Centralized Software Service Governance via Segmented Agents
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Solution Overview
Problem
Existing systems lack centralized governance and control over software and Java applications across virtualized and non-virtualized environments, leading to inefficiencies in resource allocation and quality of service (QoS) management.
Innovation Solution
A system and method that deploy and manage software services using a centralized governance framework, incorporating a Controller and Agents to define policies based on service-level agreements (SLAs), monitor resource usage, and dynamically allocate resources to ensure QoS across both virtualized and non-virtualized platforms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If centralized governance and control are implemented across virtualized and non-virtualized environments, then resource allocation efficiency and QoS management improve, but system complexity increases
Solution Approach 1:
The system segments the heterogeneous infrastructure into virtualized and non-virtualized domains, with domain-specific agents handling local resource management. This segmentation allows centralized governance to operate through modular components rather than monolithic control, reducing overall system complexity while maintaining resource allocation efficiency.
Solution Approach 2:
The controller acts as an intermediary between centralized governance policies and distributed resource management. It translates high-level QoS requirements into domain-specific configurations, enabling efficient resource allocation without direct complex interactions between all system components.
2Reliability
If dynamic resource allocation based on SLAs is implemented, then QoS consistency improves, but monitoring and control overhead increases
Solution Approach 1:
The system implements continuous feedback loops where agents monitor resource utilization and QoS metrics, report to the controller, which then adjusts resource allocation dynamically. This automated feedback mechanism ensures QoS consistency without requiring manual monitoring overhead, as the system self-regulates based on real-time conditions.
Solution Approach 2:
Domain agents autonomously manage their respective environments by interpreting controller policies and making local resource allocation decisions. This self-service capability reduces control overhead by distributing monitoring and adjustment functions to the edges of the system rather than requiring centralized micromanagement.
3Productivity
If automated deployment and management of software services is implemented, then operational efficiency improves, but initial system setup and configuration complexity increases
Solution Approach 1:
The system performs preliminary configuration by establishing domain agents and controller communication channels before software service deployment. SLA templates and resource allocation policies are pre-configured, enabling automated deployment to proceed smoothly without ad-hoc configuration complexity during operational phases.
Data Source
AI summary
A system and method can deploy and manage software services in virtualized and non-virtualized environments. The system provides an enterprise application virtualization solution that allows for centralized governance and control over software and Java applications. Operations teams can define policies, based on application-level service level agreements (SLA) that govern the allocation of hardware and software resources to ensure that quality of service (QoS) goals are met across virtual and non-virtualized platforms. The system use a rules engine that can compare administrator defined constraints with runtime metrics; generate events when a constraint is violated by a metric of the runtime metrics and generate events when a constraint is violated by a metric of the runtime metrics.