View source for Elasticsearch B.V. (20240267316). Distributed Network Data Management Systems and Method simplified abstract

=Distributed Network Data Management Systems and Method=


==Organization Name==

[[:Category:Elasticsearch B.V.|Elasticsearch B.V.]]


[[Category:Elasticsearch B.V.]]

==Inventor(s)==

[[:Category:Andrew Wilkins of Perth (AU)|Andrew Wilkins of Perth (AU)]][[Category:Andrew Wilkins of Perth (AU)]]

[[:Category:Ron Cohen of Copenhagen (DK)|Ron Cohen of Copenhagen (DK)]][[Category:Ron Cohen of Copenhagen (DK)]]

==Distributed Network Data Management Systems and Method - A simplified explanation of the abstract==


This abstract first appeared for US patent application 20240267316 titled 'Distributed Network Data Management Systems and Method

==Simplified Explanation==
The patent application describes systems and methods for managing application performance across networks. It involves distributed computing devices running applications, with collectors positioned near each device to sample trace events and identify relevant traces using probabilistic sets and tail-based sampling.

* Geographically distributed computing devices running applications
* Collectors positioned near computing devices to sample trace events
* Use of probabilistic sets and tail-based sampling to identify relevant traces
* Bandwidth savings, network cost reduction, and improved cyber security

==Potential Applications==
This technology can be applied in various industries where monitoring and optimizing application performance across networks is crucial, such as:
* IT and software development
* Telecommunications
* E-commerce
* Financial services

==Problems Solved==
The technology addresses the following problems:
* Efficient monitoring of application performance across distributed networks
* Identification of relevant traces for performance optimization
* Reduction of bandwidth usage and network costs

==Benefits==
The benefits of this technology include:
* Improved application performance management
* Enhanced cyber security through efficient trace event sampling
* Cost savings in terms of bandwidth and network expenses

==Commercial Applications==
* "Optimizing Application Performance Across Networks: A Cost-Effective Solution for Businesses"
This technology can be commercialized as a service or software solution for businesses looking to enhance their application performance management across distributed networks.

==Prior Art==
Readers interested in prior art related to this technology can explore research papers, patents, and industry publications on application performance management, distributed computing, and network monitoring.

==Frequently Updated Research==
Stay updated on the latest research in application performance management, distributed systems, and network optimization to leverage the most current advancements in the field.

==Questions about Application Performance Management==
===How does this technology improve cyber security in application performance management?===
The technology enhances cyber security by efficiently sampling trace events and identifying relevant traces, which helps in detecting and mitigating potential security threats.

===What industries can benefit the most from this application performance management technology?===
Various industries such as IT, telecommunications, e-commerce, and financial services can benefit from this technology by optimizing their application performance across distributed networks.


==Original Abstract Submitted==

systems and methods for application performance management across one or more networks are disclosed. a system includes a plurality of geographically distributed computing devices executing one or more applications. a plurality of collectors are distributed across the one or more networks, each collector being positioned proximate a respective computing device. the collectors may sample, by each of the plurality of collectors, a plurality of trace events received from the applications executing on the computing devices proximate the collector. the collectors may retain in memory sampled trace events that meet a configurable attribute. the collectors may use probabilistic sets and tail-based sampling to determine root events and policies for identifying relevant traces. benefits can be achieved in bandwidth savings, network cost and cyber security.



[[Category:H04L43/10]]
[[Category:CPC_H04L43/10]]