Workload migration recommendations in heterogeneous workspace environments
Systems and methods for workload migration recommendations in heterogeneous workspace environments are described. In some embodiments, an Information Handling System (IHS) may include a processor and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution, cause the IHS to: identify a set of workspaces launched by a set of users, among a plurality of workspaces launched by a plurality of users, where each workspace in the set of workspaces is associated with a performance or user experience metric below a threshold value; select, among a plurality of workloads executed within the set of workspaces, one or more workloads suitable for migration; and for each user of the set of users, determine whether to migrate any of the selected one or more workloads based, at least in part, upon an allocation of cloud and device resources available to the plurality of users.
1 . An Information Handling System (IHS), the IHS comprising:
a processor; and
a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution, cause the IHS to:
identify a set of workspaces launched by a set of users, among a plurality of workspaces launched by a plurality of users, wherein each workspace in the set of workspaces is associated with a performance or user experience metric below a threshold value;
select, among a plurality of workloads executed within the set of workspaces, one or more workloads suitable for migration, at least in part, based upon a comparison between contextual information obtained by a hardware sensor and a policy that specifies whether to prevent, allow, or require migration of a given workload based, at least in part, upon a user's physical presence status with respect to the IHS, wherein the IHS comprises a laptop, and wherein the user's physical presence status with respect to the IHS is determined by whether the user is present in relation to the laptop, absent in relation to the laptop, or facing an integrated display of the laptop; and
for each user of the set of users, determine whether to migrate any of the selected one or more workloads based, at least in part, upon an allocation of cloud and device resources available to the plurality of users.
2 . The IHS of claim 1 , wherein to identify the set of workspaces, the program instructions, upon execution, further cause the IHS to rank a level of performance or user experience of each of the plurality of workspaces based, at least in part, upon workspace analytics determined from workspace context for each workspace.
3 . The IHS of claim 2 , wherein the workspace analytics comprises an indication of at least one of: a workspace utilization histogram, a device utilization histogram, a customer experience rating, a service ticket metric, or an Information Technology (IT) policy.
4 . The IHS of claim 3 , wherein the IT policy is identified in a workspace definition provided by a remote orchestration service.
5 . The IHS of claim 3 , wherein the workspace context comprises an indication of at least one of: a workspace utilization metric, a device utilization metric, an Operating System (OS) metric, a customer survey result, or a service ticket.
6 . The IHS of claim 1 , wherein to select the one or more workloads suitable for migration, the program instructions, upon execution, further cause the IHS to perform a utilization assessment of the one or more workloads using an Energy Estimation Engine (E 3 ).
7 . The IHS of claim 1 , wherein to select the one or more workloads suitable for migration, the program instructions, upon execution, further cause the IHS to perform a proficiency assessment of the one or more workloads using application telemetry data.
8 . The IHS of claim 7 , wherein the application telemetry data comprises an indication of at least one of: a number of applications, a total number of files handled, a number of remote and local files handled, a number of application add-ons or plug-ins installed, or specific capability usage.
9 . The IHS of claim 1 , wherein the allocation of cloud and device resources is performed via a machine learning (ML) algorithm.
10 . The IHS of claim 1 , wherein the allocation of cloud and device resources lists the selected one or more workloads in order of migration priority.
11 . The IHS of claim 10 , wherein the list comprises, for each user and workspace combination associated with the selected one or more workloads, an indication of a corresponding cloud performance tier and an indication of a corresponding device performance tier.
12 . The IHS of claim 10 , wherein the allocation of resources maintains a total cost of the cloud and device resources for the plurality of users under a budget.
13 . The IHS of claim 1 , wherein the allocation of cloud and device resources is based at least in part upon context information associated with each device used to execute the one or more workloads.
14 . A memory storage device having program instructions stored thereon that, upon execution by an Information Handling System (IHS), cause the IHS to:
select, among a plurality of workloads executed within a set of workspaces, one or more workloads suitable for migration, at least in part, based upon a comparison between contextual information obtained by a sensor device and a policy that specifies whether to prevent, allow, or require migration of a given workload based, at least in part, upon a user's physical presence status with respect to the IHS, wherein the IHS comprises a laptop, and wherein the user's physical presence status with respect to the IHS is determined by whether the user is present in relation to the laptop, absent in relation to the laptop, or facing an integrated display of the laptop; and
for each user of a set of users, determine whether to migrate any of the selected one or more workloads based, at least in part, upon an allocation of cloud and device resources available to a plurality of users.
15 . The memory storage device of claim 14 , wherein the set of workspaces is launched by the set of users, among a plurality of workspaces launched by the plurality of users, and wherein performance metrics associated with each workspace in the set of workspaces are below a threshold value.
16 . The memory storage device of claim 14 , wherein to select the one or more workloads suitable for migration, the program instructions, upon execution, further cause the IHS to perform a utilization assessment of the one or more workloads using an Energy Estimation Engine (E3) and a proficiency assessment of the one or more workloads using application telemetry data.
17 . A method, comprising:
selecting, by an Information Handling System (IHS), among a plurality of workloads executed within a set of workspaces, one or more workloads suitable for migration, at least in part, by comparing contextual information obtained by a hardware sensor against a policy that specifies whether to prevent, allow, or require migration of a given workload based, at least in part, upon an IHS posture indicative of a mode in which the IHS is physically configured and upon a user's physical presence status with respect to the IHS; and
for each user of a set of users, determining whether to migrate any of the selected one or more workloads based, at least in part, upon an allocation of cloud and device resources available to a plurality of users;
wherein the IHS comprises a laptop, wherein the mode is indicative of a laptop posture, a landscape posture, a tablet posture, a book posture, or a tent posture, and wherein each of the postures is determined by a relative angle between two panels of the laptop; and
wherein the user's physical presence status with respect to the IHS is determined by whether the user is present in relation to the laptop, absent in relation to the laptop, or facing an integrated display of the laptop.
18 . The method of claim 17 , wherein the set of workspaces is launched by the set of users, among a plurality of workspaces launched by the plurality of users, and wherein user experience metrics associated with each workspace in the set of workspaces are below a threshold value.
19 . The method of claim 18 , wherein the allocation of resources increases the user experience metrics while maintaining a cost of the cloud and device resources available to the plurality of users under a budget.
20 . The method of claim 17 , wherein the mode is further indicative of the landscape posture, the book posture, or the tent posture.