ConfigMap-based method and system for storing large AI configuration file
By splitting large AI configuration files into smaller files and combining them using ConfigMap resources, the problem of ConfigMap resource size limitation is solved, and large AI configuration files are effectively saved.
CN121579097AActive Publication Date: 2026-02-27GRADIENT TECH CO LTD
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Patent Information
- Application Number
- CN202511774619.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-28
- Publication Date
- 2026-02-27
- Estimated Expiration
- 2045-11-28
AI Technical Summary
Technical Problem
Existing ConfigMap resources cannot effectively store large AI configuration files, limited by a 1MB size constraint.
Method used
The large AI configuration file is divided into multiple smaller AI configuration files, each with its own sub-ConfigMap resource. The names of the sub-ConfigMap resources are then combined into a single large AI configuration file using the main ConfigMap resource. This file is then stored in the workload's mount directory using the node proxy service.
Benefits of technology
It enables the storage of AI configuration files exceeding 1MB via ConfigMap resources, meeting the storage requirements for large AI configuration files.
✦ Generated by Eureka AI based on patent content.
Abstract
The invention provides a ConfigMap-based method and a ConfigMap-based system for storing a large AI configuration file, which comprises the following steps of: dividing the content of the large AI configuration file into a plurality of small AI configuration files, respectively creating sub ConfigMap resources by using each small AI configuration file, setting names of the plurality of sub ConfigMap resources in a main ConfigMap resource configuration, and storing the sub ConfigMap resources in the main ConfigMap resource configuration. And combining the data key content of each sub ConfigMap resource into a configuration file by the node proxy service, and storing the configuration file in the workload mounting directory, thereby realizing the purpose of storing a very large AI configuration file by using the ConfigMap resource.
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