Invention Application
- Patent Title: OPTIMIZING APPLICATION PERFORMANCE WITH MACHINE LEARNING
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Application No.: US17213707Application Date: 2021-03-26
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Publication No.: US20220308981A1Publication Date: 2022-09-29
- Inventor: Jenna Zeigen , Natalie Qabazard , Anuj Nair , Aaron Maurer , Yiling Chen
- Applicant: Slack Technologies, Inc.
- Applicant Address: US CA San Francisco
- Assignee: Slack Technologies, Inc.
- Current Assignee: Slack Technologies, Inc.
- Current Assignee Address: US CA San Francisco
- Main IPC: G06F11/34
- IPC: G06F11/34 ; G06N20/00

Abstract:
Media, methods, and systems are disclosed for optimizing performance of a running application in connection with a group-based communication system. Log data is collected regarding prior metrics for applications that have encountered performance events. Application state information is monitored and a machine-learning model mapping application metrics to performance outcomes predicts whether the running application will encounter a performance event. The machine-learning model mapping application metrics to performance outcomes is trained based on the collected logs. Based on whether a degradation outcome will be impactful, an application performance parameter may be degraded.
Public/Granted literature
- US11620173B2 Optimizing application performance with machine learning Public/Granted day:2023-04-04
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