Abstract: It is detected that a metric associated with a first workload has breached a first threshold. It is determined that the first workload and a second workload access the same storage resources, wherein the storage resources are associated with a storage server. It is determined that the metric is impacted by the first workload and the second workload accessing the same storage resources. A candidate solution is identifier. An estimated impact of a residual workload is determined based, at least in part, on the candidate solution. A level of caching of at least one of the first workload or the second workload is adjusted based, at least in part, on the estimated impact of the residual workload.

Abstract: It is detected that a metric associated with a first workload has breached a first threshold. It is determined that the first workload and a second workload access the same storage resources, wherein the storage resources are associated with a storage server. It is determined that the metric is impacted by the first workload and the second workload accessing the same storage resources. A candidate solution is identifier. An estimated impact of a residual workload is determined based, at least in part, on the candidate solution. A level of caching of at least one of the first workload or the second workload is adjusted based, at least in part, on the estimated impact of the residual workload.

Abstract: A system operation management server computer (server) and related methods are disclosed. The server is programmed to learn the features of and relations among computer devices from various types of data related to the computer devices and build a knowledge graph (KG) to represent IT infrastructure. The server is also programmed to manage a collection of issue resolution rules each mapping the states of certain computer devices that characterize a known issue and a known resolution of the known issue. In response to receiving a support bundle that contains data related to a target computer system that has encountered an unknown issue the server is programmed to determine which issue resolution rules are applicable to the support bundle based on the KG and transmit a recommendation for resolving the unknown issue.

Abstract: It is detected that a metric associated with a first workload has breached a first threshold. It is determined that the first workload and a second workload access the same storage resources, wherein the storage resources are associated with a storage server. It is determined that the metric is impacted by the first workload and the second workload accessing the same storage resources. A candidate solution is identifier. An estimated impact of a residual workload is determined based, at least in part, on the candidate solution. A level of caching of at least one of the first workload or the second workload is adjusted based, at least in part, on the estimated impact of the residual workload.

Abstract: A system operation management server computer (server) and related methods are disclosed. The server is programmed to learn the features of and relations among computer devices from various types of data related to the computer devices and build a knowledge graph (KG) to represent IT infrastructure. The server is also programmed to manage a collection of issue resolution rules each mapping the states of certain computer devices that characterize a known issue and a known resolution of the known issue. In response to receiving a support bundle that contains data related to a target computer system that has encountered an unknown issue the server is programmed to determine which issue resolution rules are applicable to the support bundle based on the KG and transmit a recommendation for resolving the unknown issue.

Abstract: It is detected that a metric associated with a first workload has breached a first threshold. It is determined that the first workload and a second workload access the same storage resources, wherein the storage resources are associated with a storage server. It is determined that the metric is impacted by the first workload and the second workload accessing the same storage resources. A candidate solution is identifier. An estimated impact of a residual workload is determined based, at least in part, on the candidate solution. A level of caching of at least one of the first workload or the second workload is adjusted based, at least in part, on the estimated impact of the residual workload.

Abstract: Coated diamond particles have solid diamond cores and at least one graphene layer. Methods of forming coated diamond particles include coating diamond particles with a charged species and coating the diamond particles with a graphene layer. A composition includes a substance and a plurality of coated diamond particles dispersed within the substance. An intermediate structure includes a hard polycrystalline material comprising a first plurality of diamond particles and a second plurality of diamond particles. The first plurality of diamond particles and the second plurality of diamond particles are interspersed. A method of forming a polycrystalline compact includes catalyzing the formation of inter-granular bonds between adjacent particles of a plurality of diamond particles having at least one graphene layer.

Abstract: A downhole article comprises a polymer substrate having a surface that is configured for exposure to a well fluid; the substrate comprising a thermoplastic material, an elastomer, or a combination comprising at least one of the foregoing; and a coating disposed on the surface of the polymer substrate; the coating comprising a fluorinated poly-para-xylylene.

Abstract: A cluster configuration system arranged to manage a graph database for tracking and identifying a time-varying state of a cluster of objects. The graph database may include one or more nodes and one or more associations between the nodes to represent time-varying states of the cluster. Management of the graph database may include creating, maintaining, updating, storing, administrating, querying, and/or presenting one or more elements of the graph database.

Abstract: Coated diamond particles have solid diamond cores and at least one graphene layer. Methods of forming coated diamond particles include coating diamond particles with a charged species and coating the diamond particles with a graphene layer. A composition includes a substance and a plurality of coated diamond particles dispersed within the substance. An intermediate structure includes a hard polycrystalline material comprising a first plurality of diamond particles and a second plurality of diamond particles. The first plurality of diamond particles and the second plurality of diamond particles are interspersed. A method of forming a polycrystalline compact includes catalyzing the formation of inter-granular bonds between adjacent particles of a plurality of diamond particles having at least one graphene layer.

Abstract: Coated diamond particles have solid diamond cores and at least one graphene layer. Methods of forming coated diamond particles include coating diamond particles with a charged species and coating the diamond particles with a graphene layer. A composition includes a substance and a plurality of coated diamond particles dispersed within the substance. An intermediate structure includes a hard polycrystalline material comprising a first plurality of diamond particles and a second plurality of diamond particles. The first plurality of diamond particles and the second plurality of diamond particles are interspersed. A method of forming a polycrystalline compact includes catalyzing the formation of inter-granular bonds between adjacent particles of a plurality of diamond particles having at least one graphene layer.

