Service Endpoint Creation for Cloud Disaster Recovery
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Solution Overview
Problem
Cloud-based disaster recovery systems face inefficiencies due to recovery virtual machines connecting to external networks for accessing cloud-based storage services, leading to performance and bandwidth issues during disaster recovery processes.
Innovation Solution
A system that automatically creates service endpoints allowing recovery virtual machines to access storage services directly within the cloud service system's private network by monitoring network access connections, parsing URLs to determine datastore and storage services, and configuring service endpoints based on this information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If recovery virtual machines clone all aspects of production virtual machines including external network access mechanisms, then the recovery process is simplified and automated, but the access performance and bandwidth efficiency deteriorate due to reliance on external networks
Solution Approach 1:
The system performs preliminary actions by monitoring and capturing network access connection information (URLs, domain names, data store identifiers) from production virtual machines before disaster events occur. This information is stored in advance so that when a recovery virtual machine is created, the service endpoint configuration can be automatically generated without requiring real-time analysis or manual intervention, thus resolving the contradiction between automation simplicity and performance optimization.
Solution Approach 2:
The patent introduces a service endpoint as an intermediary component that mediates between the recovery virtual machine and the cloud-based data storage service. Instead of directly cloning external network access mechanisms, the service endpoint acts as a local intermediary within the cloud service system's private network, routing access requests efficiently while maintaining the automated recovery process. This intermediary approach preserves automation while eliminating performance degradation from external network dependencies.
2Device complexity
If recovery virtual machines use external network connections to access cloud-based storage services, then system complexity is reduced by using standard access mechanisms, but bandwidth efficiency and access speed deteriorate
Solution Approach 1:
The patent applies local quality by creating service endpoints that are locally configured within the cloud service system's private network for each recovery virtual machine. Instead of using a generic external access mechanism for all virtual machines, each recovery VM gets a locally optimized service endpoint that routes traffic through the private network. This localizes the access path, maintaining simplicity in configuration while dramatically improving access speed by eliminating external network hops.
3Productivity
If service endpoints are manually configured for each recovery virtual machine, then access performance is optimized through direct private network connections, but the complexity and time required for configuration increases
Solution Approach 1:
The system implements self-service by enabling recovery virtual machines to automatically obtain their service endpoint configurations without manual intervention. The endpoint deployment system monitors network access connections from production VMs, extracts necessary information (URLs, domain names, data store identifiers), and automatically generates and assigns service endpoint configurations to recovery VMs. This self-service approach maintains optimized private network access efficiency while eliminating manual configuration complexity through automation.
4Adaptability or versatility
If external network access mechanisms are used for cloud service access, then adaptability to different cloud service providers is improved, but bandwidth consumption and execution time increase
Solution Approach 1:
The patent segments the network access path into two distinct parts: the control plane (which maintains adaptability through standard external access mechanisms for discovering and configuring services) and the data plane (which uses optimized private network connections through service endpoints for actual data transfer). This segmentation allows the system to maintain cloud service access flexibility at the control level while eliminating bandwidth consumption inefficiencies at the data transfer level, where large volumes of data are accessed between recovery VMs and storage services.
Data Source
AI summary
Described is a system (and method) that provides the ability to create an endpoint to allow cloud-based components to access services directly using network infrastructure of a cloud system. To provide such an ability, access connections from components of a production system to the cloud system may be monitored to derive a storage service and a datastore based on portions of a domain name. The derived storage service and datastore are then used to determine configuration settings required to automatically create a service endpoint. The service endpoint may then be deployed within the cloud system allowing the cloud-based component to access the storage service directly. Accordingly, the system provides the ability to automatically configure and deploy service endpoints by leveraging information derived from monitoring network access connections between a production environment and a cloud environment.