Abstract: A system and related method reduce public cloud provisioning latencies using one or more processors. The method comprises, prior to receiving a volume provisioning request from a user, creating a pool of pre-provisioned generic volumes. The method further comprises receiving the request from the user to provision a volume from the pool, and then determining that a pre-provisioned generic volume is available for customization based on the request. Responsive to the determination, the method executes the actions comprising customizing the pre-provisioned generic volume based on the request, creating a custom volume, and providing the customized pre-provisioned volume to the user.

Abstract: One or more computer processors receive an address resolution protocol (ARP) request in response to a client connecting to a compute resource. The one or more computer processors identify an internet protocol (IP) address associated with the ARP request and the compute resource. The one or more computer processors determine the compute resource is unavailable or not ready for a connection with the client utilizing the identified IP address. The one or more computer processors, responsive to determining that the compute resource is unavailable, provision and deploy a new compute resource, wherein the new compute resource is available to the client under the identified IP address.

Abstract: A computer implemented method for deprovisioning a virtual machine is provided. A number of processor units initializes a deprovisioning agent within the virtual machine. The number of processor units monitors a set of metrics in the virtual machine using the deprovisioning agent. The number of processor units deprovisions the virtual machine using the deprovisioning agent in response to the set of metrics meeting a set of criteria for deprovisioning the virtual machine.

Abstract: A system and related method reduce public cloud provisioning latencies using one or more processors. The method comprises, prior to receiving a volume provisioning request from a user, creating a pool of pre-provisioned generic volumes. The method further comprises receiving the request from the user to provision a volume from the pool, and then determining that a pre-provisioned generic volume is available for customization based on the request. Responsive to the determination, the method executes the actions comprising customizing the pre-provisioned generic volume based on the request, creating a custom volume, and providing the customized pre-provisioned volume to the user.

Abstract: Aspects of the present invention disclose a method, computer program product, and system for query execution in a multi-tenant cloud service. The method includes one or more processors determining category classes for service queries. The method further includes sending for execution, a selected number of service queries from one of the determined category classes to a shadow query engine. Respective service queries of the categorically classified service queries comprise a different set of configuration parameter values for the shadow query engine. The method further includes recording metadata for the selected number of service queries of the one category class executed on said shadow query engine. The method further includes determining correlations between the recorded metadata.

Abstract: One or more computer processors receive a domain name system (DNS) request in response to a client connecting to a compute resource. The one or more computer processors decoding the DNS request into one or more provision parameters. The one or more computer processors determining that the compute resource is unavailable for a connection with the client utilizing the identified IP address. The one or more computer processors, responsive to determining that the compute resource is not available or not ready, provisioning and deploying a new compute resource according to the one or more decoded provision parameters, wherein the new compute resource is available to the client under the identified IP address.

Abstract: An autonomic function executing in an artificial intelligence environment determines that a fused model responsive to a new problem space has below a threshold level of accuracy in the new problem space. A spliced layer in the fused model is autonomically cloned, the spliced layer having been extracted from a second model and inserted at a location in the fused model. The cloned layer is autonomically inserted at a second location in the fused model. An automatically constructed vector transformation transforms an output vector of a previous layer in an immediately previous location in the model relative to the second location. The cloned layer is automatically fused in the fused model using the transformed output vector as input to the cloned layer, forming a deep fused model that has a revised accuracy that is higher than the accuracy relative to an ontology of the new problem space.

Abstract: Systems and techniques that facilitate backend quantum runtimes are provided. In various embodiments, a system can comprise a memory that can store computer-executable components. The system can further comprise a processor that can be operably coupled to the memory and that can execute the computer-executable components stored in the memory. In various embodiments, the computer-executable components can comprise an execution orchestration engine component that can parse a computer program into classical and quantum portions and that can host the computer program by instantiating a classical computing resource.

Abstract: An autonomic function is caused to execute in an artificial intelligence environment to detect a new problem space. Using the autonomic function, a first model is selected. The first model includes a first trained neural network corresponding to a first ontology. A second model is automatically identified. the second model includes a second trained neural network corresponding to a second ontology. A layer is autonomically extracted from the second model and inserted into a location in the first model. A vector transformation is automatically constructed to transform an output vector of a previous layer in an immediately previous location in the model relative to the location. The layer is automatically fused in the first model using the transformed output vector as input to the layer, the fusing forming a fused model that is operable on an ontology of the new problem space.

Abstract: Aspects of the present invention disclose a method, computer program product, and system for query execution in a multi-tenant cloud service. The method includes one or more processors determining category classes for service queries. The method further includes sending for execution, a selected number of service queries from one of the determined category classes to a shadow query engine. Respective service queries of the categorically classified service queries comprise a different set of configuration parameter values for the shadow query engine. The method further includes recording metadata for the selected number of service queries of the one category class executed on said shadow query engine. The method further includes determining correlations between the recorded metadata.

