VM Fleet Agent Installation via Policy-Driven User Nudges
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Solution Overview
Problem
Existing methods for installing and updating agents on virtual machines (VMs) require technical proficiency and rely on third-party automation tools, leading to unawareness of agent installation needs and potential mismanagement.
Innovation Solution
A policy-controlled pre-installed package in a VM image manages agent installation and updates using a user interface, enabling user-friendly fleet-wide deployment and management without command-line tools or third-party reliance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional software distribution methods are used, then IT administrators have control over installation, but user productivity is reduced due to manual installation requirements
Solution Approach 1:
The system enables users to self-install software agents through a web interface without requiring manual intervention from IT administrators. Users can independently download, install, and configure fleet agents on their devices, transforming the traditional administrator-controlled process into a user-self-service model that eliminates productivity loss while maintaining installation control.
Solution Approach 2:
A web-based interface acts as an intermediary between IT administrators and end users. The web UI allows administrators to push installation requests and receive approvals, while users can review and approve installations without direct administrator involvement. This intermediary system resolves the contradiction by enabling automated control flow while preserving user autonomy.
2Reliability
If manual software installation is required, then security control is maintained, but installation time and complexity increase
Solution Approach 1:
The system performs preliminary actions by pre-configuring software packages with digital signatures and authentication mechanisms before distribution. IT administrators can pre-approve software sources and configure deployment policies in advance, so that when installation is initiated, the security verification is already prepared and can be automatically validated without time-consuming manual checks during the actual installation process.
Solution Approach 2:
The system implements feedback loops where installation requests are automatically verified against pre-configured security policies, and users receive real-time feedback on approval status. The web interface provides immediate confirmation of security validations, allowing rapid decision-making without manual security review delays, thus maintaining security control while reducing installation time.
3Stability of the object's composition
If fleet-wide software deployment is implemented, then software consistency is improved, but network bandwidth is consumed during synchronization
Solution Approach 1:
The system applies local quality by allowing different deployment strategies for different regions or device groups within the fleet. Instead of forcing a uniform synchronization approach across all devices, the system can selectively update only specific device groups or regions that require software consistency, thereby reducing unnecessary network bandwidth consumption while maintaining stability where needed.
Solution Approach 2:
The system implements partial action by deploying software updates to subsets of the fleet rather than forcing complete fleet-wide synchronization at once. Devices can be updated in waves or batches, allowing network bandwidth to be managed more efficiently while still achieving eventual fleet-wide consistency. This partial deployment approach reduces peak bandwidth consumption compared to simultaneous fleet-wide updates.
Data Source
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AI summary
A method for installing an agent at one or more virtual machines (VMs) of a VM fleet includes transmitting a message to a user interface according to a policy defined in a pre-installed package included in a VM image of the VM fleet, receiving a user input indicating to install the agent at the one or more VMs, and installing the agent at the one or more VMs based on the user input.