Cloud Configuration Classes Ranked by Deployment Performance
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Solution Overview
Problem
Existing cloud-based deployment configurations are complex, inefficient, and lack reusability, leading to increased development efforts and difficulties in customization and performance monitoring.
Innovation Solution
A high-level object-oriented specification language is used to model cloud-based deployments using class definitions with configurable parameters, supporting instantiation, inheritance, and dependency management, enabling efficient configuration and reuse of class definitions across deployments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If traditional cloud deployment configurations are used, then deployment can be performed, but the configurations are complex and lack reusability, leading to increased development efforts
Solution Approach 1:
The patent segments cloud deployment configurations into reusable class definitions with standardized parameters. Each class definition represents a modular unit that can be independently configured and reused, breaking down the complexity of entire deployment configurations into manageable, repeatable components.
Solution Approach 2:
The patent creates universal class definitions that can be applied across multiple cloud deployment scenarios. These class definitions serve as templates that can be instantiated and customized for different deployments, enabling a single configuration structure to handle diverse cloud deployment needs.
2Adaptability or versatility
If traditional cloud deployment configurations are used, then deployment can be performed, but customization and performance monitoring become difficult
Solution Approach 1:
The patent incorporates performance monitoring capabilities directly into the class definition framework. Performance metrics are collected from deployed instances and fed back to evaluate and refine class definitions, enabling continuous improvement and easier monitoring of deployment performance across different configurations.
3Productivity
If existing cloud-based service configurations are used, then services can be deployed, but reusability is limited and development efforts increase
Solution Approach 1:
The patent performs preliminary configuration work by defining standardized class definitions before actual deployments occur. These pre-defined class definitions serve as ready-to-use templates that reduce the need for ad-hoc configuration work during deployment, saving time and improving efficiency.
Solution Approach 2:
The patent enables recovery and reuse of successful configuration patterns through class definitions. When a deployment is successful, the configuration can be captured as a class definition and reused in future deployments, avoiding the need to recreate working configurations from scratch.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for selection of ranked configurations. In one aspect, a method includes providing a plurality of class definitions for selection, each class definition modeling a respective data or functional component of a cloud-based environment using a group of configurable class parameters, each class definition supporting instantiation and inheritance of the class definition in a configuration specification for a cloud-based deployment; deriving respective performance metrics associated with each of the plurality of class definitions based on aggregated performance of multiple cloud-based deployments, wherein the multiple cloud-based deployments had been carried out according to respective configuration specifications that require instantiation of the class definition or a new class definition derived from the class definition; and utilizing the respective performance metrics associated with each of the plurality of class definitions in ranking the plurality of class definitions.