The disclosed embodiments disclose techniques for journaling data received in a cloud-based distributed computing environment (CBDCE). Multiple services simultaneously execute on the CBDCE compute nodes, with each service comprising multiple service instances that simultaneously execute on multiple, distinct compute nodes of the CBDCE. The CBDCE includes a distributed database that enables coordination between the service instances of services that execute in the CBDCE; this distributed database also includes multiple distributed database instances that simultaneously executing on multiple different CBDCE compute nodes. During operation, a service instance executing on one of these compute nodes receives a client request. The service instance submits this client request to a distributed database instance and, in parallel, also submits the client request and its associated user data to a distributed journaling service.

An example networked computing system for iterative node level recovery comprises a node cluster; a database; at least one processor configured by instructions to perform operations comprising at least: identifying a failed node among existing nodes in the node cluster; identifying and initiating a replacement node as a new node for the node cluster; accessing at the database a logical backup of the node cluster; retrieving logical backup data of the node cluster and identifying specific rows of backup data to be restored to the new node; restoring the specific data rows to the new node; identifying new data written by applications, to the existing nodes of the node cluster, during restoration of the new node; iteratively accessing supplementary back up data to identify supplementary data rows to be restored to the new node; and iteratively restoring the supplementary data rows to the new node until the new node is synchronized with the existing nodes in the node cluster.

The present disclosure relates to a method of operating a database system. The database system comprises: a database; a first compute node comprising a first database proxy; and a second compute node comprising a second database proxy. The method comprises receiving and processing, at the first database proxy, a first plurality of access requests to access the database; receiving and processing, at the second database proxy, a second plurality of database access requests to access the database; monitoring for a failure event associated with the first database proxy; and, in response to the monitoring indicating a failure event, initiating a failover procedure between the first database proxy and the second database proxy. The failover procedure comprises: redirecting the first plurality of access requests to the second database proxy; and processing, at the second database proxy, the first plurality of access requests.

An analysis function imparting device (10) includes a virtual machine analyzing unit (121) that analyzes a virtual machine of a script engine, a command set architecture analyzing unit (122) that analyzes a command set architecture that is a command system of the virtual machine, and an analysis function imparting unit (123) that performs hooking for imparting multipath execution functions to the script engine, on the basis of architecture information acquired by the analysis performed by the virtual machine analyzing unit (121) and the command set architecture analyzing unit (122).

A smart network interface card in an information handling system monitors a local host memory associated with a computer resource for an update to a memory page in the local host memory. After the update to the memory page, the smart network interface card copies the memory page to its memory. The smart network interface card sets a watchdog timer to detect a failure in an the information handling system that hosts the computer resource and if the failure is detected, then the smart network interface card migrates the computer resource from its to another information handling system.

It is presented a method for enabling allocation of resources for a plurality of hosts. The method is performed by a server (1) and comprises identifying (S100) a service running on one or more of the plurality of hosts, determining (S140) a stretch factor for a recurring load pattern for the service running on the one or more of the plurality of hosts, and storing (S150) the identified service together with the determined stretch factor. It is also presented a server, a computer program and a computer program product.

A plurality of computing devices are communicatively coupled to each other via a network, and each of the plurality of computing devices is operably coupled to one or more of a plurality of storage devices. One or more of the computing devices and/or the storage devices may be used to rebuild data that may be lost due to a power failure.

Systems and methods for detecting, e.g., that a Network Function (NF) service consumer in a core network of a cellular communications system has restarted are disclosed. In some embodiments, a method of operation of a NF service consumer in a core network of a cellular communications system comprises sending, to a NF service producer, a message comprising information related to a unit of the NF service consumer.

A data management system includes: a transceiver; a memory; and a processor communicatively coupled to the transceiver and the memory and configured to: receive, via the transceiver, a copy data request for unstructured data; access, via the transceiver in response to the copy data request, a plurality of backed-up files of unstructured data stored in a first data storage device; send, in response to the copy data request, a plurality of Virtual Data Files (VDFs) to a second data storage device, the processor being configured to respond to receipt of information from each of the plurality of VDFs to retrieve a respective backed-up file of unstructured data of the plurality of backed-up files of unstructured data stored in the first data storage device.

Herein are resource-constrained techniques that plan ahead for resiliently moving pluggable databases between container databases after a failure in a high-availability database cluster. In an embodiment that has a database cluster that hierarchically contains many pluggable databases in many container databases in many virtual machines, a computer identifies many alternative placements that respectively assign each pluggable database instance (PDB) to a respective container database management system (CDBMS). For each alternative placement, a respective placement score is calculated based on the PDBs and the CDBMSs. Based on the placement scores of the alternative placements, a particular placement is selected with a best placement score that indicates optimal resilience for accommodating adversity such as failover and overcrowding.