Virtual Infrastructure Management Server Datastore Maintenance Automation
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Solution Overview
Problem
In virtualized computing environments, manually identifying and taking operational actions on virtual machines (VMs) whose virtual disks are stored in a datastore scheduled for maintenance is time-consuming and difficult due to the potential spread of datastores across multiple host clusters and environments.
Innovation Solution
A virtual infrastructure management (VIM) server is implemented with configuration settings for VMs to define actions for datastore unavailability and a mechanism to track mounted datastores and VMs, allowing automatic identification and execution of storage-unavailability-response actions, such as powering off VMs or migrating disks, when a datastore is scheduled to be brought offline.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual identification and operational actions on VMs are performed, then operational control and monitoring are maintained, but time consumption and operational difficulty increase significantly
Solution Approach 1:
The system performs preliminary actions by automatically identifying all VMs associated with a datastore before maintenance begins. The VIM server proactively queries the datastore mapping information and prepares the list of affected VMs in advance, so that when maintenance is initiated, the administrator only needs to approve or review the pre-identified list rather than manually searching for affected VMs during the maintenance window.
Solution Approach 2:
The VIM server acts as an intermediary between the storage infrastructure and the VM management system. It receives maintenance requests from the storage side, automatically resolves the mapping between datastores and VMs using its internal tracking mechanisms, and then communicates the affected VMs back to administrators or automation systems. This intermediary role eliminates the need for administrators to manually perform the complex mapping lookup process.
2Productivity
If automated identification and processing of VMs is implemented, then time and effort are reduced, but system complexity increases
Solution Approach 1:
The VIM server leverages its existing multi-functional role in the virtualized environment to handle datastore-VM mapping queries. Rather than introducing a dedicated automation tool, the existing VIM server—which already performs resource management, monitoring, and coordination—extends its capabilities to include automatic identification of VMs affected by datastore maintenance. This universal approach avoids adding separate complex systems while achieving automation.
Solution Approach 2:
The system implements self-service by enabling the VIM server to autonomously query its own internal datastore mapping information and automatically generate the list of affected VMs without human intervention. The automation uses pre-existing tracking data structures that the VIM server maintains for other management functions, allowing it to serve itself in the context of maintenance coordination without requiring external automation tools or complex integrations.
3Measurement precision
If comprehensive tracking of datastores and VMs is implemented, then automated identification accuracy is improved, but data management complexity increases
Solution Approach 1:
The patent merges the datastore tracking functionality with the existing VIM server's resource management capabilities. Instead of maintaining separate tracking systems for datastores and VMs, the solution integrates both tracking dimensions into a unified data structure within the VIM server. This consolidation allows the system to accurately identify VMs by datastore while avoiding the complexity of multiple independent tracking mechanisms.
Data Source
AI summary
Techniques for automated datastore unavailability handling are provided. In one set of embodiments, a computer system can receive a request to bring a datastore offline and, in response to the request, identify one or more virtual machines (VMs) in a virtualized computing environment that have one or more virtual disks stored in the datastore. The computer system can then, for each of the one or more VMs, determine an action to be taken with respect to the VM in response to the datastore's unavailability and trigger execution of the action.