Managed Control Plane Service for Cloud Application Integration
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Solution Overview
Problem
Complex applications deployed in cloud computing environments require significant effort from engineering teams to integrate and manage various services, including common operational requirements like logging, monitoring, and authentication, which can be repetitive and resource-intensive, especially when changes occur or new requirements are introduced.
Innovation Solution
A managed control plane service (MCPS) streamlines operations by providing plugins for common operational requirements, automating integration, and reducing the need for application developers to write code for these tasks, allowing for easy updates and resource management, thereby simplifying the development, deployment, and maintenance of applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If engineering teams manually integrate and manage various services for complex applications, then customization and control over application components are improved, but the workload, time consumption, and resource requirements increase significantly
Solution Approach 1:
The patent introduces a service integration platform that acts as an intermediary between engineering teams and multiple cloud services. This platform automatically handles service integration, configuration management, and coordination, reducing manual workload while maintaining control through standardized interfaces and abstraction layers.
Solution Approach 2:
The service integration platform provides universal functionality for managing diverse cloud services through a unified interface. It handles common tasks such as authentication, resource provisioning, and configuration across different services, eliminating the need for separate integration efforts for each service type.
2Reliability
If engineering teams become familiar with each service employed in complex applications, then service integration quality is improved, but the learning curve and training requirements increase
Solution Approach 1:
The service integration platform serves as an intermediary that abstracts away service-specific complexities. It provides a unified management interface that handles service integration logic centrally, allowing engineering teams to work with standardized patterns rather than learning each service's unique integration requirements.
Solution Approach 2:
The platform creates standardized templates and patterns for service integration that can be reused across different applications. These templates encapsulate best practices and integration logic, allowing teams to deploy services quickly without extensive learning while maintaining integration quality through proven patterns.
3Adaptability or versatility
If engineering teams are responsible for updating application components when new requirements are identified, then responsiveness to changing requirements is improved, but the maintenance burden and update complexity increase
Solution Approach 1:
The service integration platform acts as an intermediary that manages update coordination across multiple services. When new requirements are identified, the platform handles the complexity of propagating changes through the service architecture, coordinating updates and managing dependencies, thereby reducing maintenance burden on engineering teams.
Solution Approach 2:
The platform performs preliminary analysis and preparation for updates by identifying affected services and coordinating change sequences. This preliminary action reduces update complexity by pre-planning the maintenance workflow before engineering teams begin implementation.
4Adaptability or versatility
If repetitive coding and resource management tasks are performed manually for common operational requirements, then flexibility in handling specific application needs is improved, but the workload and resource consumption increase
Solution Approach 1:
The service integration platform enables self-service automation for common operational requirements such as logging, monitoring, and authentication. It automatically performs repetitive tasks like service configuration, resource provisioning, and operational management, reducing manual workload while maintaining flexibility through configurable parameters and customizable service compositions.
Data Source
AI summary
At a managed control plane service, constituent services and operational requirements of an application are identified. In response to an end-user request directed to the application, contents of an inter-service request are generated at a resource selected by the managed control plane service for a first constituent service, and a response to the message is generated at another resource selected for a second constituent service. Tasks to be performed for the operational requirements are initiated by the managed control plane service.