Abstract: Automatically managing database applications, including identifying, by a management extension, an SQL server host connected to a storage system, wherein the SQL server host comprises an SQL server managing an SQL database supported by the storage system; identifying, by the management extension, the SQL database supported by the storage system based on the identified SQL server host; and scheduling, by the management extension, a backup of the SQL database.

Abstract: Providing storage tailored for a storage consuming application, including: identifying, for an application that utilizes storage resources within a cloud-based storage system, one or more storage performance characteristics associated with the application; comparing the storage performance characteristics of the application that were identified with storage performance characteristics of storage resources of one or more cloud-based storage systems; and selecting, based on the comparing, one or more storage resources within the one or more cloud-based storage systems to provide storage services to the application.

Abstract: Providing application-specific storage by a cloud-based storage system, including: identifying, for an application that utilizes resources within the cloud-based storage system, one or more characteristics associated with the application; and selecting, in dependence upon the one or more characteristics associated with the application and characteristics of resources within the cloud-based storage system, one or more resources within the cloud-based storage system to support the execution of the application, wherein at least a portion of a dataset associated with the application is stored as blocks within block storage resources in the cloud-based storage system and also stored as objects within object storage resources in the cloud-based storage system.

Abstract: Providing highly available application-specific storage by a cloud-based storage system, including: detecting that a component within a cloud-based storage system that supports an application has become unavailable; and selecting a replacement component within the cloud-based storage system to support the application, wherein at least a portion of a dataset associated with the application is stored as blocks within block storage resources in the cloud-based storage system and also stored as objects within object storage resources in the cloud-based storage system.

Abstract: Providing application-aware analytics for storage systems, including: collecting, by a workload migration module, from a first host, first data describing performance characteristics of the first host and second data describing performance characteristics of one or more clients connected to the first host and associated with a workload supported by the first host; identifying, based on the data, a second host for servicing the workload; and deploying the workload in the second host.

Abstract: Migrating workloads to a preferred environment, including: predicting, for each of a plurality of environments, a performance load on each of a plurality of environments that would result from placing one or more of a plurality of workloads on the environment; determining a preferred environment for each of the plurality of workloads by determining a placement of each of the plurality of workloads that results in a best fit for the plurality of workloads; and deploying each of the plurality of workloads in the corresponding preferred environment.

Abstract: Providing workload mobility between disparate execution environments, including: identifying, by a workload migration module, a workload executing in a first environment, wherein the workload includes a software application that is being executed and data that is accessed by the software application; identifying, by a workload migration module, a second environment for servicing the workload; and deploying, by a workload migration module, the workload in the second environment.

Abstract: Example methods and systems for background subtraction re-initialization are disclosed. In an example method, computing system may use a set of active sensors to determine a background representation of a space that can be divided into subspaces with each subspace depicted by a quantity of data points that depends on the active sensors. The system may determine locations of objects moving the space using the active sensors and the background representation. In some instances, the system may receive an indication of a change in the active sensors and responsively determine new quantities of data points that depict each subspace after the change. The system may further adjust the background representation of the space by subtracting data points corresponding to the determined locations of the objects moving in the space from the new quantities of data points that depict each subspace of the space after the change in the active sensors.

Abstract: Aspects and implementations of the present disclosure are directed to methods and systems for a network tolerant to a network device that is temporarily absent from the control plane. In one aspect, in general, the system includes an event manager configured to send, to a controller configured to exchange control messages with a network device, a first request to temporarily withdraw the network device from control plane interactions. The event manager then triggers an event at the network device during which the network device is non-responsive to control plane interactions. After determining that the event has completed, the event manager sends the controller a second request to restore the network device. The controller is configured to request, responsive to the first request, a network application to transition to a tolerant state; and to request, responsive to the second request, the network application to transition to a sensitive state.

Abstract: An adaptive and interactive training system and method is provided. The system provides training content to a user of an application program based upon a variety of factors. The system selects the training content based upon the user's individualized needs vis-à-vis an application program. The system may customize the training sent to the user by evaluating the user's actual interaction with the application program, the user's personal profile and the group profile of groups to which the user belongs.