Abstract: A method, computer program product and computer system for predicting excessive resource usage in a distributed computing environment is provided. A processor retrieves a portion of code associated with a workload in a distributed computing environment. A processor retrieves account information associated with the workload. A processor determines a likelihood that the workload is indicative of excessive resource usage based on the portion of code and the account information associated with the workload. In response to the likelihood of excessive resource usage exceeding a threshold, a processor reschedules the workload in the distributed computing environment.

Abstract: Enhancing data processing is provided. A plurality of derivative application instances is generated to run a plurality of parallel jobs based on an image of an instance of an application providing a service corresponding to a data processing request. One derivative application instance is generated for each respective job of the plurality of parallel jobs to run the plurality of parallel jobs to meet defined data processing performance objectives. The plurality of parallel jobs is run on the plurality of derivative application instances at the same time in parallel to increase data processing throughput and decrease an amount of time and resources needed to fulfill the data processing request. Each job of the plurality of parallel jobs retrieves a particular chunk of a dataset corresponding to the data processing request from a database to process that particular chunk of the dataset to generate a sub-result of the data processing request.

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: An approach is provided for sidecar sizing. An application running in a cluster of a containerized system is provided. The application includes at least one sidecar container having configuration data including a first size of the at least one sidecar container. Requests for the application over time and usage data for the application over time, including memory and/or CPU consumption, are monitored. The first size of the at least one sidecar container is evaluated, and a second size of the least one sidecar container is determined, based on the monitored requests for the application and usage data for the application. Updated configuration data for the at least one sidecar container, including the second size of the at least one sidecar container, is provided.

Abstract: A computer-implemented method for executing a serverless workload on a transient infrastructure is disclosed. The method comprises receiving a request for executing a workload and at least one policy, selecting an infrastructure component of the transient infrastructure for an execution of the workload, wherein the transient infrastructure is implemented utilizing a plurality of geographically distributed computing nodes, and executing the workload on the transient infrastructure. Furthermore, the method comprises upon receiving an interfering event during the execution of the workload causing a stop of the workload execution, freezing the execution of the workload, storing intermediate results and statuses of the workload execution in a cross-domain storage system, terminating the execution of the workload, and continuing the workload execution using the intermediate results and under a constraint defined by the at least one policy.

Abstract: A method, system, and computer program product for implementing automated serverless runtime container allocation is provided. The method includes defining a number of runtime containers and associated characteristics required for each worker node of a plurality of worker nodes for execution of a specified workload. The specified workload is dispatched to the plurality of worker nodes and a specified portion of the specified workload is assigned to each worker node. An application executing a universal runtime container that includes potential application runtimes and associated supported software versions within a layered modifiable format is generated and unused layers are removed from the universal runtime container. The specified workload is executed via the universal runtime container and a set of available universal runtime containers is refilled on an associated work node.

Abstract: A method, system, and computer program product for implementing automated serverless runtime container allocation is provided. The method includes defining a number of runtime containers and associated characteristics required for each worker node of a plurality of worker nodes for execution of a specified workload. The specified workload is dispatched to the plurality of worker nodes and a specified portion of the specified workload is assigned to each worker node. An application executing a universal runtime container that includes potential application runtimes and associated supported software versions within a layered modifiable format is generated and unused layers are removed from the universal runtime container. The specified workload is executed via the universal runtime container and a set of available universal runtime containers is refilled on an associated work node.

Abstract: A method, computer program product and computer system for predicting excessive resource usage in a distributed computing environment is provided. A processor retrieves a portion of code associated with a workload in a distributed computing environment. A processor retrieves account information associated with the workload. A processor determines a likelihood that the workload is indicative of excessive resource usage based on the portion of code and the account information associated with the workload. In response to the likelihood of excessive resource usage exceeding a threshold, a processor reschedules the workload in the distributed computing environment.

Abstract: A message flow environment permits a developer to define a debug session in which nodes in a defined message flow have a debug function. A debug controller is used to select nodes as breakpoints using data in shared memory accessible to the nodes in the defined message flow. Each node having a debug function will determine whether it is a breakpoint by accessing the shared memory. Where a node determines that it is a breakpoint, the node will communicate debug information to the debug controller. An independent daemon runs to permit a developer to define breakpoints from the set of debug nodes. The nodes having a debug function maintain a stack in the shared memory which is sent to the debug controller by each breakpoint node when reached by a message.

Abstract: A message flow environment permits a developer to define a debug session in which nodes in a defined message flow have a debug function. A debug controller is used to select nodes as breakpoints using data in shared memory accessible to the nodes in the defined message flow. Each node having a debug function will determine whether it is a breakpoint by accessing the shared memory. Where a node determines that it is a breakpoint, the node will communicate debug information to the debug controller. An independent daemon runs to permit a developer to define breakpoints from the set of debug nodes. The nodes having a debug function maintain a stack in the shared memory which is sent to the debug controller by each breakpoint node when reached by a message.