Command Suggestion Engine for Cloud Virtual Instances
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In cloud computing environments, users face challenges in identifying the appropriate commands to interact with newly instantiated virtual resource instances, as there is no effective method to determine which commands to use or where to access them.
Innovation Solution
A system and method that analyze a set of commands for virtual resource instances, store information about these commands, and provide a set of suggested commands based on usage patterns, time since provisioning, middleware installation, and other factors, allowing users to access and execute relevant commands for similar or previous instances.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users manually identify commands for virtual resource instances in cloud computing environments, then users have full control over command selection, but users face challenges in identifying the appropriate commands to interact with newly instantiated virtual resource instances
Solution Approach 1:
The system performs preliminary analysis of commands and their associations with virtual resource instances before users need them. Command information including usage patterns, success rates, and instance types is pre-processed and stored in a database, so when users need commands for a newly instantiated instance, the system can quickly retrieve and suggest relevant commands without requiring users to manually search or identify them from scratch
Solution Approach 2:
The system implements feedback mechanisms by analyzing command execution results and usage patterns. When commands are executed against virtual resource instances, the system collects information about which commands were used, their success rates, and associations with specific instance types. This feedback is used to continuously improve command suggestions by updating the database with new patterns and associations, making the system progressively more accurate in suggesting relevant commands
2Ease of operation
If the system provides comprehensive command suggestions for all virtual resource instances, then users can access relevant commands easily, but the system complexity increases due to command analysis and storage requirements
Solution Approach 1:
The system extracts only the essential and most relevant command information from the vast universe of possible commands. Instead of analyzing and storing all possible commands, the system identifies and extracts commands that have been successfully used with virtual resource instances, focusing on those with high usage patterns and success rates. This extraction approach reduces the amount of data that needs to be stored and processed while still providing comprehensive enough suggestions for users
Solution Approach 2:
The system applies local quality by providing different levels of command suggestion detail based on the specific context of each virtual resource instance. Rather than providing the same comprehensive set of commands for all instances, the system tailors the command suggestions to match the specific instance type, usage patterns, and historical data associated with each instance, reducing unnecessary information while maintaining relevance
3Measurement precision
If the system analyzes and stores information about all commands for all virtual resource instances, then accurate command suggestions can be provided, but information storage and processing requirements increase
Solution Approach 1:
The system applies partial action by focusing on analyzing and storing information about only the most frequently used and successful commands rather than attempting to capture all possible commands. The system identifies a subset of commands that represent the majority of useful interactions with virtual resource instances, storing detailed information about these high-value commands while using more aggregated or simplified representations for less common commands, thus reducing overall data storage requirements while maintaining suggestion accuracy
Data Source
AI summary
Embodiments of the present invention provide an approach for identifying commands for virtual resource instances in a networked computing environment (e.g., a cloud computing environment). Specifically, in a typical embodiment, a set of commands for an instance of a virtual resource may be received in a computer memory medium or the like. The commands may then be analyzed and information pertaining to the commands may be stored in a computer storage device or the like. When a user/requester later wishes to identify a command to be utilized for another instance of the virtual resource, the requester can access the information and be provided with a set of suggested commands that are typically utilized for similar and/or previous instances of the virtual resource.