Abstract: A downhole article comprises a polymer substrate having a surface that is configured for exposure to a well fluid; the substrate comprising a thermoplastic material, an elastomer, or a combination comprising at least one of the foregoing; and a coating disposed on the surface of the polymer substrate; the coating comprising a fluorinated poly-para-xylylene.

Abstract: Described herein is a system and method for dynamically managing service-level objectives (SLOs) for workloads of a cluster storage system. Proposed states/solutions of the cluster may be produced and evaluated to select one that achieves the SLOs for each workload. A planner engine may produce a state tree comprising nodes, each node representing a proposed state/solution. New nodes may be added to the state tree based on new solution types that are permitted, or nodes may be removed based on a received time constraint for executing a proposed solution or a client certification of a solution. The planner engine may call an evaluation engine to evaluate proposed states, the evaluation engine using an evaluation function that considers SLO, cost, and optimization goal characteristics to produce a single evaluation value for each proposed state. The planner engine may call a modeler engine that is trained using machine learning techniques.

Abstract: Described herein is a system and method for dynamically managing service-level objectives (SLOs) for workloads of a cluster storage system. Proposed states/solutions of the cluster may be produced and evaluated to select one that achieves the SLOs for each workload. A planner engine may produce a state tree comprising nodes, each node representing a proposed state/solution. New nodes may be added to the state tree based on new solution types that are permitted, or nodes may be removed based on a received time constraint for executing a proposed solution or a client certification of a solution. The planner engine may call an evaluation engine to evaluate proposed states, the evaluation engine using an evaluation function that considers SLO, cost, and optimization goal characteristics to produce a single evaluation value for each proposed state. The planner engine may call a modeler engine that is trained using machine learning techniques.

Abstract: It is detected that a metric associated with a first workload has breached a first threshold. It is determined that the first workload and a second workload access the same storage resources, wherein the storage resources are associated with a storage server. It is determined that the metric is impacted by the first workload and the second workload accessing the same storage resources. A candidate solution is identifier. An estimated impact of a residual workload is determined based, at least in part, on the candidate solution. A level of caching of at least one of the first workload or the second workload is adjusted based, at least in part, on the estimated impact of the residual workload.

Abstract: Described herein is a system and method for dynamically managing service-level objectives (SLOs) for workloads of a cluster storage system. Proposed states/solutions of the cluster may be produced and evaluated to select one that achieves the SLOs for each workload. A planner engine may produce a state tree comprising nodes, each node representing a proposed state/solution. New nodes may be added to the state tree based on new solution types that are permitted, or nodes may be removed based on a received time constraint for executing a proposed solution or a client certification of a solution. The planner engine may call an evaluation engine to evaluate proposed states, the evaluation engine using an evaluation function that considers SLO, cost, and optimization goal characteristics to produce a single evaluation value for each proposed state. The planner engine may call a modeler engine that is trained using machine learning techniques.

Abstract: A change in workload characteristics detected at one tier of a multi-tiered cache is communicated to another tier of the multi-tiered cache. Multiple caching elements exist at different tiers, and at least one tier includes a cache element that is dynamically resizable. The communicated change in workload characteristics causes the receiving tier to adjust at least one aspect of cache performance in the multi-tiered cache. In one aspect, at least one dynamically resizable element in the multi-tiered cache is resized responsive to the change in workload characteristics.

Abstract: Embodiments of the systems and techniques described here can leverage several insights into the nature of workload access patterns and the working-set behavior to reduce the memory overheads. As a result, various embodiments make it feasible to maintain running estimates of a workload's cacheability in current storage systems with limited resources. For example, some embodiments provide for a method comprising estimating cacheability of a workload based on a first working-set size estimate generated from the workload over a first monitoring interval. Then, based on the cacheability of the workload, a workload cache size can be determined. A cache then can be dynamically allocated (e.g., change, possibly frequently, the cache allocation for the workload when the current allocation and the desired workload cache size differ), within a storage system for example, in accordance with the workload cache size.

Abstract: It is detected that a metric associated with a first workload has breached a first threshold. It is determined that the first workload and a second workload access the same storage resources, wherein the storage resources are associated with a storage server. It is determined that the metric is impacted by the first workload and the second workload accessing the same storage resources. In response to a determination that the metric is impacted by the first workload and the second workload accessing the same storage resources, a first virtual cache appliance is instantiated and one of the first workload or the second workload is routed through the virtual cache appliance. Routing one of the first workload or the second workload through the first virtual cache appliance causes the first virtual cache appliance to cache data associated with the storage resources.

Abstract: Described herein is a system and method for dynamically managing service-level objectives (SLOs) for workloads of a cluster storage system. Proposed states/solutions of the cluster may be produced and evaluated to select one that achieves the SLOs for each workload. A planner engine may produce a state tree comprising nodes, each node representing a proposed state/solution. New nodes may be added to the state tree based on new solution types that are permitted, or nodes may be removed based on a received time constraint for executing a proposed solution or a client certification of a solution. The planner engine may call an evaluation engine to evaluate proposed states, the evaluation engine using an evaluation function that considers SLO, cost, and optimization goal characteristics to produce a single evaluation value for each proposed state. The planner engine may call a modeler engine that is trained using machine learning techniques.