Abstract: Embodiments for increasing resource allocations and application instances in diagonal scaling in a distributed computing environment. Resource consumption of each one of a plurality of application instances is tracked and compared to resource allocations of each one of the plurality of application instances. For each one of a plurality of resource increase operations, a resource increase operation to an associated application instance of the plurality of application instances is computed and applied, the resource increase operation being applied when a resource increase can be accommodated on a host running the associated application instance and an increase limit associated with the associated application instance for the resource has not been reached, thereby optimizing application efficiency and resource utilization in the distributed computing environment.

Abstract: Various embodiments for reducing resource allocations and application instances in diagonal scaling in a distributed computing environment. Resource consumption of each one of a plurality of application instances is tracked, and the tracked resource consumption is compared to a resource allocation of each one of the plurality of application instances. A plurality of resource reduction operations for allocation of resources assigned to each one of the plurality of application instances is computed and applied. Idle application instances of the plurality of application instances are identified, and one or more of the identified idle application instances are terminated, thereby optimizing application efficiency and resource utilization in the distributed computing environment.

Abstract: Provided are a computer program product, system, and method for profiling workloads in host systems allocated to a cluster to determine adjustments to allocation of host systems to the cluster. A determination is made of workloads processing and resource usage in a computing system. An aggregate completion duration for determined workloads that have completed processing is updated. An aggregate consumed resources, comprising an aggregate of resources consumed by workloads, by resources consumed by the determined workloads is updated. The aggregate completion duration and the aggregate consumed resources are used to determine resources to provision for workloads.

Abstract: Provided are a computer program product, system, and method for determining allocatable host system resources to remove from a cluster and return to a host service provider. A determination is made of unused host system resources, that are not currently being used by workloads, in a plurality of host systems. A determination is made of required resources for computational resources required to complete processing unfinished workloads that have not completed. A determination is made of an amount of resources to remove from the cluster by subtracting the unused host system resources by the required resources for computational resources. At least one of the host systems available for the workloads is selected to remove from the cluster having resources that satisfy the amount of resources to remove.

Abstract: A system for improving workload performance using data locality and workload placement may include a schedule module that schedules workloads for execution on a computing device in one or more computing devices. Also, the computing devices access a shared data storage. Further, the system may include a tracking module that maintains a data store that associates paths in the shared data storage with dispatched workloads and associates the paths with at least one computing device, wherein a dispatched workload and the at least one computing device accessed a path; and a preferred device identification module that identifies preferred computing devices in the one or more computing devices for executing undispatched workloads based on information in the data store, wherein the schedule module schedules the execution of the undispatched workloads in response to the identified preferred computing devices.

Abstract: A system for resolving a resource deadlock between processes. A shared data structure is maintained that includes process records of the processes. Process states and process priorities are defined for each of the processes. Values of the process states and process priorities are indicated in the process records. One or more aggregated states of the processes are defined. A respective state of the process is determined, by each process, based on at least one of the process states and process priorities of the process records, and the aggregated states of the processes. The respective state is used to allocate or deallocate resources to the process to mitigate and resolve the resource deadlock between the processes.

Abstract: A computer-implemented method according to one embodiment includes identifying a plurality of storage resources. Additionally, the method includes creating a storage capacity, where the storage capacity has a first plurality of associated attributes. Further, the method includes defining one or more data volumes for the storage capacity, where each of the one or more data volumes has a second plurality of associated attributes and inherits the first plurality of associated attributes. Further still, the method includes configuring one or more volume shares for each data volume, where each of the volume shares has a third plurality of associated attributes and inherits the first plurality of associated attributes as well as the second plurality of associated attributes.

Abstract: Embodiments for automatic diagonal scaling of workloads in a distributed computing environment. For each of a plurality of resources of each of a plurality of application instances, a determination as to whether a change in allocation of at least one of the plurality of resources is required. Operations requirements are computed for each of the plurality of application instances, the computed requirements including vertical increase and decrease operations, and horizontal split and collapse operations. The vertical decrease and horizontal collapse operations are first processed, the vertical increase and horizontal split operations are ordered, and the vertical increase and horizontal split operations are subsequently processed based on the ordering, thereby optimizing application efficiency and utilization of the plurality of resources in the distributed computing environment.

Abstract: For calculation of digest segmentations for input data using similar data in a data deduplication system using a processor device in a computing environment, a stream of input data is partitioned into input data chunks. Similar repository intervals are calculated for each input data chunk. Anchor positions are determined between an input data chunk and the similar repository intervals, based on data matches between a previous input data chunk and previous similar repository intervals. Digest segmentations of the similar repository intervals are projected onto the input data chunk, starting at the anchor positions.

