Abstract: A technique of training a model for determining a test case for software testing is presented, wherein the software testing is based on a set of test cases built for a set of software modules comprised by a software to be tested. The technique uses artificial intelligence and comprises obtaining log information resulting from execution of each of the test cases, wherein the log information is obtained per software module and per executed test case, and performing supervised machine learning based on the log information obtained per software module and per executed test case as input to train a model for predicting the executed test case.

Abstract: There is provided a method performed by an encryption node for provisioning storage in a system. The encryption node is associated with an application node and the application node is configured to run at least part of one or more applications. In response to an unencrypted storage volume becoming available to the encryption node from a storage provisioning node of the system, an encrypted storage volume is generated (20) from the unencrypted storage volume and provisioning of the encrypted storage volume is initiated (22) to make the encrypted storage volume available at a compute node of the system for use by the application node.

Abstract: There is provided a method performed by a first storage provisioning node of a system for provisioning storage in the system. In response to a first request for an encrypted storage volume for an application node, transmission of a second request is initiated (20) towards a second storage provisioning node for an unencrypted storage volume. In response to the requested unencrypted storage volume becoming available to the first storage provisioning node, an encrypted storage volume is generated (22) from the unencrypted storage volume and provisioning of the encrypted storage volume is initiated (24) to make the encrypted storage volume available at a compute node of the system for use by the application node.

Abstract: There is provided a method of training a model for use with a software installation process. A software installation process is run a plurality of times (102). Each time the software installation process is run, one parameter in a set of parameters with which the software installation process is rum is changed to generate a respective software installation process output (104). Each software installation process output is used with its respective set of parameters to train a model (106). The model is trained to identify one or more parameters that are a cause of a failed software installation process based on the output of the failed software installation process.

Abstract: A technique for buffering packets in a Software Defined Networking (SDN) infrastructure is disclosed. A method implementation of the technique is performed by an SDN network device and comprises receiving (S304) a configuration message from an SDN controller, the configuration message defining at least one characteristic characterizing packets to be buffered, receiving (S306) a packet, triggering (S308) inserting the packet into a buffer if the packet matches the at least one characteristic, and triggering (S310) sending a notification message to the SDN controller notifying the SDN controller that the packet is inserted into the buffer.

Abstract: The invention relates to a method for operating a control entity (100) configured to influence a selection of one service instance (31) from a plurality of service instances provided by a distributed cloud system (30), each service instance providing a predefined service to a data packet flow of a user entity (60) connected to a mobile communications network.

Abstract: A technique for buffering packets in a Software Defined Networking (SDN) infrastructure is disclosed. A method implementation of the technique is performed by an SDN network device and comprises receiving (S304) a configuration message from an SDN controller, the configuration message defining at least one characteristic characterizing packets to be buffered, receiving (S306) a packet, triggering (S308) inserting the packet into a buffer if the packet matches the at least one characteristic, and triggering (S310) sending a notification message to the SDN controller notifying the SDN controller that the packet is inserted into the buffer.