Dynamic Service Deployment Orchestrator for Telco Networks
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Solution Overview
Problem
Existing service deployment systems are inefficient and ineffective in managing the high dynamic nature of telco services, leading to suboptimal performance due to frequent changes in user demands and deployment configurations.
Innovation Solution
An apparatus and method for automatically and dynamically determining an optimal deployment configuration for software-based services, using a processor to receive service information, determine service metrics, and generate optimal deployment profiles to manage service deployment efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual deployment configuration is used by network operators, then deployment decisions can be made based on service requirements, but the system cannot adapt to frequent changes in user demands and service performance requirements
Solution Approach 1:
The system enables self-service through automated deployment configuration. The orchestrator automatically determines optimal deployment configurations based on service requirements and user demands without requiring manual intervention from network operators. The system monitors service metrics and autonomously adjusts deployment parameters, allowing the network to adapt to changing conditions through self-service mechanisms rather than human operators.
Solution Approach 2:
The system implements feedback loops where service metrics and user demand information are continuously collected and fed back to the orchestrator. This feedback mechanism enables the system to dynamically adjust deployment configurations in response to changing service requirements and user demands, transforming the static manual process into an adaptive automated system that learns from operational data.
2Productivity
If one-time optimal deployment configuration is determined, then initial deployment efficiency is improved, but the configuration becomes suboptimal when user demands change
Solution Approach 1:
The system transitions from static one-time configuration to dynamic continuous optimization. The orchestrator continuously monitors service metrics and user demands, automatically adjusting deployment configurations in real-time or near-real-time. This dynamic approach ensures that deployment efficiency is maintained or improved even as service requirements evolve, eliminating the obsolescence problem of fixed configurations.
Solution Approach 2:
The system performs preliminary actions by pre-establishing deployment configurations for multiple service scenarios and requirements. When user demands change, the orchestrator can quickly select and activate pre-prepared optimal configurations rather than performing lengthy re-optimization calculations, thus maintaining high deployment efficiency while adapting to dynamic conditions.
3Reliability
If deployment configuration is manually decided based on service requirements, then initial service performance can be optimized, but frequent changes in user demands make the approach inefficient
Solution Approach 1:
The system uses feedback mechanisms to continuously monitor service performance metrics and user demand patterns. This real-time information flow enables the orchestrator to detect when performance optimization is needed and automatically initiate reconfiguration, eliminating the time loss associated with manual detection and decision-making processes.
Solution Approach 2:
The orchestrator performs self-service by automatically determining and implementing deployment configuration changes in response to performance requirements and user demands. This eliminates the need for manual intervention and the associated time delays, allowing the system to maintain optimized service performance dynamically without human operator involvement.
4Adaptability or versatility
If software-based services are deployed in data centers, then service flexibility and virtualization are improved, but deployment management complexity increases
Solution Approach 1:
The orchestrator serves as an intermediary between the complex virtualized service infrastructure and the deployment management process. It abstracts the complexity of managing software-based services in data centers by providing a unified interface for configuration management, automatically handling the coordination between multiple virtual network functions and physical resources, thus reducing perceived complexity while maintaining virtualization benefits.
Data Source
AI summary
Provided are apparatus, method, and device for managing deployment of one or more services. The apparatus including: a memory storing instructions; and at least one processor configured to execute the instructions to: receive information associated with a service; determine, based on the received information, an optimal deployment configuration; determine whether or not the service is required to be deployed according to the optimal deployment configuration; and based on determining that the service is required to be deployed according to the optimal deployment configuration, output information defining an action for deploying the service according to the optimal deployment configuration.