Abstract: Distributed data analysis systems and methods are provided. A data broker distributes received data to consumers, such as information and repository consumers, which can be subscribed to the data. A subsystem with a processor for data processing can provide data to the data broker. A first information consumer may include a receiving module for receiving the data from the data broker, an analysis module for analyzing the received data to obtain a result, and a publication module for sending the result to the data broker when a second information consumer is subscribed to the result.

Abstract: Data values of metrics for a plurality of functional entities are aggregated, the aggregating producing aggregated values for the respective metrics. A set of the aggregated values is produced for the respective metrics. Based on the set of aggregated values, an interactive visualization of the metrics is generated, the interactive visualization including visual indicators based on the aggregated values for the respective metrics across a plurality of time intervals. The interactive visualization is selectable to focus on a portion of the interactive visualization.

Abstract: The present disclosure provides a computer system with an event handling architecture. The computer system includes a processing node (104) comprising an event generator (200) configured to detect a system error corresponding to the processing node (104) and generate a tokenized event message. The tokenized event message is structured according to conformance rules. The system also includes a data broker (202) configured to receive the tokenized event message and send the tokenized event message to a structured query language (SQL) event consumer (204). The SQL event consumer (204) is configured to generate a database record based on the tokenized event message and the conformance rules. The system also includes an event repository (106) with a relational database configured to receive the database record from the SQL event consumer (204).

Abstract: There is provided a computer-implemented method of aggregating data. An exemplary method comprises receiving an aggregation scheme and generating numerous first aggregations by aggregating data at a first level of granularity. The data may be associated with a time and stored in a first table. Further, generating the numerous first aggregations may be based on the time and the aggregation scheme. The exemplary method further comprises generating a second aggregation by aggregating the first aggregations at a second level of granularity based on the aggregation scheme. The second level of granularity may comprise the first level of granularity.

Abstract: Distributed data analysis systems and methods are provided. A data broker distributes received data to consumers, such as information and repository consumers, which can be subscribed to the data. A subsystem with a processor for data processing can provide data to the data broker. A first information consumer may include a receiving module for receiving the data from the data broker, an analysis module for analyzing the received data to obtain a result, and a publication module for sending the result to the data broker when a second information consumer is subscribed to the result.

Abstract: A fault tolerant cluster of computer systems includes a “process quad” comprising four duplicate processes—a primary process and a backup process on a primary system, and a primary process and a backup process on a backup system. The state of the backup process on the primary system is maintained by receiving checkpoint information from the primary process on the primary system, and the states of the primary and backup processes on the backup system are maintained by receiving checkpoint information either directly or indirectly from the primary process on the primary system.

Abstract: A redundant system includes a primary process and a backup process. The system is configured to conduct online software replacement by sending an instruction to the backup process to terminate, and then starting a replacement backup process using an updated code version. Tokenized checkpoints are provided to the replacement backup process from the primary process, the tokenized checkpoints including a basic data structure and a token data structure. The token data structure includes one or more tokens that may be considered or may be ignored by the replacement backup process. After the state of the replacement backup process has been established, the replacement backup process is designated to be the new primary process. At that time, a new backup process is started using the updated code.