Self-Describing Services Dynamic Dependency Resolution
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Solution Overview
Problem
Existing systems face challenges in efficiently managing and deploying computer-implemented services due to reliance on static deployment schemes, leading to redundant instances and wastage of limited computing resources.
Innovation Solution
The system employs self-describing services stored in a repository, allowing for dynamic identification and deployment of dependencies, thereby enabling the instantiation of complete services without relying on static or hard-coded deployment methods, utilizing containers and sidecars to manage and integrate services dynamically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If static or hard-coded deployment schemes are used, then deployment simplicity is maintained, but redundant service instances are created and computing resources are wasted
Solution Approach 1:
The patent transforms static deployment schemes into dynamic ones by introducing self-describing services that automatically declare their dependencies. The system dynamically discovers and instantiates only the necessary complementary services based on actual runtime needs, rather than pre-defining all service instances. This dynamic approach eliminates redundant service instances while maintaining deployment simplicity through automated service composition.
Solution Approach 2:
The patent implements self-service by enabling services to describe themselves and their dependencies through self-describing metadata. Each service automatically identifies what complementary services it needs, and the system automatically instantiates these services without manual intervention. This self-describing mechanism replaces static hard-coded deployment configurations with automated, adaptive service discovery and instantiation.
2Ease of operation
If static deployment schemes are used, then deployment process is simple, but service dependencies are not dynamically identified leading to resource inefficiency
Solution Approach 1:
The system replaces static deployment processes with dynamic service discovery. Instead of following predetermined deployment paths, the system dynamically identifies service dependencies at runtime through self-describing metadata. This allows the deployment process to adapt to actual service requirements, improving deployment efficiency while keeping the process simple through automated dependency resolution.
Solution Approach 2:
The patent introduces feedback mechanisms where services provide self-describing information about their dependencies. The deployment system uses this feedback to automatically instantiate only the necessary complementary services. This feedback loop enables the system to optimize resource allocation by deploying exactly what is needed, improving productivity without complicating the deployment process.
3Reliability
If redundant service instances are deployed, then service availability is increased, but computing resource consumption increases
Solution Approach 1:
The patent enables services to automatically describe their dependencies and requirements. The system uses this self-describing information to intelligently instantiate only the necessary service instances, avoiding redundant deployments. This self-service approach ensures that service availability is maintained through proper dependency satisfaction while minimizing computing resource consumption by deploying only what is actually needed.
Solution Approach 2:
The system changes the parameter of service instantiation from static (always deploy all possible instances) to dynamic (deploy only when dependencies are satisfied). By using self-describing services, the system can adaptively determine the optimal number of service instances to deploy, maintaining reliability through proper service composition while reducing resource consumption by eliminating redundant instances.
Data Source
AI summary
Methods and systems for managing service deployment are disclosed. To deploy services, dependencies and other characteristics of services may be dynamically analyzed through self-descriptions of the services. The dependencies and other characteristics may be used to identify any number of instances of various instances for deployment to provide a complete service. By dynamically analyzing the self-description of the services, efficiency of use of computing resources may be improved by limiting the deployed services to only those necessary for operation of the complete service.