Dell products l.p. (20240176662). SUPPORT FOR DYNAMIC SCALING simplified abstract
Contents
- 1 SUPPORT FOR DYNAMIC SCALING
SUPPORT FOR DYNAMIC SCALING
Organization Name
Inventor(s)
Julius Jian Zhu of Shanghai (CN)
SUPPORT FOR DYNAMIC SCALING - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240176662 titled 'SUPPORT FOR DYNAMIC SCALING
Simplified Explanation
The abstract describes a method for dynamic scaling of components in an application based on metric values and a custom scaling policy. This allows for automatic updating of the configuration manifest at runtime without additional user effort.
- Acquiring current metric values of components in an application
- Determining target number of replicas based on metric values and scaling policy
- Updating configuration manifest based on target number of replicas
Potential Applications
This technology can be applied in cloud computing environments, microservices architectures, and distributed systems where dynamic scaling of components is required.
Problems Solved
1. Manual scaling of components can be time-consuming and error-prone. 2. Adapting to changing workload demands can be challenging without dynamic scaling capabilities.
Benefits
1. Improved efficiency by automatically adjusting resources based on workload. 2. Enhanced scalability to handle varying levels of demand. 3. Reduced operational costs by optimizing resource allocation.
Potential Commercial Applications
"Dynamic Scaling Automation in Cloud Computing Environments"
Possible Prior Art
Prior art may include existing auto-scaling solutions in cloud platforms such as AWS Auto Scaling or Kubernetes Horizontal Pod Autoscaler.
What are the potential limitations of this technology in real-world applications?
In real-world applications, the effectiveness of dynamic scaling may depend on the accuracy of the metrics used for scaling decisions and the scalability of the underlying infrastructure.
How does this technology compare to existing manual scaling methods in terms of performance and cost?
Compared to manual scaling methods, dynamic scaling offers the advantage of real-time adjustments based on actual workload metrics, potentially leading to better performance and cost optimization.
Original Abstract Submitted
support for dynamic scaling is provided. an example method includes: acquiring a current value of a metric associated with a plurality of components of an application; determining a target number of replicas of at least one component of the plurality of components based on the current value of the metric and a scaling policy for the plurality of components; and updating a configuration manifest of the application based on the target number of replicas of the at least one component. in this manner, the configuration manifest of the application can be automatically updated based on metric values of the components at runtime and a custom scaling policy, thereby achieving dynamic scaling of various components of the application without additional user effort to implement separate dynamic scaling mechanisms.
