公开(公告)号：US11553015B2

公开(公告)日：2023-01-10

申请号：US17222202

申请日：2021-04-05

Applicant: Slack Technologies, Inc.

Inventor： Natalie Qabazard ,  Anuj Nair ,  Tyler Lewis ,  Drew Schuster

IPC: H04L65/403 ,  G06N20/00 ,  H04L67/568 ,  G06Q10/10 ,  G06Q10/06 ,  G06Q50/00 ,  G06N5/04

Abstract: Media, methods, and systems are disclosed for progressively instantiating workspaces for a group-based communication system. A request is received to load group-based communication system workspaces and begin receiving real-time events. The workspaces are classified into a plurality of priority and dormant workspaces. The priority workspaces are instantiated, and real-time events associated with the priority workspaces are transmitted to a group-based communication system. Real-time events are detected that trigger instantiation of dormant workspaces, and associated dormant workspaces added to the set of priority workspaces.

公开(公告)号：US20220308981A1

公开(公告)日：2022-09-29

申请号：US17213707

申请日：2021-03-26

Applicant: Slack Technologies, Inc.

Inventor： Jenna Zeigen ,  Natalie Qabazard ,  Anuj Nair ,  Aaron Maurer ,  Yiling Chen

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.

公开(公告)号：US11620173B2

公开(公告)日：2023-04-04

申请号：US17213707

申请日：2021-03-26

Applicant: Slack Technologies, Inc.

Inventor： Jenna Zeigen ,  Natalie Qabazard ,  Anuj Nair ,  Aaron Maurer ,  Yiling Chen

IPC: G06F11/00 ,  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.

公开(公告)号：US20220321615A1

公开(公告)日：2022-10-06

申请号：US17222202

申请日：2021-04-05

Applicant: Slack Technologies, Inc.

Inventor： Natalie Qabazard ,  Anuj Nair ,  Tyler Lewis ,  Drew Schuster

IPC: H04L29/06 ,  H04L29/08 ,  G06N20/00 ,  G06N5/04 ,  G06Q10/06 ,  G06Q50/00 ,  G06Q10/10

Abstract: Media, methods, and systems are disclosed for progressively instantiating workspaces for a group-based communication system. A request is received to load group-based communication system workspaces and begin receiving real-time events. The workspaces are classified into a plurality of priority and dormant workspaces. The priority workspaces are instantiated, and real-time events associated with the priority workspaces are transmitted to a group-based communication system. Real-time events are detected that trigger instantiation of dormant workspaces, and associated dormant workspaces added to the set of priority workspaces.