Profile-Based Software Deployment for Resource Optimization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Standard software application deployments often result in large, resource-intensive packages that include features unused by many users, leading to inefficient use of computing resources and limited customization options for users with unique feature requirements.
Innovation Solution
A method for profiling users based on their interaction data, allowing for customized deployments of software applications that include only the features and resources necessary for each user's specific usage patterns, using a deployment engine to determine and assign appropriate application profiles and deployments dynamically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a single monolithic deployment is provided to all users, then all features are available to every user, but disk space and computing resources are unnecessarily consumed
Solution Approach 1:
The software application is divided into multiple independent deployment packages, each containing a specific subset of features. Users receive only the deployment package that matches their usage patterns, rather than a single monolithic package containing all features. This segmentation allows the system to provide full feature availability across different user groups while minimizing individual disk space consumption.
Solution Approach 2:
Different deployment packages are created with different feature sets tailored to specific user profiles (e.g., beginner, intermediate, expert). Each user receives a deployment with the appropriate quality and depth of features for their specific needs, rather than a uniform deployment for all users. This ensures adaptability while reducing resource consumption for each individual user.
2Quantity of substance
If lean builds with limited features are provided, then disk space consumption is reduced, but users cannot access features outside the predefined category
Solution Approach 1:
The system dynamically determines which deployment package to provide to each user based on their actual usage patterns and behavior, rather than requiring users to pre-select a fixed category. The deployment assignment is flexible and can be adjusted as user behavior changes, allowing users to access features beyond their initial category if their usage patterns evolve to justify it.
Solution Approach 2:
The system monitors user usage patterns and feedback to continuously optimize deployment assignments. If users demonstrate usage patterns that justify access to additional features, the system can reassign them to a different deployment package that includes those features. This feedback mechanism ensures that disk space consumption is minimized while still providing adaptability when users' needs change.
3Adaptability or versatility
If multiple predefined deployment categories are provided, then users can select from different feature sets, but users with unique usage patterns cannot receive customized deployments
Solution Approach 1:
The system automatically analyzes user usage patterns and autonomously determines the most appropriate deployment package for each user without requiring manual intervention or complex configuration. The system serves itself by using usage data to make intelligent deployment assignments, reducing the complexity of deployment management while providing high adaptability to unique user patterns.
Solution Approach 2:
The system uses usage pattern parameters (frequency of feature use, types of operations performed, time of day, device type) to dynamically adjust deployment assignments. By monitoring changes in these parameters over time, the system can automatically transition users between different deployment packages as their needs evolve, providing customization without increasing management complexity.
Data Source
AI summary
Disclosed are techniques for deploying an application. An application system may host one or more software applications, each software application having a plurality of application deployments. A first application deployment is customized based on a first set of user interactions with the application and a second application deployment is different to the first deployment due to being customized based on a second set of user interactions with the application. The second set of user interactions is different to the first set of user interactions. Usage information about a user is received, the usage information indicating a third set of user interactions with an application of the one or more software applications. A user profile of the user is determined from the usage information. The first application deployment is determined based on the user profile. The first application is deployed for the user based on the first application deployment.