Controller-Worker Flow Plans for Accurate Custom Resource Deployment
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Solution Overview
Problem
In container orchestration systems like Kubernetes, there is a need for effective management of custom resources between controllers and worker nodes, particularly in deployments such as 5G RAN, to ensure deployment accuracy and error detection.
Innovation Solution
A method involving a controller generating a flow plan for custom resources, which is executed by worker nodes, with event notification back to the controller, ensuring coordinated deployment and error reporting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If the controller directly manages custom resources on worker nodes without a structured flow plan, then the deployment process is simpler, but deployment accuracy and error detection capability deteriorate
Solution Approach 1:
The patent segments the custom resource deployment process into discrete flows within a flow plan. Each flow represents a specific deployment step or action that can be independently executed and tracked on worker nodes. This segmentation enables precise control and monitoring of deployment operations, improving deployment accuracy while maintaining manageable complexity through structured breakdown of operations.
Solution Approach 2:
The controller generates a complete flow plan before deployment, which outlines the entire sequence of deployment steps in advance. This preliminary action allows the system to plan and prepare the deployment sequence, ensuring accuracy through pre-defined steps while the actual execution follows the predetermined plan, reducing complexity during runtime.
2Reliability
If the controller monitors all custom resource states across worker nodes continuously, then error detection capability is improved, but system complexity and resource consumption increase
Solution Approach 1:
The patent implements a feedback mechanism where worker nodes report status information back to the controller as events during flow plan execution. This feedback allows the controller to monitor custom resource states and detect errors without continuous polling, improving reliability through event-driven monitoring while reducing system complexity compared to continuous state tracking.
Solution Approach 2:
Instead of continuous monitoring, the system uses periodic event reporting where worker nodes notify the controller of state changes or errors at specific intervals or upon occurrence of events. This periodic action improves error detection capability while avoiding the complexity and resource consumption of continuous monitoring.
3Manufacturing precision
If a detailed flow plan with sequence of flows is implemented for custom resource deployment, then deployment precision is improved, but the complexity of deployment management increases
Solution Approach 1:
The flow plan structure enables worker nodes to autonomously execute deployment steps according to the predefined sequence without requiring complex external coordination. Each worker node can independently process and execute flows in the sequence provided by the controller, improving deployment precision through structured execution while simplifying management through self-service execution at the worker level.
Data Source
AI summary
An example method of managing a custom resource in a container orchestration (CO) system, the CO system including a plurality of hosts executing a controller and a set of workers, is described. The method includes generating, at the controller in response to a specification of the custom resource by a user, a flow plan, the flow plan including a sequence of flows for execution by a worker in the set of workers; providing, by the controller, the flow plan to the worker; executing, by a flow executor on the worker, the sequence of flows in the flow plan to deploy the custom resource; generating, by the flow executor on the worker, at least one event during execution of the flow plan; and notifying, by the worker, the controller of the at least one event.