Cloud Elasticity Manager for Dynamic Service Scaling
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Solution Overview
Problem
Cloud computing environments face challenges in managing elasticity, particularly in scaling enterprise applications to meet increased workload demands, which can lead to inefficiencies and administrative complexities.
Innovation Solution
A system and method for elasticity management in cloud computing environments, utilizing service definition packages (SDPs) and service management engines (SMEs) to provision enterprise applications, with an elasticity manager that monitors service health and adjusts resources accordingly, including alerting and orchestrating scaling actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual resource allocation and scaling management is used in cloud computing environments, then administrative control and monitoring capability are maintained, but operational efficiency decreases and administrative complexity increases
Solution Approach 1:
The elasticity manager automatically monitors service health metrics and triggers scaling actions without requiring manual administrative intervention. The system self-manages resource allocation by detecting workload changes and autonomously provisioning or de-provisioning computing resources, thereby improving operational efficiency while reducing administrative complexity
Solution Approach 2:
The patent implements accelerated elasticity management through automated feedback loops that continuously monitor service health and rapidly respond to scaling requirements. The elasticity manager uses real-time metric collection and automated decision-making to speed up the resource allocation process, enabling the system to adapt quickly to changing workload demands without manual intervention
2Adaptability or versatility
If static resource allocation is used for enterprise applications in the cloud, then system stability is maintained, but responsiveness to demand fluctuations deteriorates
Solution Approach 1:
The elasticity manager implements dynamic resource allocation by continuously monitoring service health metrics and adjusting computing resources in real-time based on actual workload demands. This dynamic approach allows the system to scale resources up or down automatically, maintaining both responsiveness to demand fluctuations and system stability through controlled, metric-driven adjustments
Solution Approach 2:
The system employs continuous feedback loops where the elasticity manager collects service health metrics, analyzes workload patterns, and automatically adjusts resource allocation accordingly. This feedback mechanism ensures that scaling decisions are based on actual system performance and demand conditions, maintaining stability while improving adaptability to changing requirements
3Ease of operation
If automated elasticity management is implemented, then operational efficiency and responsiveness improve, but system complexity and monitoring requirements increase
Solution Approach 1:
The elasticity manager provides self-service automated scaling by monitoring service health metrics and triggering appropriate scaling actions without requiring manual administrative intervention. This automation simplifies the user experience and ease of scaling while the system internally manages the complexity of monitoring and decision-making processes
Solution Approach 2:
The elasticity manager is designed as a universal component that can manage multiple services and workload types through a single integrated system. By providing multi-functional capabilities to monitor, analyze, and scale various enterprise applications uniformly, the system reduces overall complexity while maintaining ease of operation across diverse cloud workloads
Data Source
AI summary
A system and method for elasticity management of services for use with a cloud computing environment. In accordance with an embodiment, a cloud platform enables provisioning of enterprise software applications within a cloud environment, including packaging enterprise applications as service definition packages (SDP), and instantiating the services using service management engines (SME). In an embodiment, an elasticity manager can be used to determine the health of the services, and to take appropriate actions, including detecting events, issuing alerts and/or notifying the orchestration engine to manage the service lifecycle, e.g., to respond to an increased demand for particular services.