Abstract: Methods and systems for managing data processing systems are disclosed. The data processing systems may be managed by monitoring remediation of incidents. The remediation of the incidents may be monitored by assigning personnel. Notifications of the assigning of personnel and progress of the remediation may be made to at least two other data processing systems. The at least two other data processing systems may update the status of a data processing with the incident as the progress of the remediation continues towards completion of the remediation.

Abstract: A method of computing real-time metrics for automated workflows includes aggregating a set of ingested spans into a set of traces. The method further includes executing a set of rules to determine a set of workflows associated with the set of traces, wherein each workflow of the set of workflows is associated with a respective trace of the set of traces, and wherein each workflow is operable to group together activity associated with a client process within a respective trace. The method also includes assigning a name to each workflow based on the rules and computing real-time metrics for each of the workflows.

Abstract: Methods and system for managing data processing system are disclosed. To manage the operation of the data processing system, hardware components may be replaced from time to time. To improve the likelihood of hardware components being available, procurement plans for proactive management of hardware component inventors for replacement may be used. The procurement plans may be based on various limits regarding when and how many hardware components may be purchased, predicted hardware component failures, and goals for hardware component acquisition that may reduce or manage cost associated with hardware component acquisition.

Abstract: A method of identifying a root cause of a failure for a trace within a microservices-based application includes determining if a root span of the trace is an error span resulting in an error experienced by a user at a front end of the microservices-based application. If the root span of the trace is an error span, the method analyzes a plurality of spans comprising the trace to determine if the trace comprises at least one leaf error span. If the trace comprises a single leaf error span, the method attributes the root cause of the failure in the trace to a service associated with the single leaf error span. If the trace comprises multiple leaf error spans the method attributes the root cause of the failure in the trace to a service associated with a leaf error span of the multiple leaf error spans comprising a latest starting timestamp.

Abstract: Methods and systems for managing data processing system are disclosed. A data processing system may include one or more hardware and/or software components. The operation of the data processing system may depend on the operation of these components. To manage the operation of the data processing system, future failures of the hardware components may be predicted and used as a basis for predicted services to reduce the threat of the predicted component failures. To manage performance of the predicted services, the predicted services may be scheduled for performance. To schedule performance of the predicted services, limitations on availability of service professionals that may complete the predicted services may be taken into account.