Cloud Service State Reconciliation for Event-Driven Deployment
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Solution Overview
Problem
Existing cloud service platforms struggle with automating the deployment and maintenance of cloud services, particularly when multiple services need to be synchronized across different regions, leading to inefficiencies and resource wastage due to out-of-date operations.
Innovation Solution
A computer-implemented reconciliation process that automatically detects and reconciles the current state of a cloud service with a goal state, generating a plan of operations to achieve the goal state, including asynchronous execution of operations without dependencies and tracking operation states to optimize resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional batch deployment methods are used for cloud services, then deployment simplicity is maintained, but deployment speed and defect discovery rate decrease
Solution Approach 1:
The patent segments the monolithic batch deployment process into multiple independent, fine-grained deployment units that can be executed separately. Each deployment unit represents a discrete operation that can be tracked, managed, and reconciled independently, enabling faster iteration and defect isolation while maintaining overall deployment coherence through the reconciliation mechanism.
Solution Approach 2:
The patent introduces dynamic state tracking and reconciliation mechanisms that adapt the deployment process in real-time. The system continuously monitors the actual state of cloud resources against the desired state and dynamically adjusts subsequent deployment operations, enabling rapid response to defects and changes while maintaining deployment simplicity through automated state management.
2Adaptability or versatility
If cloud service resources are frequently updated and redeployed, then service adaptability and responsiveness improve, but resource consumption and operational overhead increase
Solution Approach 1:
The patent implements partial updates by comparing the desired state with the actual state and executing only the necessary reconciliation operations. Instead of performing complete redeployments, the system identifies and executes only the minimal set of operations required to achieve state alignment, reducing resource consumption while maintaining service adaptability through targeted updates.
Solution Approach 2:
The patent establishes a feedback loop where the system continuously monitors the actual state of cloud resources and compares it against the desired state. This feedback mechanism enables intelligent decision-making about which resources need updating and which can remain unchanged, optimizing resource utilization while maintaining high service adaptability through responsive, data-driven update decisions.
3Productivity
If manual portal operations are used for cloud service deployment, then operational control is maintained, but deployment efficiency and timeliness decrease
Solution Approach 1:
The patent implements self-service automation where the system automatically performs state reconciliation and executes necessary deployment operations without requiring manual portal intervention. The reconciliation engine autonomously compares desired and actual states, generates deployment plans, and executes operations, thereby dramatically improving deployment efficiency while maintaining operational control through automated decision-making and state management.
4Manufacturing precision
If comprehensive state tracking and reconciliation operations are performed, then deployment accuracy and service alignment improve, but processing time and system complexity increase
Solution Approach 1:
The patent applies partial action by performing reconciliation operations only on resources that have changed or are relevant to the current deployment context. The system identifies the minimal subset of resources requiring state verification and reconciliation, avoiding unnecessary processing of unchanged resources. This approach maintains high deployment accuracy while significantly reducing reconciliation processing time through selective, targeted operations.
Data Source
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AI summary
A computer system is configured to perform a reconciliation process with respect to a current state of a cloud service and a goal state of the cloud service. Performing the reconciliation process includes obtaining the current state of the cloud service, obtaining the goal state of the cloud service, evaluating the current state against the goal state to generate a reconciliation plan that comprises a plurality of operations, and starting execution of the reconciliation plan at the cloud service including performing at least one of the plurality of operations in the reconciliation plan. In response to detecting an event, the computer system reperforms the reconciliation process again such that one or more current state, the goal state, or the reconciliation plan changes.