One embodiment comprises a stateless container of binaries and a broker. The stateless container of binaries includes a code memory having stored thereon code for a first version of a first functional component of a content management system, the first functional component executable to provide a first version of a service. The broker may be executable to: receive a request for the service from a client application, the request associated with a user of the content management system; determine that the first version of the service is accessible with regard to the user; determine an available first server that hosts the first version of the service; provide an indication of the first version of the service to the client application; and provide an IP address and a port number associated with the available first server to the client application.

The present disclosure provides a method for information storage and a system thereof, which adapts to a data storage system. A monitoring unit is configured to detecting and monitoring operations of a storage node in the data storage system to generate corresponding one and more monitoring data. A recording processor is configured to receiving the one or the plurality of monitoring data, and rendering one or a plurality of logs according to the difference of content of the one or the plurality of monitoring data. The adjustment mechanism is performed according to the stored logs, thereby the amount of large data generated during monitoring is effectively reduced.

A non-transitory computer-readable storage medium storing a program that causes a computer to execute a process, the process includes acquiring information in a log regarding an operating state of a plurality of robots; based on the acquired information in the log, calculating a first load in each time slot related to control of the plurality of robots; when there is a first time slot in which the first load is higher than or equal to a first threshold, extracting a robot that performs a first task, from the plurality of robots, in the first time slot; and changing a time slot for operating the extracted robot.

A technique for tracking web browsing activity of a client device that includes storing, in a memory, a client profile having a client identifier associated therewith, providing a client device with a cache file having the client identifier embedded therein, receiving from the client device an identification of a client action and the client identifier, and updating the client profile to include the identification of the client action.

A computer-implemented method includes scanning a clip of messages that includes message requests and message responses arranged in a sequence. The scanning is performed based on one or more search parameters and produces a list of one or more name/value pairs. The clip is utilized to perform a load test on a target website. Each name/value pair has a corresponding value. For each name/value pair in the list a message request in the clip is identified where the corresponding value is first used. Then, looking backwards in the sequence from the message request where the corresponding value is first used, prior message responses are located where the corresponding value is found. An extraction point is specified in the clip for the corresponding value as a latest message response in the sequence where the corresponding value was returned from the target website. The corresponding value is then stored as a property.

An automotive electronics system includes an electronic control unit and a trace adapter. The electronic control unit is configured to receive measurement signals and provide control signals. Additionally, the electronic control unit is configured to generate or provide trace signals by replacing original instructions in a binary image with trace instructions. The trace instructions are functionally equivalent, but trigger providing the trace signals. The trace adapter is coupled to the electronic control unit. The trace adapter is configured to obtain the trace signals from the electronic control unit.

A method of detecting abnormality may include the following steps. A normal-value range of a parameter for a target object is determined based on historical values of the parameter in a preset time period or at a preset time point. Whether the target object is abnormal is determined based on the normal-value range and the value of the parameter for the target object in the preset time period or at the preset time point within a current time cycle. Further, another normal-value range may be determined based on historical deviation values for the target object in historical time periods or at historical time points before the preset time period or the preset time point. Whether the target object is abnormal is determined based on either of the two normal-value ranges.

A disclosed load estimation method includes: collecting run information of a processor being executing a predetermined program; specifying execution status of the processor based on the collected run information; and estimating a load of the predetermined program based on a result of comparison between the execution status of the processor and execution characteristics of the processor. Each of the execution characteristics is stored in association with a load level of the predetermined program.

Techniques and solutions are described for improving user interfaces, such as by analyzing user interactions with a user interface with a machine learning component. The machine learning component can be trained with user interaction data that includes an interaction identifier and a timestamp. The identifiers and timestamps can be used to determine the duration of an interaction with a user interface element, as well as patterns of interactions. Training data can be used to establish baseline or threshold values or ranges for particular user interface elements or types of user interface elements. Test data can be obtained that includes identifiers and timestamps. The time taken to complete an interaction with a user interface element, and optionally an interaction pattern, can be analyzed. If the machine learning component determines that an interaction time or pattern is abnormal, various actions can be taken, such as providing a report or user interface guidance.

A method, a system, and a computer program product for analyzing error messages. A first error log generated as a result of an execution of at least one task of a computing system at a first instance is received. The first error log include a plurality of first error messages. A first association rules model is generated using the first error messages. The first association rules model includes a plurality of association rules defining one or more relationships. A second error log, including a plurality of second error messages, generated as a result of an execution of the task at a second instance is received and a second association rules model is generated using the second error messages. Based on the first and second association rules models, at least one error message pattern associated with execution of the at least one task is determined.