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Publication Number
US-12688093-B1
Publication Date
2026-07-21
Expiration Date
Abstract
Aspects of the present disclosure provide a monitoring algorithm that ensures that each step of an automated virtual machine reclamation process executes correctly before moving on to the next step. After each step of the process, some implementations can determine whether the resulting data is correct. If the resulting data is incorrect, some implementations can initially revert any fields updated by the process to their correct value. Some implementations can further decide whether to resubmit the virtual machine for reclamation automatically, or queue it for manual review based on, for example, multiple or repeated failures, server or data center failures, etc. Thus, some implementations can not only automate each step of the reclamation process, but also provide process evaluation and error detection for the reclamation process.
Core Innovation
The disclosed subject matter addresses monitoring of an automated virtual machine reclamation workflow. After a reclamation step is performed for multiple virtual machines stored on one or more respective computing devices, the workflow analyzes virtual machine-associated metadata and/or logs to determine whether the step has failed.
When a step failure is detected, at least some metadata associated with the virtual machine is automatically reverted to a previous state that is associated with the failed step. The workflow then automatically attempts to reperform the failed step for the virtual machine, including cases where the failed step is retried after metadata reversion.
To manage repeated failures, the disclosed monitoring further includes classifying or recording failure information and, when repeated failures and/or failure counts exceed thresholds, placing the virtual machine into a manual review queue. The document also describes building a reclamation list using contractual-obligation data and legal-hold data together with inactivity, availability, and/or assignment rules, and carrying out reclamation steps such as tagging for removal, disabling, unassigning users, generating change tickets, and facilitating deletion.
Claims Coverage
The provided material includes three independent claims (clm-00001, clm-00012, clm-00017). Across these claims, the inventive focus is step-failure detection using analyzed VM-associated metadata, automatic metadata reversion to a failed-step-associated previous state, and automatic reattempt of the failed reclamation step, with optional failure escalation and eligibility/selection constraints in dependent claims.
Analyzing VM-associated metadata to determine failed reclamation step
Automatically determining that a step, for a virtual machine of multiple virtual machines, of a virtual machine reclamation process has failed by analyzing metadata associated with the virtual machine resulting from the failed step.
Automatically reverting VM metadata to a failed-step-associated previous state
Automatically reverting at least some of the metadata associated with the virtual machine to a previous state, the previous state being associated with the failed step.
Automatically attempting to reperform the failed reclamation step
Automatically attempting to reperform at least the failed step of the virtual machine reclamation process.
Automatically monitoring automated virtual machine reclamation with step failure detection, metadata reversion, and reattempt
A computing system for monitoring automated virtual machine reclamation, performing a process comprising automatically determining that a step has failed by analyzing metadata, automatically reverting at least some of the metadata to a previous state associated with the failed step, and automatically attempting to reperform at least the failed step.
Collectively, the independent claims cover automated reclamation step failure handling for multiple virtual machines: detecting failure by analyzing VM-associated metadata, reverting related metadata to a failed-step-associated previous state, and automatically attempting to reperform the failed reclamation step. The document’s dependent claim set further includes repeated-failure escalation via a manual review queue and selection/eligibility constraints using contractual obligations and legal holds, as well as inactivity/availability and assignment rules.
Stated Advantages
Avoided or reduced incorrect results by detecting step failures and reverting metadata associated with the failed step.
Automatic retry of failed reclamation steps after metadata reversion.
Routing of repeatedly failed cases to a manual review queue based on failure counts and/or failure type.
Reclamation list generation using contractual-obligation data and legal-hold data together with inactivity/availability/assignment rules.
Documented Applications
Monitoring an automated virtual machine reclamation process for multiple virtual machines stored on one or more computing devices, including automatic detection of failed reclamation steps, metadata reversion, reattempts, and escalation to manual review.
Automated virtual machine reclamation workflow that builds a reclamation list using contractual-obligation data and legal-hold data plus inactivity/availability/assignment rules and then carries out reclamation steps such as tagging for removal, disabling, unassigning users, facilitating deletion, and generating change tickets.
Dashboard and reporting for the reclamation monitoring and reclamation workflow, including metrics such as savings and avoided patch failures, and counts related to VMs reclaimed and manhours saved.
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