Oracle international corporation (20240126564). CONFIGURING AN ENRICHED DATA METRICS PIPELINE simplified abstract
Contents
- 1 CONFIGURING AN ENRICHED DATA METRICS PIPELINE
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 CONFIGURING AN ENRICHED DATA METRICS PIPELINE - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Unanswered Questions
- 1.11 Original Abstract Submitted
CONFIGURING AN ENRICHED DATA METRICS PIPELINE
Organization Name
oracle international corporation
Inventor(s)
Swapnil Sinvhal of Belmont CA (US)
Elizabeth Li of Sugar Land TX (US)
CONFIGURING AN ENRICHED DATA METRICS PIPELINE - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240126564 titled 'CONFIGURING AN ENRICHED DATA METRICS PIPELINE
Simplified Explanation
The abstract describes techniques for configuring an enriched data metrics pipeline (DMP) for nodes of a heterogeneous computing platform. The unenriched DMP provides node-level unenriched data to a service, which generates node-level data metrics. The enriched DMP is configured based on node configuration data to provide node-level enriched data to the service less frequently, allowing the service to generate fleet-level data metrics.
- Obtaining node configuration data for different kinds of nodes on a heterogeneous computing platform
- Configuring an enriched data metrics pipeline to provide node-level enriched data less frequently than unenriched data
- Generating fleet-level data metrics based on node-level enriched data
Potential Applications
The technology can be applied in various industries such as data analytics, IoT, cloud computing, and performance monitoring.
Problems Solved
1. Efficient data processing and analysis for heterogeneous computing platforms 2. Generating fleet-level data metrics from node-level enriched data
Benefits
1. Improved performance monitoring and optimization 2. Enhanced data analytics capabilities 3. Streamlined data processing workflows
Potential Commercial Applications
Optimizing cloud computing infrastructure, enhancing IoT data analytics, improving performance monitoring in data centers.
Possible Prior Art
Prior art may include existing data processing and analytics tools for heterogeneous computing platforms, as well as techniques for generating fleet-level data metrics.
Unanswered Questions
How does the technology handle real-time data processing?
The abstract does not mention the real-time processing capabilities of the enriched DMP.
What security measures are in place to protect the data being processed?
The abstract does not address the security aspects of the data metrics pipeline.
Original Abstract Submitted
techniques for configuring an enriched data metrics pipeline (dmp) include: obtaining node configuration data associated with an unenriched dmp for nodes of a heterogeneous computing platform, including (a) a first kind of node including an application programming interface (api) for obtaining unenriched data associated with the first kind of node and (b) a second kind of node including an api for obtaining unenriched data associated with the second kind of node; the unenriched dmp being configured to provide node-level unenriched data to a service according to a first schedule; the service being configured to generate node-level data metrics based on the unenriched data; based on the node configuration data, configuring an enriched dmp to provide node-level enriched data to the service according to a second schedule that is less frequent than the first schedule; the service being configured to generate fleet-level data metrics based on the node-level enriched data.
