Service Update Resource Reallocation for Kubernetes Clusters
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Solution Overview
Problem
In distributed application systems, especially those using Kubernetes clusters, resource shortages occur during rolling updates due to the coexistence of old and new service instances, leading to inefficient service update management and increased manual labor for developers.
Innovation Solution
A computer-implemented method that detects failed update procedures, suspends them, reallocates resources to dependent services, and resumes updates once the dependent services are updated, ensuring efficient resource utilization and automatic failure handling based on dependency relationships.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If rolling update is used to ensure business continuity, then service availability is improved, but resource consumption doubles causing resource shortage
Solution Approach 1:
The system dynamically adjusts resource allocation based on update status. When an update fails, the system detects the failure state and reallocates resources from the failed service to other services that need resources, transforming the static resource allocation into a dynamic one that adapts to changing conditions.
Solution Approach 2:
The system recovers resources from failed update procedures by detecting failure states and suspending those updates. The resources previously allocated to failed services are released and made available for other services, effectively recovering and reusing resources that would otherwise be wasted.
2Productivity
If resources are allocated to multiple update procedures simultaneously, then update throughput is improved, but resource shortage occurs when dependent services compete for resources
Solution Approach 1:
The system implements feedback mechanisms by monitoring the states of services with dependency relationships. When a dependent service fails or runs out of resources, the system detects this through state checks and adjusts resource allocation accordingly, creating a closed-loop control system that responds to actual resource availability and service states.
Solution Approach 2:
The system performs preliminary checks of service states before allocating resources to update procedures. By checking whether dependent services are in states that would allow successful updates, the system prevents resource allocation to updates that are likely to fail, thereby avoiding wasted resources and improving overall update throughput.
3Measurement precision
If manual management of service updates is performed, then control precision is improved, but labor cost and time consumption increase
Solution Approach 1:
The system enables self-service automation by automatically detecting update failures, checking service states, suspending failed updates, and reallocating resources without human intervention. The system monitors its own state and performs corrective actions autonomously, eliminating the need for manual management while maintaining precise control over the update process.
Solution Approach 2:
The system replaces manual mechanical operations with automated computational processes. Instead of manually monitoring service states and adjusting resource allocation, the system uses automated detection mechanisms and algorithmic resource management to achieve the same control objectives, significantly reducing labor time while maintaining or improving control precision.
Data Source
AI summary
The invention discloses a method, system, and computer program product for service update management. The method, during a first update procedure for a first service in a computing system, in response to a detection that the first update procedure fails, a state of a second service on which the first service depends in the computing system is checked. In response to the second service being in a first state, the first update procedure is suspended. Resources allocated to the first update procedure by the computing system are released. The released resources are allocated to the second update procedure of the second service. The second update procedure is implemented based on the allocated released resources. With these embodiments, failures during the update procedures for the services may be automatically detected and removed based on a dependency relationship between the services. Therefore, the performance of the update procedures may be increased.