One or more techniques and/or computing devices are provided for utilizing snapshots for data integrity validation and/or faster application recovery. For example, a first storage controller, hosting first storage, has a synchronous replication relationship with a second storage controller hosting second storage. A snapshot replication policy rule is defined to specify that a replication label is to be used for snapshot create requests, targeting the first storage, that are to be replicated to the second storage. A snapshot creation policy is created to issue snapshot create requests comprising the replication label. Thus a snapshot of the first storage and a replication snapshot of the second storage are created based upon a snapshot create request comprising the replication label. The snapshot and the replication snapshot may be compared for data integrity validation (e.g., determine whether the snapshots comprise the same data) and/or quickly recovering an application after a disaster.

Disclosed embodiments relate to reporting Electronic Control Unit (ECU) errors or faults to a remote monitoring server. Operations may include receiving operational data from a plurality of ECUs in the vehicle, the operational data being indicative of a plurality of runtime attributes of the plurality of ECUs; generating, through a machine learning process, a statistical model of the operational data; receiving live, runtime updates from the plurality of ECUs in the communications network of the vehicle; identifying an ECU error associated with an ECU in the communications network of the vehicle, the ECU error being determined by a comparison of the live, runtime updates with the statistical model of the operational data to identify at least one deviation from the operational data; and wirelessly sending a report to the remote monitoring server based on the live, runtime updates, the report identifying the ECU and the identified ECU error.

Disclosed embodiments relate to automatically providing updates to at least one vehicle. Operations may include receiving, at a server remote from the at least one vehicle, Electronic Control Unit (ECU) activity data from the at least one vehicle, the ECU activity data corresponding to actual operation of the ECU in the at least one vehicle; determining, at the server and based on the ECU activity data, a software vulnerability affecting the at least one vehicle, the software vulnerability being determined based on a deviation between the received ECU activity data and expected ECU activity data; identifying, at the server, an ECU software update based on the determined software vulnerability; and sending, from the server, a delta file configured to update software on tree ECU with a software update corresponding to the identified ECU software update.

Systems and methods that make use of cluster-level redundancy within a distributed storage management system to address various node-level error scenarios are provided. Rather than making use of a generalized one-size-fits-all approach in an effort to reduce complexity, an approach tailored to the node-level error scenario at issue may be performed to avoid doing more than necessary. According to one embodiment, responsive to identification of a failed RAID stripe by a node of a cluster of a distributed storage management system, for each block ID of multiple block IDs associated with the failed RAID stripe, a data block is restored corresponding to the block ID by reading the data block from another node of the cluster having a redundant copy of the data block; and writing the redundant copy of the data block to a storage area of the node that is unaffected by the failed RAID stripe.

Examples of the present disclosure describe improved systems and methods for disaster recovery for edge devices. In one example implementation, a current device configuration for a first device is received. The current device configuration comprises a device state and a workload configuration of the first device. A bootstrapping package for the first device is generated based on the current device configuration for the first device. Generating the bootstrapping package comprises segmenting the device state and the workload configuration into a namespace. The bootstrapping package is provided to a second device. The bootstrapping package is configured to be automatically installed on the second device.

A technique for enhancing reliability is provided. A semiconductor device includes a main device which operates in a delayed lockstep mode, a sub device which operates in parallel to the main device in a delayed lockstep mode, a delay circuit which delays an output of the main device, a switching circuit which switches the main device to the sub device according to failure information of the main device.

A device, comprising: a main module; a plurality of secondary modules; and a data bus configured to enable data transmission between the main module and the plurality of secondary modules over a data line of the data bus; wherein each of the plurality of secondary modules is configured with a unique secondary address used by the main module to communicate with the respective secondary module over the data line, wherein the main module is operable to configure a first two or more of the plurality of secondary modules with a first common secondary address for simultaneous data transmission from the main module to the first two or more of the plurality of secondary modules over the data line.

A memory cell array unit according to an embodiment of the present disclosure includes a memory cell array and a microcontroller. The memory cell array includes an n-bit allocation bit allocated from a memory controller in read/write control, and a redundant bit of one or a plurality of bits not being provided with a switching mechanism that switches as a substitution for a portion of the allocation bit. The microcontroller reads and writes n-bit data from and into the memory cell array using the allocation bit and the redundant bit on the basis of the read/write control from the memory controller.

High availability and disaster recovery for replicated object stores is disclosed. An embodiment includes receiving, by a first storage system of a plurality of storage systems symmetrically replicating objects of a bucket, a request to establish immutable content for the bucket; indicating, by the first storage system to a second storage system of the plurality of storage systems, the request to establish immutable content, wherein the second storage system establishes an ordering for conflicting requests of different storage systems to establish immutable content for the bucket; and processing, by the first storage system, the request based on ordering information received from the second storage system.

Disclosed embodiments relate to reporting Electronic Control Unit (ECU) errors or faults to a remote monitoring server. Operations may include receiving operational data from a plurality of ECUs in the vehicle, the operational data being indicative of a plurality of runtime attributes of the plurality of ECUs; generating, through a machine learning process, a statistical model of the operational data; receiving live, runtime updates from the plurality of ECUs in the communications network of the vehicle; identifying an ECU error associated with an ECU in the communications network of the vehicle, the ECU error being determined by a comparison of the live, runtime updates with the statistical model of the operational data to identify at least one deviation from the operational data; and wirelessly sending a report to the remote monitoring server based on the live, runtime updates, the report identifying the ECU and the identified ECU error.