Zynga Inc.

Salesforce Com, Inc.

Sudhish Iyer

Michael Waite

Jeffrey Zakrzewski

Oliver Attila Tabay

John vanSuchtelen

Alexandros Ntoulas

John Carlton Ware

Christopher Vance Haire

Paul Yih Yarng Chong

Yuko Yamazaki

Ameya Vilankar

Gaurav Narang

Ana Bertran

Daisuke Kawamoto

Xuyang (Amy) Tan

Lauren Valdivia

Carl Morgenstern

Nicholas Roan

Dmitry Volkov

Xiaohong Huang

Xuyang Tan

Steve Bobrowski

Chin Lee

Kunal Vashi

Zahid Rahman

A system, a non-transitory machine-readable storage medium storing instructions, and a computer-implemented method to adjust twitch response and collision determination to a player's skill level is provided. Gameplay information of a computer-implemented game is accessed. The gameplay information including input information indicating one or more attributes of gameplay input provided by the player. A gameplay skill level of the player of the player is estimated based on the one or more gameplay input attributes. Based on the estimated gameplay skill level of the player, respective values of one or more gameplay parameters that determine on-screen behavior of virtual in-game objects are modified, thereby a gameplay difficulty level is modified.

Dynamic game difficulty modification via swipe input parater change

Adjusting object adaptive modification or game level difficulty and physical gestures through level definition files

Multitier, multitenant architecture of pods comprise multiple stacks with different metrics and workload compositions that constantly change over time. A computer system may identify an overall pod time-to-live (TTL) based on the changing metrics and workloads. The TTL may be a forecasted time that pod remediation is needed to avoid negative impact on pod performance and customer experience. Additionally, the computer system may identify the appropriate remediation(s) for each pod. The computer system may compare and prioritize remediations across a collection of pods with different configurations and workload characteristics based on the TTLs. Other embodiments may be described and/or claimed.

Technologies for capacity remediation in multi-tenant cloud environments

Among other things, embodiments of the present disclosure relate to detecting performance degradation in database systems. For example, some embodiments of the present disclosure help to identify events associated with anomalous database system parameter states and assess the severity of such anomalous events. Other embodiments may be described and/or claimed.

Database system performance degradation detection

Growing community of inventors

San Francisco, CA, United States of America

Sudhish Iyer