Cloud VM Failover via Image Replication and Delta Sync
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Solution Overview
Problem
In high availability virtualization systems, reserved hosts for failover capacity often remain idle, leading to inefficient resource utilization and high investment costs, as existing solutions do not effectively share failover capacity across clusters within an on-premises network.
Innovation Solution
A method is introduced to restart virtual machines from a failed host in an on-premises cluster to a cloud computing center, involving the transmission of VM images, generation and transmission of difference data, and activation of replicated VMs in the cloud, allowing for efficient resource allocation and reduced idle host costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If hosts are reserved for failover capacity in on-premises networks, then high availability is maintained, but resource utilization deteriorates due to idle hosts
Solution Approach 1:
The patent introduces a cloud dimension to the traditional on-premises failover model. Instead of maintaining idle physical hosts for failover, the system replicates VM images to a cloud computing center and uses difference data to track changes. This dimensional shift from physical host reservation to cloud-based image replication enables failover capacity to be shared across multiple clusters, transforming the failover mechanism from a static on-premises resource to a dynamic cloud-service.
2Productivity
If failover capacity is shared among different clusters, then resource efficiency improves, but system complexity increases
Solution Approach 1:
The patent employs image replication of VMs to the cloud computing center as a foundational copying mechanism. Instead of maintaining complex real-time synchronization between multiple clusters, the system creates static or near-static copies of VM images in the cloud and uses difference data to manage changes. This copying approach simplifies the architecture by decoupling the replication mechanism from the failover execution, allowing the cloud to serve as a centralized repository for multiple clusters.
Solution Approach 2:
The cloud computing center acts as an intermediary between multiple on-premises clusters. It receives VM images from clusters, stores them, and provides them back when needed. The difference data mechanism serves as another intermediary layer that tracks changes between on-premises VM states and cloud-replicated states. This intermediary architecture enables failover capacity sharing without requiring direct complex inter-cluster coordination.
3Reliability
If VM images are replicated to cloud computing center, then failover capability is improved, but data transmission requirements increase
Solution Approach 1:
The patent extracts only the essential VM image data to the cloud computing center rather than replicating entire running VM states continuously. By taking out just the base image and using difference data to capture changes, the system significantly reduces the data transmission volume required for failover preparation. This extraction approach allows the cloud to store compact representations of VM states while maintaining the ability to reconstruct full VM images when failover is needed.
Data Source
AI summary
A method of restarting a virtual machine (VM) running in a cluster in a first data center, in a second data center, includes: transmitting images of VMs, including a first VM, running in the cluster of hosts at a first point in time to the second data center for replication in the second data center; generating difference data representing a difference in an image of the first VM at a second point in time and the image of the first VM at the first point in time; transmitting the difference data to the second data center; setting the first VM to be inactive in the first data center; and communicating with a control plane in the second data center to set as active, and power on, a VM in the second data center using the replicated image of the first VM updated with the difference data.