Abstract: Selecting an optimal combination of cloud resources within budget constraints, by a processor. All possible combinations for cloud resource bundles are computed which are available for allocation. The possible combinations are filtered according to predetermined criteria. The filtered possible combinations are divided into a first set that satisfies an overall workload demand for resources and a second set that partially satisfies the overall workload demand for resources. A level of goodness may be calculated for one or both of the first and second sets, and resources may be allocated from the first or second set to a cluster according to the calculated level of goodness. In some embodiments, the level of goodness may be defined based on the relative desirability (i.e., a user's preference) of aspects such as compute power, cost of resources, and the distribution or co-location of respective resources of the cloud resource bundles.

Abstract: A computer-implemented method and a computer program product for estimating attributes of running workloads on platforms in a system of multiple platforms as a service. A computer receives definitions of respective workloads and respective platforms that are eligible to run a set of the respective workloads. The computer maps the respective workloads and the respective platforms to attributes of running the respective workloads on the respective platforms. The computer estimates the attributes and storing the attributes in a matrix. The computer updates the attribute in the matrix, in response to a triggering event for modifying the matrix.

Abstract: A computer-implemented method and a computer program product for estimating attributes of running workloads on platforms in a system of multiple platforms as a service. A computer receives definitions of respective workloads and respective platforms that are eligible to run a set of the respective workloads. The computer maps the respective workloads and the respective platforms to attributes of running the respective workloads on the respective platforms. The computer estimates the attributes and storing the attributes in a matrix. The computer updates the attribute in the matrix, in response to a triggering event for modifying the matrix.

Abstract: A computer-implemented method, a computer program product, and a computer system for placements of workloads in a system of multiple platforms as a service. A computer detects a triggering event for modifying a matrix that pairs respective workloads on respective platforms and includes attributes of running respective workloads on respective platforms. The computer recalculates the attributes in the matrix, in response to the triggering event being detected. The computer determines optimal placements of the respective workloads on the respective platforms, based on information in the matrix. The computer places the respective workloads on the respective platforms, based on the optimal placements.

Abstract: A computer-implemented method, a computer program product, and a computer system for optimizing workload placements in a system of multiple platforms as a service. A computer first places respective workloads on respective platforms that yield lowest costs for the respective workloads. The computer determines whether mandatory constraints are satisfied. The computer checks best effort constraints, in response to the mandatory constraints being satisfied. The computer determines a set of workloads for which the best effort constraints are not satisfied and determines a set of candidate platforms that yield the lowest costs and enable the best effort constraints to be satisfied. From the set of workloads, the computer selects a workload that has a lowest upgraded cost and updates the workload by setting an upgraded platform index.

Abstract: Sensor data can be collected from a first set of sensors associated with a first seat within a vehicle during a first vehicle stage. The outputs of each sensor of the first set of sensors can then be aggregated to calculate a probability of life within the first seat during the first vehicle stage.

Abstract: Provided is a method for identifying problematic input fields in a webform. The method comprises obtaining a set of user interaction data for a plurality of user interactions with input fields of a webform. The user interaction data for each input field includes data corresponding to at least one aspect. The method comprises assigning an aspect value to each aspect of each user interaction with each input field. The method comprises aggregating aspect values into an aggregated aspect value for each input field, generating a score for each input field based at least in part on the aggregated aspect field, ranking the input fields by their respective scores to identify at least one particular input field in the webform as problematic, and indicating that the at least one particular input field in the webform is problematic.

Abstract: Embodiments for aggregated information calculation and injection for application containers by one or more processors. Prior to commencing execution of an application inside a working container, a temporary container having an equivalent application template or container template as the working container is started. A first instance of the application is instantiated and executed from inside the temporary container. Relevant information, obtained during the execution of the first application instance from inside the temporary container, and relevant information from a host associated with the application, is extracted. The relevant information from the host and the temporary container is aggregated. A second instance of the application is executed and the aggregated information is injected into the working container.

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: Calculating a remaining budget in a cloud bursting environment, by a processor. Within a particular time window, a first cost is computed of allocated and released cloud hosts. A second cost is computed of the cloud hosts that are allocated and not yet released. A remaining budget is computed as a difference between a budget limit and a sum of the first cost and the second cost, at the current point in time. A third, estimated cost of allocated and not yet released cloud hosts; and a fourth, estimated cost of cloud host requests currently in progress are each then determined. A safe remaining budget is then computed by subtracting the third and fourth estimated costs from the remaining budget determined prior.

