Autonomous Agents for Virtual Desktop Self-Healing
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Solution Overview
Problem
Cloud-based virtual desktop systems face challenges in managing and troubleshooting problematic events without centralized orchestration, leading to decreased responsiveness and increased troubleshooting time.
Innovation Solution
A virtual desktop system with a control plane that configures and stores rules for agents to execute actions autonomously, allowing them to diagnose and repair issues independently, reducing the need for centralized coordination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If centralized coordination is used to manage and troubleshoot virtual desktops, then system control and management are improved, but responsiveness and troubleshooting time deteriorate due to orchestration delays
Solution Approach 1:
The patent divides the centralized control function into distributed segments by deploying autonomous agents on individual virtual desktops and infrastructure components. Each agent independently monitors and troubleshoots its local environment, eliminating the need for centralized orchestration delays while maintaining system-wide reliability through coordinated autonomous actions.
Solution Approach 2:
The patent implements self-service by enabling virtual desktops and infrastructure components to autonomously diagnose and resolve their own issues through embedded agents. These agents continuously monitor system state, detect problems, and execute remediation actions without requiring centralized coordination, thereby reducing troubleshooting time while maintaining reliable system control.
2Reliability
If centralized orchestration is used to troubleshoot problematic events, then comprehensive system management is improved, but system responsiveness deteriorates due to coordination overhead
Solution Approach 1:
The patent segments the centralized orchestration function into distributed autonomous agents deployed across virtual desktops and infrastructure components. Each agent independently responds to local events in real-time, eliminating coordination overhead and improving system responsiveness while maintaining comprehensive system management through the collective action of multiple agents.
Solution Approach 2:
The patent implements preliminary action by pre-deploying autonomous agents on virtual desktops and infrastructure components with pre-configured troubleshooting capabilities. These agents are ready to immediately detect and respond to problems as they occur, eliminating the delay of waiting for centralized orchestration instructions and improving system responsiveness.
3Reliability
If autonomous self-healing agents are deployed to perform diagnostic and repair operations, then system responsiveness and reliability are improved, but system complexity increases
Solution Approach 1:
The patent applies universality by designing a standardized autonomous agent architecture that can perform multiple diagnostic and repair functions across different virtual desktops and infrastructure components. This multi-functional agent design improves system reliability through comprehensive self-healing capabilities while managing complexity by reusing the same agent framework across diverse systems.
Solution Approach 2:
The patent manages complexity through parameter changes by configuring autonomous agents with adjustable monitoring thresholds, response priorities, and remediation parameters. This allows the system to adapt agent behavior to specific environments and requirements without fundamentally changing the agent architecture, thereby improving reliability while controlling system complexity through flexible parameter tuning.
Data Source
AI summary
A virtual desktop system includes one or more virtual desktops, associated cloud infrastructure, and a control plane configured to manage a life cycle of the one or more virtual desktops on the cloud infrastructure. The cloud infrastructure is configured to: (i) receive a first configurable set of rules from the control plane, (ii) store the first configurable set of rules, (iii) evaluate the first configurable set of rules to determine whether conditions associated with one or more rules are met, (iv) based on the conditions being met, perform one or more actions to execute the one or more rules, and (v) provide diagnostics related to the one or more executed rules to the control plane for further analysis.