Hierarchical Service Rendering Engines for Cloud Disaster Recovery
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Solution Overview
Problem
Current cloud computing environments face challenges in automating the placement, rendering, and provisioning of cloud services, leading to significant time delays and scalability issues, particularly during failures which can result in lengthy service outages requiring manual re-provisioning.
Innovation Solution
A distributed hierarchical mechanism is introduced, utilizing service rendering engines across multiple levels (network, data center, and POD) to automate the placement, rendering, and provisioning of cloud services, enabling automatic service relocation and disaster recovery without human intervention by leveraging abstract device brokers and resource managers to manage policy-based cloud service requests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If centralized orchestration tools are used to manage cloud services, then service placement and provisioning can be controlled, but the system complexity increases and scalability deteriorates
Solution Approach 1:
The patent divides the centralized orchestration system into distributed service rendering engines deployed across multiple data centers and hierarchical levels. Each engine independently handles service placement and provisioning in its local domain, eliminating the need for a single complex centralized controller while maintaining automated service management across the entire cloud infrastructure.
Solution Approach 2:
The patent introduces a hierarchical dimension to service rendering, organizing engines across multiple levels (global, regional, local) and data centers. This hierarchical structure distributes complexity vertically across layers while maintaining coordinated service management, transforming the flat centralized architecture into a multi-dimensional distributed system.
2Reliability
If manual re-provisioning is performed during failures, then service restoration can be achieved, but service outage duration increases
Solution Approach 1:
The patent pre-configures service rendering capabilities across multiple data centers and hierarchical levels before failures occur. Service rendering engines are deployed in advance with the authority and capability to immediately provision services locally when failures are detected, eliminating the need for manual intervention and reducing outage duration to minutes or seconds.
Solution Approach 2:
The patent enables service rendering engines to autonomously detect failures, select alternative data centers or resources, and re-provision services without human intervention. The distributed engines self-manage service restoration by leveraging local knowledge of available resources, automatically recovering services while minimizing outage time.
3Adaptability or versatility
If highly customizable orchestration tools are deployed to interface with diverse cloud elements, then adaptability improves, but implementation time and operational complexity increase
Solution Approach 1:
The patent creates service rendering engines with universal interfaces that can interact with multiple types of cloud elements (virtual machines, storage, networks, applications) through standardized protocols. This universal design enables the same engine architecture to adapt to diverse cloud elements without requiring custom integration work for each new element type, significantly reducing implementation time while maintaining versatility.
Data Source
AI summary
Techniques are provided to move the services performed on one device to another device in a cloud computing system for a variety of reasons including failure, maintenance or upgrade of the device. A notification is received that services performed by an impacted device in a domain of a plurality of hierarchical domains need to be moved. A determination is made as to whether there are replacement resources available in the domain to perform the services, and if so, the replacement resources are automatically rendered to perform the services. The process continues to higher level domains that have a view into the capabilities of subordinate domains in order to determine where to move the services within the cloud computing system.