A computer system installed on board a carrier, communicating in a network with a data concentrator and with a monitor, and implementing at least one service that is critical for the operating safety of the carrier, the critical service being redundant in at least two instances (δ.sub.1, . . . δ.sub.m) on different respective computers (C.sub.1, . . . , C.sub.m) connected to the network, each computer (C.sub.k) implementing at least one software task implementing an instance (δ.sub.k) of the critical service being configured to implement the critical service by way of time control.

Methods, systems, apparatuses, and computer-readable storage mediums are described for machine learning-based techniques for reducing the visual complexity of a dependency graph that is representative of an application or service. For example, the dependency graph is generated that comprises a plurality of nodes and edges. Each node represents a compute resource (e.g., a microservice) of the application or service. Each edge represents a dependency between nodes coupled thereto. A machine learning-based classification model analyzes each of the nodes to determine a likelihood that each of the nodes is a problematic compute resource. For instance, the classification model may output a score indicative of the likelihood that a particular compute resource is problematic. The nodes and/or edges having a score that exceed a predetermined threshold are provided focus via the dependency graph.

An asynchronous first device in communication with an asynchronous second device. The time for the first device to complete a processing cycle is a first device major frame and the first device major frame comprises a first device dedicated processing time slot at the end of the first device major frame. The first device is configured to send a rescheduling signal to the second device when it has completed a first device major frame. The first device is configured, during every first device dedicated processing slot, to: monitor for a rescheduling signal sent from the second device to the first device; and if a rescheduling signal from the second device is received: reschedule the current first device major frame to a rescheduled first device major frame; wherein the end of the rescheduled first device major frame coincides with the time the rescheduling signal from the second device was received.

The confidentiality of data is maintained in a case where analysis of an operation state of a facility is entrusted to the outside. Time difference information in operation between the manufacturing apparatuses (RB1), (RB2), . . . , arranged on the production line (LN) is stored for each of the apparatuses, in an inter-apparatus time difference information storage unit (33). At the occurrence of a failure in one of the manufacturing apparatuses (RB1), (RB2), . . . , the operation estimation unit (13) selects, from among the peripheral apparatuses on the upstream side and the downstream side with respect to the manufacturing apparatus concerned, one on the upstream side and one on the downstream side, estimates an operation period of each selected peripheral apparatus associated with the failure, reads log data corresponding to the estimated operation period from the operation history storage unit (31), and transmits the read piece to the external support center (SC).

Methods, systems, and devices for providing computer implemented services using managed systems are disclosed. To provide the computer implemented services, the managed systems may need to operate in a predetermined manner conducive to, for example, execution of applications that provide the computer implemented services. Similarly, the managed system may need access to certain hardware resources (e.g., and also software resources such as drivers, firmware, etc.) to provide the desired computer implemented services. To improve the likelihood of the computer implemented services being provided, the managed devices may be managed using a subscription based model. The subscription model may utilize a highly accessible service to obtain information regarding desired capabilities (e.g., a subscription) of a managed system, and use the acquired information to automatically configure and manage the features and capabilities of the managed systems.

The present invention is directed to a system and a method for ensuring high availability and guarantee delivery of event streams to target consumer applications. The distributed event streaming platform of the present invention is provided with an event streaming layer comprising a plurality of independent and non-replicating event streaming clusters that are configured to process events received from a producer module. A monitoring module is provided to monitor the propagation and delivery of each propagated event based on event notifications received from an event producer module and a plurality of the consumer modules.

Aspects of the disclosure describe methods and systems for cross-referencing forensic snapshots over time. In one exemplary aspect, a method may comprise receiving a first snapshot of a computing device at a first time and a second snapshot of the computing device at a second time and applying a pre-defined filter to the first snapshot and the second snapshot, wherein the pre-defined filter includes a list of files that are to be extracted from each snapshot. The method may comprise subsequent to applying the pre-defined filter, identifying differences in the list of files extracted from the first snapshot and the second snapshot. The method may comprise creating a change map for the computing device that comprises the differences in the list of files over a period of time, wherein the period of time comprises the first time and the second time, and outputting the change map in a user interface.

Systems and methods for adaptive fault prediction analysis are described. In one embodiment, the system includes one or more computing components, and one or more hardware controllers. In some embodiments, the storage system includes a storage drive. At least one of the one or more hardware controllers is configured to analyze one or more tolerance limits of a first computing component among the plurality of computing components; calculate a failure metric of the first computing component based at least in part on the analysis of the one or more tolerance limits of the first computing component; analyze sensor data from the first computing component in real time; and update the failure metric based at least in part on the analyzing of the sensor data.

A system, method, and computer-readable medium are disclosed for browser based polling of jobs used to build a web page of a web application. A web browser builds the web page of the web application and connects with one or more web services for jobs used to build the web page of the web application. A reusable service from a library is downloaded and is used at the web browser to poll the jobs as they are received from the web services. Polling the jobs is performed until download is complete. The web page application is updated when the download is complete.

Techniques for processing a request may include: providing tasks to a state machine framework, wherein the tasks perform processing of a workflow for servicing the request; generating, by the state machine framework, a state machine for processing the request, wherein the state machine includes states associated with the tasks, wherein generating the state machine may include automatically determining a first state transition of the state machine between a first and a second of the states; receiving the request; and responsive to receiving the request, performing first processing using the state machine to service the request. The framework may automatically generate triggers that drive the state machine to determine subsequent states in accordance with defined state transitions. State machine internal state information may be persistently stored and used in restoring the state machine to one of its states in connection processing of the command.