Automated Cluster Configuration via Management Templates
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Solution Overview
Problem
Configuring multiple computing clusters is a time-consuming, complex, and error-prone manual process, which can significantly affect user experience and is inefficient in terms of deployment and error reduction.
Innovation Solution
Automatically configuring managed clusters using configuration datasets stored within a management cluster, where the management cluster communicates with individual managed clusters to create, modify, or delete target objects, enabling rapid deployment with reduced errors and improved customizability and security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual configuration of computing clusters is performed, then flexibility and control are improved, but time consumption and error rate increase
Solution Approach 1:
The patent uses templates to define configuration parameters for computing clusters. These templates serve as reusable copies of configuration patterns that can be applied across multiple clusters, eliminating the need to manually configure each cluster from scratch while maintaining consistency and control.
Solution Approach 2:
The system performs preliminary configuration work by pre-defining template parameters and validation rules before actual cluster deployment. This advance preparation includes setting up configuration schemas, defining valid parameter ranges, and establishing validation logic that automatically checks cluster configurations before deployment.
2Adaptability or versatility
If manual configuration of computing clusters is performed, then customization capability is improved, but error rate increases
Solution Approach 1:
The patent implements automatic validation that provides feedback on configuration parameters. The system checks whether provided parameters match the template schema, validates parameter ranges and formats, and returns error messages guiding users to correct invalid configurations. This feedback mechanism maintains customization while ensuring configuration accuracy.
Solution Approach 2:
The patent replaces manual verification and validation processes with automated computational checks. Instead of relying on human operators to manually verify configuration correctness, the system uses automated validation logic to check parameters against defined schemas, eliminating human error while preserving customization options.
3Productivity
If automated configuration is implemented, then deployment speed is improved, but system complexity increases
Solution Approach 1:
The patent segments the configuration system into distinct components: templates defining configuration schemas, validators checking parameter compliance, and deployers executing cluster creation. This segmentation allows each component to be independently developed and maintained, managing overall system complexity while enabling automated high-speed deployment.
4Manufacturing precision
If configuration validation is performed, then configuration accuracy is improved, but processing time increases
Solution Approach 1:
The patent performs validation selectively based on the configuration stage and risk level. Not all parameters require full validation scrutiny in every scenario - the system applies appropriate validation depth based on context, maintaining high accuracy for critical parameters while reducing overhead for less critical ones, thus balancing accuracy with processing time.
Data Source
AI summary
Computing clusters can be automatically configured according to some aspects described herein. For example, a system can receive configuration datasets from instantiated objects in a management cluster. The configuration datasets can be for configuring target objects in managed clusters, where the managed clusters are separate from the management cluster. The system can then configure the target objects within each of the managed clusters based on the configuration datasets.