VM Scale Set Provisioning with Equivalent Image Labels
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing provisioning systems face challenges in maintaining consistent VM software configurations across a VM scale set when the original software images become obsolete or change, leading to errors and the need for manual customer intervention.
Innovation Solution
A VM-metadata service analyzes the metadata of existing VMs to identify software updates and updates the virtualized software, allowing the VM-provisioning service to automatically match the new VM with the correct software configuration by machine-learning an equivalent label from a label database.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If the original software image label is used to provision new VMs, then provisioning speed is improved, but reliability deteriorates when the original label becomes obsolete or changes
Solution Approach 1:
The system performs preliminary actions by analyzing metadata from existing VMs before provisioning new ones. The VM-metadata service proactively identifies software updates and determines equivalent labels in advance, so when a new VM needs to be provisioned, the correct updated configuration is already identified and ready to be applied, preventing obsolescence issues
Solution Approach 2:
The system implements feedback by continuously monitoring existing VMs for software updates through metadata analysis. The VM-metadata service receives feedback about software changes from the VM scale set, processes this information to identify equivalent labels, and feeds back the updated configuration information to the VM-provisioning service for applying to new VMs
2Manufacturing precision
If manual customer intervention is required to update software images, then manufacturing precision is improved, but ease of operation deteriorates
Solution Approach 1:
The system enables self-service by automating the entire process of detecting software updates, analyzing metadata, identifying equivalent labels, and provisioning new VMs with correct configurations. The VM-metadata service and VM-provisioning service work together autonomously without requiring manual customer intervention, maintaining precision through automated metadata analysis while significantly improving ease of operation
3Adaptability or versatility
If software updates are automatically detected and applied, then adaptability is improved, but device complexity increases
Solution Approach 1:
The system applies segmentation by dividing the complex provisioning task into distinct functional components: the VM-metadata service that handles metadata analysis and update detection, and the VM-provisioning service that handles label identification and VM creation. This segmentation manages complexity by creating specialized, modular services with clear responsibilities while enabling sophisticated adaptability to software updates
Data Source
Figure 1
Figure 2
Figure 3
AI summary
Cloud services intelligently provision new VMs for a VM scale set when the original label that included the OS or other software images used to provision existing VMs of the VM scale set is no longer available or has been changed. Metadata of the existing VMs are analyzed to identify an OS image or other software image used to provision the existing VMs. The metadata also reveals updates that are running on the new VMs. These updates include software that was not part of the original label used to provision the existing VMs and are used to find the second label in a label database. The second labels include the OS or software of the existing VMs-or a later version thereof-and some portion of the updates. A VM-provisioning service uses the second label to provision the new VM.