Abstract: This technology is directed to facilitating scalable and secure data collection. In particular, scalability of data collection is enabled in a secure manner by, among other things, abstracting a connector(s) to a pod(s) and/or container(s) that executes separate from other data-collecting functionality. For example, an execution manager can initiate deployment of a collect coordinator on a first pod associated with a first job and deployment of a first connector on a second pod associated with a second job separate from the first job of a container-managed platform. The collect coordinator can provide a data collection task to the first connector deployed on the second pod of the second job. The first connector can then obtain the set of data from the data source and provide the set of data to the collect coordinator for providing the set of data to a remote source.

Abstract: A fan includes a rotor; a stator; a first bearing assembly disposed at a radial outer side of an end of the rotor; and an impeller including an impeller body, where the impeller body is provided with a receiving cavity for receiving the first bearing assembly; and one end of the first bearing assembly is disposed in the receiving cavity, and the rotor, the first bearing assembly and the impeller body are disposed coaxially.

Abstract: Systems and methods are disclosed for processing data associated with isolated execution environments. A chunk of data associated with an isolated execution environment can include log data and non-log data. At least a portion of the log data can include log data generated by the isolated execution environment. The system can parse the chunk of data to identify the log data and the non-log data and extract at least a portion of the log data from the chunk of data. The extracted data can be further processed to generate one or more events.

Abstract: Systems and methods are described for a streaming data processing system that defers processing of some data based on a determined importance of the data. A streaming data processing system can ingest a data stream that contains multiple events, and can extract data field values from individual events and process the data field values to determine event importance. The streaming data processing system can then do further processing and indexing of high importance events, and can generate a storage prefix for each low importance event that determines where to store the low importance event in a data storage system. The streaming data processing system can then process queries by retrieving the indexed high importance events, and can extract the data field values from a high importance event to determine the storage prefix for retrieving corresponding low importance events from the data storage system.

Abstract: Systems and methods are disclosed for processing data associated with isolated execution environments. A chunk of data associated with an isolated execution environment can include log data and non-log data. At least a portion of the log data can include log data generated by the isolated execution environment. The system can parse the chunk of data to identify the log data and the non-log data and extract at least a portion of the log data from the chunk of data. The extracted data can be further processed to generate one or more events.

Abstract: This technology is directed to facilitating scalable and secure data collection. In particular, scalability of data collection is enabled in a secure manner by, among other things, abstracting a connector(s) to a pod(s) and/or container(s) that executes separate from other data-collecting functionality. For example, an execution manager can initiate deployment of a collect coordinator on a first pod associated with a first job and deployment of a first connector on a second pod associated with a second job separate from the first job of a container-managed platform. The collect coordinator can provide a data collection task to the first connector deployed on the second pod of the second job. The first connector can then obtain the set of data from the data source and provide the set of data to the collect coordinator for providing the set of data to a remote source.

Abstract: Systems and methods are disclosed for processing data associated with isolated execution environments. A chunk of data associated with an isolated execution environment can include log data and non-log data. At least a portion of the log data can include log data generated by the isolated execution environment. The system can parse the chunk of data to identify the log data and the non-log data and extract at least a portion of the log data from the chunk of data. The extracted data can be further processed to generate one or more events.

Abstract: Systems and methods are disclosed for processing location information associated with isolated execution environments and generating metadata for events based on the location information. A system can parse location information of a log file that includes chunks of data associated with an isolated execution environment to identify characteristics of the isolated execution environment. The system can generate events based on the chunks of data and associated the events with metadata generated based on the characteristics of the isolated execution environment.

Abstract: Systems and methods are disclosed for processing data associated with isolated execution environments. A chunk of data associated with an isolated execution environment can include log data and non-log data. At least a portion of the log data can include log data generated by the isolated execution environment. The system can parse the chunk of data to identify the log data and the non-log data and extract at least a portion of the log data from the chunk of data. The extracted data can be further processed to generate one or more events.