Abstract: Embodiments for reducing resource consumption of a similarity index in data deduplication by a processor. Only a latest generation of repository data is represented in the similarity index. Implicit deletion is applied in the similarity index. A subset of bytes of a full representative value is maintained in a similarity index entry. A respective one of a plurality of similarity units is deduplicated with a corresponding similarity unit of a previous snapshot, and a deduplication coverage thereof is examined. If a deduplication coverage threshold is not met, a similarity search is conducted and the respective one of the similarity units is deduplicated with a found similarity unit residing in the similarity index.

Abstract: Calculating a remaining budget in a cloud bursting environment, by a processor. Within a particular time window, a first cost is computed of allocated and released cloud hosts. A second cost is computed of the cloud hosts that are allocated and not yet released. A remaining budget is computed as a difference between a budget limit and a sum of the first cost and the second cost, at the current point in time. A third, estimated cost of allocated and not yet released cloud hosts; and a fourth, estimated cost of cloud host requests currently in progress are each then determined. A safe remaining budget is then computed by subtracting the third and fourth estimated costs from the remaining budget determined prior.

Abstract: Nodes of a weighted tree each have their own weight. A normalized weight of a node, relative to other nodes in the tree, is determined based on a proportional weight of the node and a lesser unique sum of the node, as well as those of the node's parents and grandparents, up to a root of the tree. The proportional weight and lesser unique sum of a given node depend only on the unique weights of the sibling group including the given node. Thus, if a weight is modified, the normalized weight can be updated without necessarily recalculating the entire tree.

Abstract: Selecting an optimal combination of cloud resources within budget constraints, by a processor. All possible combinations for cloud resource bundles are computed which are available for allocation. The possible combinations are filtered according to predetermined criteria. The filtered possible combinations are divided into a first set that satisfies an overall workload demand for resources and a second set that partially satisfies the overall workload demand for resources. A level of goodness may be calculated for one or both of the first and second sets, and resources may be allocated from the first or second set to a cluster according to the calculated level of goodness. In some embodiments, the level of goodness may be defined based on the relative desirability (i.e., a user's preference) of aspects such as compute power, cost of resources, and the distribution or co-location of respective resources of the cloud resource bundles.

Abstract: Provided is a method for identifying problematic input fields in a webform. The method comprises obtaining a set of user interaction data for a plurality of user interactions with input fields of a webform. The user interaction data for each input field includes data corresponding to at least one aspect. The method comprises assigning an aspect value to each aspect of each user interaction with each input field. The method comprises aggregating aspect values into an aggregated aspect value for each input field, generating a score for each input field based at least in part on the aggregated aspect field, ranking the input fields by their respective scores to identify at least one particular input field in the webform as problematic, and indicating that the at least one particular input field in the webform is problematic.

Abstract: Provided are a computer program product, system, and method for estimating resource requests for workloads to offload to host systems in a computing environment. A calculation is made required resources of computational resources required to complete processing a plurality of unfinished workloads that have not completed. A determination is made of allocated resources that are not yet provisioned to workloads. The required resources are reduced by the allocated resources not yet provisioned to determine resources to provision. The resources to provision for the unfinished workloads are requested.

Abstract: Embodiments for workload management with data access awareness by ordering hosts for scheduling workloads 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.

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: Provided are a computer program product, system, and method for estimating resource requests for workloads to offload to host systems in a computing environment. A calculation is made required resources of computational resources required to complete processing a plurality of unfinished workloads that have not completed. A determination is made of allocated resources that are not yet provisioned to workloads. The required resources are reduced by the allocated resources not yet provisioned to determine resources to provision. The resources to provision for the unfinished workloads are requested.

Abstract: A computer-implemented method according to one embodiment includes identifying a request to create a consumer within a converged system, defining the consumer within a hierarchy of consumers, where the consumer represents a function in an organization, setting a storage capacity attribute for the consumer, and conditionally defining a data volume for the consumer, based at least in part on the storage capacity attribute.