Best Known Workspace Configurations for Automated Device-Group Deployment
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Solution Overview
Problem
Deploying workspaces to end-user computing devices is a tedious and largely manual process, as existing technologies fail to customize workspaces to the specific capabilities of individual devices within an organization, requiring substantial manual intervention.
Innovation Solution
Implement a system for managing best known configurations (BKC) of workspaces by defining device groups based on functional roles or organizational departments, associating each group with a customized workspace configuration, and deploying workspaces accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If workspaces are deployed manually to end-user computing devices, then workspace deployment can be performed, but the process is tedious and requires substantial manual intervention
Solution Approach 1:
The system performs preliminary actions by pre-defining device groups based on functional roles or organizational departments and associating each device group with a customized workspace configuration (best known configuration) before actual deployment. This preparation enables automated deployment without manual intervention during the actual deployment process.
Solution Approach 2:
The system enables self-service by allowing workspaces to be automatically deployed to appropriate end-user computing devices based on pre-configured device group associations. The system autonomously matches devices to workspaces without requiring manual intervention, thereby reducing deployment time and increasing automation.
2Adaptability or versatility
If workspaces are deployed without customization to device capabilities, then deployment is simpler, but workspaces are not customized to the particular capabilities of end-user computing devices
Solution Approach 1:
The system segments the organization's computing devices into distinct device groups based on functional roles or organizational departments. Each device group is associated with a specific customized workspace configuration. This segmentation allows the system to manage complexity by organizing devices into manageable groups while providing tailored configurations for each group.
Solution Approach 2:
The system applies local quality by providing different workspace configurations tailored to the specific capabilities and requirements of each device group. Instead of a uniform configuration for all devices, each device group receives a customized configuration that matches its particular capabilities, functional role, or organizational department needs.
3Productivity
If device groups are created and associated with best known configurations, then automated customized deployment is enabled, but the initial setup process becomes more complex
Solution Approach 1:
The system performs the complex initial setup work in advance by defining device groups and associating them with best known configurations before deployment begins. Although this preliminary setup requires initial effort, it enables highly efficient automated deployments thereafter, improving overall productivity.
Solution Approach 2:
The system uses copying by creating reusable device group definitions and best known configuration templates that can be replicated across multiple devices. Once a device group and its associated configuration are defined, they can be copied and applied to multiple end-user computing devices, reducing the complexity of repeated configuration tasks.
Data Source
AI summary
Best known configurations for workspaces can be managed. Device groups can be defined based on functional roles or organizational departments. Each device group can be associated with a workspace along with a best known configuration for the workspace that is based on the device group. Workspaces can then be deployed to the end-user computing devices based on the device group to which each end-user computing device belongs and in accordance with the associated best known configuration.