provisions, scales, and manages its own nodes based on workload demands, reducing dependency on cloud provider infrastructure while maintaining ease of deployment through automated management.
Data Source
AI summary
Systems and methods for management of workloads within container orchestration systems associated with cloud systems are disclosed herein. A first request for at least one additional node from a cloud provider can be transmitted. Based on the first request, a first set of one or more node addresses can be received. Control plane network connections between control plane nodes can be configured. A workload processing request can be received. Based on generating an estimate of required resources for the workload processing request, a second request for at least one additional node can be transmitted. Based on receiving a second plurality of node identifiers, a worker node group can be configured.