Abstract: A system for resolving a resource deadlock between processes. A shared data structure is maintained that includes process records of the processes. Process states and process priorities are defined for each of the processes. Values of the process states and process priorities are indicated in the process records. One or more aggregated states of the processes are defined. A respective state of the process is determined, by each process, based on at least one of the process states and process priorities of the process records, and the aggregated states of the processes. The respective state is used to allocate or deallocate resources to the process to mitigate and resolve the resource deadlock between the processes.

Abstract: A system for resolving a resource deadlock between processes. The processes are configured to belong to process groups. Resources are allocated on behalf of the process groups to be assigned to respective processes within the process groups. A shared data structure is maintained that includes process records of each of the processes. A determination is made that a respective process is involved in a resource deadlock if the process group to which the process belongs to is involved in the resource deadlock.

Abstract: A system for resolving a resource deadlock between processes. A shared data structure is maintained that includes process records of the processes. Process states and process priorities are defined for each of the processes. A respective state of the process is determined for each process based on the process states and process priorities of the process records maintained in the shared data structure. The respective state is used to allocate and deallocate resources to the process to mitigate and resolve the resource deadlock between the processes.

Abstract: A computer-implemented method according to one embodiment includes identifying a request to create a consumer within a converged system. Additionally, the method includes defining the consumer within a hierarchy of consumers, where the consumer represents a function in an organization. Further, the method includes associating the consumer with a plurality of storage resources and a plurality of computing resources. Further still, the method includes setting a storage capacity attribute for the consumer.

Abstract: Embodiments for workload management with data access awareness in a computing cluster. In response to receiving an input workload for scheduling by a workload manager, a set of inputs is retrieved from a storage system by a data requirements evaluator module. The data requirements evaluator module generates a list of cluster hosts ranked for performing the input workload according to data access considerations and provides the ranked list of cluster hosts to a scheduler module. The scheduler module generates a scheduling of the input workload to certain hosts within the computing cluster where the generated scheduling is optimized with the data access considerations.

Abstract: Embodiments for workload management by aggregating locality information for a set of files in a cluster of hosts, from a file level to a level of the set of files in a cluster of hosts. To facilitate workload scheduling in the cluster, a subset of the set of files is selected. A set of storage size counters, each assigned to a host in the cluster, is reset. An overall storage size counter is reset, and the files in the subset of the set of files are scanned. For each scanned file, locality information of the file is retrieved and added to the storage size counters of the hosts, and a total size of the file is added to the overall storage size counter. An output proportion of the storage size counter of each host is then computed from the overall storage size counter.

Abstract: Embodiments for prioritizing applications for diagonal scaling operations in a distributed computing environment. A significance value of an application of a plurality of applications is defined, the significance value representing an importance of the application or the functionality performed by the application, and dependencies between the plurality of applications are configured. A significance value of a dependency of a dependent application on an antecedent one of the plurality of applications is defined, and priorities for each of the plurality of applications are computed based on the significance values of each of the plurality of applications and respective dependencies therebetween for performing the diagonal scaling operations of resources allocated to each of the applications in the distributed computing environment.

Abstract: Various embodiments for adaptively computing and implementing changes in resource allocations using historical data in a distributed computing environment. Historical data on resource consumption levels of an application is maintained. Either of an increase operation or reduction operation is triggered for a resource required by an application instance of the application, where a predicted consumption level for the resource required by the application instance is computed. The increase or reduction operation is computed and implemented for the resource required by the application instance to accommodate the predicted consumption level, thereby optimizing application efficiency and resource utilization in the distributed computing environment.

Abstract: Embodiments for applying host access control rules for application containers by one or more processors. A first set of user identifiers and permissions is extracted from a temporary container and a second set of user identifiers and permissions is extracted from a host on which a working container will reside. The first set and the second set of user identifiers and permissions are combined into an aggregate set of user identifiers and permissions and injected into the working container.

Abstract: For reducing activation of similarity search in a data deduplication system using a processor device in a computing environment, input data is partitioned into data chunks. A determination is made as to whether to apply a similarity search process for an input data chunk based on deduplication results of a previous input data chunk in the input data.

Abstract: Provided are a computer program product, system, and method for determining allocatable host system resources to remove from a cluster and return to a host service provider. A determination is made of unused host system resources, that are not currently being used by workloads, in a plurality of host systems. A determination is made of required resources for computational resources required to complete processing unfinished workloads that have not completed. A determination is made of an amount of resources to remove from the cluster by subtracting the unused host system resources by the required resources for computational resources. At least one of the host systems available for the workloads is selected to remove from the cluster having resources that satisfy the amount of resources to remove.