Service Configuration Engine Automating Provisioning Dependencies
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Solution Overview
Problem
The complexity of managing and provisioning computing environments, such as data centers, leads to time-consuming and error-prone manual processes, requiring significant administrator time and increasing costs due to the need for manual configuration and management of numerous hardware components and dependencies.
Innovation Solution
A method and system for automating service configuration and deployment using a Service Configuration and Deployment Engine (SCDE) that provides a virtualization layer to communicate with provisioning tools, collect real-time data from agents, and manage dependencies, reducing human error and optimizing provisioning decisions through integration with observability and policy-based network management systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual provisioning processes are used by administrators, then flexibility and control over configuration decisions are maintained, but provisioning time and human error increase significantly
Solution Approach 1:
The provisioning system performs self-service by automatically executing configuration tasks without human intervention. The automation engine reads provisioning manifests, determines dependencies, and executes provisioning steps autonomously, eliminating manual administrator actions while maintaining accuracy and reducing provisioning time.
Solution Approach 2:
The patent replaces the mechanical manual process of administrator actions with an automated software-based system. The automation engine substitutes human operators by programmatically executing provisioning tasks, thereby eliminating human error and significantly reducing the time required for system provisioning.
2Ease of operation
If administrators manually manage dependencies between provisioning tasks, then control over task ordering is maintained, but complexity and error-proneness increase
Solution Approach 1:
The automation engine acts as an intermediary between provisioning tasks and dependencies. It automatically determines task ordering by analyzing dependency relationships defined in the provisioning manifest, eliminating the need for administrators to manually manage complex dependency chains while ensuring correct execution order.
Solution Approach 2:
The system uses provisioning manifests that copy and define all dependency relationships in a structured format. This declarative approach allows the automation engine to automatically infer task ordering from the manifest definitions without requiring administrators to manually configure complex dependency management logic.
3Productivity
If sequential provisioning is performed by administrators, then dependency compliance is ensured, but productivity and throughput decrease
Solution Approach 1:
The automation engine dynamically determines provisioning execution order based on dependency analysis. It can adaptively sequence tasks by analyzing the provisioning manifest and real-time system state, allowing parallel execution of independent tasks while maintaining correct ordering for dependent tasks, thereby maximizing throughput without compromising dependency compliance.
Solution Approach 2:
The system implements feedback mechanisms where the automation engine continuously monitors task execution status and updates the provisioning state. This feedback loop ensures that dependency constraints are enforced while enabling efficient task scheduling, as the engine can adjust execution order based on completed tasks and remaining dependencies.
4Reliability
If human operators are involved in provisioning decisions, then optimization decisions can be made based on experience, but operator error and inconsistency increase
Solution Approach 1:
The system transforms provisioning from a manual decision-making process to an automated parameter-driven process. Provisioning manifests define all configuration parameters and dependencies in a structured format, allowing the automation engine to consistently execute identical operations without human variation, thereby ensuring reliability and consistency across all provisioning operations.
Data Source
AI summary
A method for automating provisioning of services in a target computer system. The method includes providing a set of provisioning adaptors each defining an interface to a provisioning application and receiving a provisioning request from a user interface. The method further includes identifying one of the provisioning applications for completing a provisioning operation based on the received provisioning request, and then, invoking the identified one of the provisioning applications using one of the interfaces defined by one of the provisioning adaptors associated with the provisioning tool or application. The method includes providing agents on the components of the target computer system collecting configuration regarding the components from the provisioning agents, and using the collected data during identifying provisioning applications and invoking the identified applications. Dependencies are determined during the method that need to be complied with during provisioning, and the method includes ensuring compliance with these dependencies.