Abstract: Disclosed herein are a system, method, and computer program product embodiments for elastic job pulling. For example, a first indication of a number of jobs at the job scheduler stage that are yet to be executed is obtained. This indication may be obtained from a job scheduler. A second indication of a total number of available job executors communicatively coupled to the job scheduler may be obtained from the job scheduler. A pull request for a job may be issued to the job scheduler based on at least one of the first indication, the second indication, or a computing resource status of a job executor. The job executor may obtain and execute the job based on the pull request. A status indication of the job may be transmitted, where the status indication indicates whether the job executed successfully.

Abstract: A refrigerator is provided. The refrigerator includes a refrigerator body, a door body and an ice making compartment. The refrigerator body includes a storage compartment. The door body is configured to open or close the storage compartment. The ice making compartment is disposed in the storage compartment, and includes an ice making compartment shell, an ice maker, and an ice storage box. The ice maker is configured to make ice cubes. The ice storage box is located below the ice maker, and is configured to store the ice cubes made by the ice maker. The ice storage box includes a box body and a first ice baffle. At least a part of the first ice baffle is located in the box body, and the first ice baffle is configured to prevent the ice cubes from accumulating at a position of the box body close to the door body.

Abstract: Systems and methods described herein relate to the handling of resource-intensive computing jobs in a cloud-based job execution environment. An unexecuted computing job has a plurality of features. A resource intensity prediction is generated for the unexecuted computing job based on the features and on historical job data that classifies each of a plurality of executed computing jobs as either resource intensive or non-resource intensive. The resource intensity prediction indicates that the unexecuted computing job is predicted to be classified as resource intensive. A predicted resource intensity category of the unexecuted computing job is determined. Utilization data associated with one or more of a plurality of job execution destinations may be accessed. The unexecuted computing job may be assigned to a selected job execution destination from among the plurality of job execution destinations based on the predicted resource intensity category and the utilization data.

Abstract: Flexible scheduling, self-healing, high-utilization strong stability for cellular network communications are discussed. Cellular network communication settings and strategies are developed with communication interval, transmit power data rate, channel delay, spectrum occupancy, source coding, receiving sensitivity, channel coding, signal-to-noise ratio, packet loss rate, channel occupancy rate, reception frequencies frequency band size of data package transmission frequencies, data package structure, modulation scheme, information coding scheme, antenna configuration.

Abstract: The present disclosure relates to suspension systems, control methods, and vehicles. One example suspension system includes a suspension assembly, a driver, a controller, a compressor, and a gas tank. The suspension assembly has a gas spring and a height sensor. The gas tank contains gas, the gas tank is connected to the compressor through a first ventilation pipe, and the compressor is connected to the gas spring through a second ventilation pipe. A first switch valve is disposed on the first ventilation pipe, and a second switch valve is disposed on the second ventilation pipe. The driver is separately electrically connected to the controller, the compressor, the first switch valve, the second switch valve, and the height sensor. The suspension system is installed between a wheel and a vehicle body of the vehicle.

Abstract: A refrigerator is provided. The refrigerator includes a refrigerator body, a door body and an ice making compartment. The refrigerator body includes a storage compartment. The door body is configured to open or dose the storage compartment. The ice making compartment is disposed in the storage compartment, and includes an ice making compartment shell, an ice maker, and an ice storage box. The ice maker is configured to make ice cubes. The ice storage box is located below the ice maker, and is configured to store the ice cubes made by the ice maker. The ice storage box includes a box body and a first ice baffle. At least a part of the first ice baffle is located in the box body, and the first ice baffle is configured to prevent the ice cubes from accumulating at a position of the box body close to the door body.

Abstract: An application error detection platform computer processor may monitor execution of an application for a customer and determine that an application error has occurred. Responsive to the determination that an application error has occurred, an error fingerprint creation platform computer processor may access a stack trace representing execution of the application when the application error occurred. An error fingerprint associated with the occurrence of the application error may then be determined by applying a hash function (e.g., SHA-1) to information contained in the stack trace. Electronic records including an indication of the error fingerprint may then be received by and stored in an application error log data store. The application error log data store may then be searched for duplicate error fingerprints to facilitate application error resolution.

Abstract: Systems and methods are provided for receiving a notification of an issue with a cloud services application, determining that troubleshooting of the issue comprises review of server logs containing personal data, enabling a data protection and privacy log level instead of a default log level to capture the personal data, generating the one or more server logs containing personal data during replication of the issue based on detecting that the data protection and privacy log level is enabled, indexing the one or more server logs containing personal data and setting access permission to the one or more server logs, detecting that a specified retention time period for the personal data has lapsed, automatically purging the personal data of the one or more server logs based on detecting that the specified retention time period has lapsed, and recording a record that the personal data has been purged.

Abstract: Systems and methods are provided for receiving a notification of an issue with a cloud services application, determining that troubleshooting of the issue comprises review of server logs containing personal data, enabling a data protection and privacy log level instead of a default log level to capture the personal data, generating the one or more server logs containing personal data during replication of the issue based on detecting that the data protection and privacy log level is enabled, indexing the one or more server logs containing personal data and setting access permission to the one or more server logs, detecting that a specified retention time period for the personal data has lapsed, automatically purging the personal data of the one or more server logs based on detecting that the specified retention time period has lapsed, and recording a record that the personal data has been purged.

Abstract: According to some embodiments, an application error detection platform computer processor may monitor execution of an application for a customer and determine that an application error has occurred. Responsive to the determination that an application error has occurred, an error fingerprint creation platform computer processor may access a stack trace representing execution of the application when the application error occurred. An error fingerprint associated with the occurrence of the application error may then be determined by applying a hash function (e.g., SHA-1) to information contained in the stack trace. Electronic records including an indication of the error fingerprint may then be received by and stored in an application error log data store. The application error log data store may then be searched for duplicate error fingerprints to facilitate application error resolution.