Multi-Queue Container Scheduler for Special Workload Placement
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Solution Overview
Problem
Existing multi-queue container schedulers in cloud computing environments face inefficiencies due to the lack of dedicated queues for managing special pods, which can lead to suboptimal resource allocation and increased computational resource usage, as higher priority pods may be delayed in deployment and face less favorable placement.
Innovation Solution
Implementing a multi-queue scheduler with separate queues for standard and special pods, where the scheduler includes an event handler and error handler to identify special pods based on characteristics and assign them to appropriate nodes according to placement rules, thereby optimizing resource allocation and deployment efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a single queue is used to manage all pods, then the scheduler structure is simple, but special pods may be delayed and receive less favorable placement
Solution Approach 1:
The patent divides the single pod queue into multiple specialized queues: a standard pod queue for regular workloads and a special pod queue for high-priority or specialized workloads. This segmentation allows different pod types to be managed separately, ensuring special pods receive appropriate placement priority while maintaining overall scheduler organization and operational simplicity.
2Productivity
If separate queues are implemented for standard and special pods, then deployment efficiency improves, but scheduler complexity increases
Solution Approach 1:
The scheduler is segmented into specialized queues (standard pod queue and special pod queue) that can be independently managed. This allows efficient handling of different pod types simultaneously while keeping each queue's management logic relatively simple, thus improving deployment efficiency without excessive complexity increase.
Solution Approach 2:
The scheduler maintains a unified event handler and error handler that serve both standard and special pod queues. These shared components provide multi-functionality, allowing the system to handle different pod types efficiently while avoiding the need for completely separate processing logic for each queue type.
3Productivity
If special pods are prioritized in deployment, then resource allocation optimizes, but computational resource usage increases
Solution Approach 1:
By segmenting pods into standard and special categories with separate queues, the scheduler can apply optimized placement rules specific to each type. This allows special pods to receive prioritized resource allocation without requiring the entire scheduling system to use computationally intensive algorithms for every pod, thus improving resource allocation efficiency while controlling overall computational resource usage.
Data Source
AI summary
A computer-implemented method to schedule special containers using a multi-queue scheduler. The method includes receiving, by a scheduler, a first pod including a first container including a first queue, a second queue, an event handler, and an error handler. The method further includes obtaining a set of characteristics for the first pod and determining that the first pod is a special pod. The method includes adding the first pod to the first queue, wherein the first queue is a special queue and includes a special function. The method also includes initiating the special function. The method further includes assigning, based on one or more placement rules, the first pod to a first node of a plurality of nodes.