System and computer-implemented method for managing multi-availability zone (AZ) clusters of host computers in a cloud computing environment automatically detects a degraded state of a first AZ in the cloud computing environment based on host failure events for host computers in a first cluster section of a multi-AZ cluster of host computers located in the first AZ and a recovered state of the first AZ based a successful scale-in operation of another multi-AZ cluster located partially in the first AZ. In response to the detection of the degraded state of the first AZ, a second cluster section of the multi-AZ cluster of host computers located in a second AZ is scaled out. In response to the detection of the recovered state of the first AZ, the second cluster section of the multi-AZ cluster of host computers located in the second AZ is scaled in.

To address loss of access to computing instances in a cloud computing environment, techniques are introduced for moving an application between computing instances in the cloud computing environment. A computing service captures baseline or delta snapshots of the state of the application running on a first computing instance. A baseline snapshot is indicative of the full state of the application, and a delta snapshot is indicative of changes in the state since a most recent snapshot was captured. Responsive to receiving an indication that the first computing instance is to stop servicing the application, the computing service stops the application from running on the first computing instance and moves data from the captured snapshots to a second computing instance. The computing service resume execution of the application on the second computing instances and captures snapshots of the state of the application at the second computing instance.

The present disclosure relates to a method and system for controlling output characteristics of a media streaming over a media output device. The system [100] comprises a processing unit [102] and a testing unit [104] coupled with the processing unit [102]. The processing unit [102] identifies one or more unused hardware servers from the datacenter hardware, and then selects a first set of unused hardware servers for testing, from the identified one or more unused hardware servers. Further, the testing unit [104] performs one or more tests on the selected first set of unused hardware servers, wherein each unused hardware server from the selected first set of unused hardware servers is in operational state. The system [100] further repeats the steps to perform testing on a second set of unused hardware servers, a third set of unused hardware servers, and so on.

An aircraft includes a plurality of control targets, avionics devices and a control switch unit. The control targets each includes a power line communication unit configured to perform communication via a power line. The avionics devices are respectively connected with the control targets via exclusive-use signal lines. The avionics devices are configured to control the control targets via the signal lines. The avionics devices each includes a PLC unit configured to perform communication via the power line. The control switch unit is configured to, when an abnormality occurs in any of the avionics devices, cause another one of the avionics devices to control the control target which has been controlled by the any of the avionics devices, via the power line.

A storage system determines source addresses, and destination addresses in a storage system, for network traffic. The storage system determines a hash algorithm, from a plurality of hash algorithms. The hash algorithm is to be used across the source addresses for load-balancing the network traffic to the destination addresses. The storage system determines that the hash algorithm more closely meets one or more load-balancing criteria than at least one other hash algorithm, of the plurality of hash algorithms. The storage system distributes the network traffic from the source addresses to the destination addresses in the storage system, with load-balancing according to the determined hash algorithm.

Systems and methods for managing a highly available distributed database comprising: a memory storing instructions; and one or more processors configured to execute the instructions to: determine that a source node, in a distributed database comprising the source node and one or more replica nodes, is not available; select a most-updated replica node from the one or more replica nodes; switch a role of the most-updated replica node to source; update a data store to label the source node as unavailable and the selected replica node as being a promoted source node; send a notification to a user device to update a database topology based on the updated data store; determine whether the user device has updated the database topology; and upon determining the user device has not updated the database topology, continue to send the notification to the user device until the user device has updated the database topology.

A workgroup-computing-entity-based fail-safe/evolvable hardware core structure is disclosed which includes a 3-hierarchical-level 6-workgroup-Basic-Building-Block (6-wBBB) created to supplant the node-computing-entity-based non-fail-safe/limited evolvable von-Neumann core structure of 3-hierarchical-level 3-node-BBB, (i.e., base-level JO-devices/mid-level main memory/top-level CPU) and all the first-time fail-safe workgroup systems can be subsequently generated in the second period along the workgroup-computing evolutionary timeline. Furthermore, based on the first 6-wBBB evolvable architecture, the workgroup evolutionary processes can go up to 7 generations in creating all the necessary workgroup-computing entity-based hardware core structures, so that all the real-time intelligent workgroup-computing systems can be generated in the third period along the workgroup-computing evolutionary timeline.

For efficient high availability for a multi-node cluster using a processor device in a computing environment, using duplicate, standby host-bus adaptors (HBAs) for alternate nodes with respect to a node with the duplicate, standby HBAs using duplicate credentials of active HBAs of the node for shutting down the node, taking an active HBA of the node offline, and/or activating one of the alternate nodes.

A spare robot controller for replacing any one of a plurality of initial robot controllers configured to control operation of respective industrial robots includes a key storage storing a plurality of shared keys and a secure storage. The spare robot controller is configured to decrypt, using one of the shared keys, an encrypted backup copy of the initial robot controller to be replaced, and to store resulting data in the secure storage. In embodiments, the is configured to extract data from the secure storage during operation and to encrypt the extracted data, using a selected one of the shared keys, for storage as a backup copy in a backup storage available to all of the initial robot controllers.

A system includes a computer system, a memory, and processor. The computer system includes a plurality of units of system resources, each executing a workload unit. The memory stores a set of remediation scripts. Each remediation script is associated with a known failure of a set of known failures within the computer system. Each remediation script is configured, when executed, to remediate the known failure. The processor measures performance metrics associated with the computer system. The processor determines, based on the performance metrics, that a probability that a failure within the computer system will occur within a future time is greater than a set threshold. In response, the processor determines, based on the values for the set of metrics, that the failure is a known failure, and executes a remediation script associated with the known failure.