Abstract: An autonomic function executing in an artificial intelligence environment determines that a fused model responsive to a new problem space has below a threshold level of accuracy in the new problem space. A spliced layer in the fused model is autonomically cloned, the spliced layer having been extracted from a second model and inserted at a location in the fused model. The cloned layer is autonomically inserted at a second location in the fused model. An automatically constructed vector transformation transforms an output vector of a previous layer in an immediately previous location in the model relative to the second location. The cloned layer is automatically fused in the fused model using the transformed output vector as input to the cloned layer, forming a deep fused model that has a revised accuracy that is higher than the accuracy relative to an ontology of the new problem space.

Abstract: An autonomic function is caused to execute in an artificial intelligence environment to detect a new problem space. Using the autonomic function, a first model is selected. The first model includes a first trained neural network corresponding to a first ontology. A second model is automatically identified. the second model includes a second trained neural network corresponding to a second ontology. A layer is autonomically extracted from the second model and inserted into a location in the first model. A vector transformation is automatically constructed to transform an output vector of a previous layer in an immediately previous location in the model relative to the location. The layer is automatically fused in the first model using the transformed output vector as input to the layer, the fusing forming a fused model that is operable on an ontology of the new problem space.

Abstract: Deploying a software service. A defined software service offering is selected from a plurality of defined software service offerings. An instantiation order for deploying the selected defined software service offering on a corresponding computer system is generated. Each defined software service offering comprises a software service definition and at least one defined software policy. One selected from the group consisting of the software service definition, the software policy, and a combination thereof, provides a hardware configuration for the software service, a software configuration for the software service, and a managing policy for the software service. The instantiation order of the software service for execution on the computer system is created based on the hardware configuration, the software configuration and the managing policy.

Abstract: Event-driven processing is facilitated by a unikernel-based method which includes receiving, based on an event, a code execution request containing parameter values for an application code unikernel. The application code unikernel includes uploaded application code in a single-purpose virtual machine image. Based on receiving the code execution request, the application code unikernel is run, which includes providing the parameter values as bootvariables as part of booting the program code unikernel. Further, running the application code unikernel may include executing the application code unikernel directly on a hypervisor. The application code unikernel may include only operating system components required to run the uploaded application code.

Abstract: Event-driven processing is facilitated by a unikernel-based method which includes receiving, based on an event, a code execution request containing parameter values for an application code unikernel. The application code unikernel includes uploaded application code in a single-purpose virtual machine image. Based on receiving the code execution request, the application code unikernel is run, which includes providing the parameter values as bootvariables as part of booting the program code unikernel. Further, running the application code unikernel may include executing the application code unikernel directly on a hypervisor. The application code unikernel may include only operating system components required to run the uploaded application code.

Abstract: A mechanism is provided for evaluating a service based on a request for the service. At least one attribute, having at least one preference parameter, is assigned to at least one generic configuration, the at least one generic configuration comprising at least one resource. A request is received for the service having an assigned quality-of-service-value, and a respective preference parameter value is assigned to each of the at least one preference parameters based on the quality-of-service-value. Furthermore, a combination of the resources is selected based on the request, the combination of the resources forming a selected configuration. Additionally, the selected, configuration is mapped to one of the at least one of the generic configurations and the at least one preference parameter of the at least one attributes of the mapped at least one of the generic configurations is mapped to the selected, configuration.

Abstract: A mechanism is provided for evaluating a service based on a request for the service. At least one attribute, having at least one preference parameter, is assigned to at least one generic configuration, the at least one generic configuration comprising at least one resource. A request is received for the service having an assigned quality-of-service-value, and a respective preference parameter value is assigned to each of the at least one preference parameters based on the quality-of-service-value. Furthermore, a combination of the resources is selected based on the request, the combination of the resources forming a selected configuration. Additionally, the selected configuration is mapped to one of the at least one of the generic configurations and the at least one preference parameter of the at least one attributes of the mapped at least one of the generic configurations is mapped to the selected configuration.

Abstract: A computer-implemented method of enabling security in network resources provisioned as part of a service landscape instance is provided. The method includes initiating an orchestration process for creating a landscape service instance to provide services to a service subscriber over a data communications network. The method further includes deriving from the orchestration process at least one parameter, and generating at least one security configuration profile based upon the at least one parameter for at least one system of the landscape service instance.

Abstract: A computer-implemented method is provided for updating network security policy rules when network resources are provisioned in a service landscape instance. The method includes categorizing network resources in a service landscape instance based on a service landscape model. The method further includes responding to the provisioning of a network resource by automatically generating one or more security policy rules for a newly-provisioned network resource. Additionally, the method includes updating security policy rules of pre-existing network resources in the service landscape instance that are determined to be eligible to communicate with the newly-provisioned network resource so as to include the newly-provisioned network resource as a remote resource based on the service landscape model.

Abstract: Method, computer program products and systems for conserving energy in data processing center, wherein a plurality of services are offered to a plurality of subscribed service consumers in a dynamic fashion, allowing a created service instance to be re-assigned from one to another server of the resources. Control parameters comprising power consumption and temperature of a group of resources are monitored. A workload may be assigned properties such as “hot” and “cold.” which are then assessed. A hot workload may be relocated to a cold spot, and if necessary, a cold workload may be relocated to a location which was de-loaded from a workload, that is, a hot spot, which is then considered to cool down due to addition of less workload in form of the cold workload. Thus, the energy required to cool the data center may be minimized.