Abstract: For power management in a disaggregated computing system, a set of initial electrical power levels are allocated to a set of processor cores according to a predicted desired workload, where the set of initial power levels aggregate to an initial collective contracted power level. Electrical power is dynamically allocated to respective processor cores within the set of processor cores to produce a capacity to execute a collective demanded workload while maintaining the electrical power to the set of processor cores to an approximately constant electrical power level within a threshold of the initial collective contracted electrical power level.

Abstract: For measuring component utilization in a computing system, a server energy utilization reading of a statistical significant number of servers out of a total number of servers located in the datacenter is obtained by measuring, at predetermined intervals, a collective energy consumed by all processing components within each server. The collective energy is measured by virtually probing thereby monitoring an energy consumption of individual ones of all the processing components to each collect an individual energy utilization reading, where the individual energy utilization reading is aggregated over a predetermined time period to collect an energy consumption pattern associated with the server utilization reading.

Abstract: Identify individual machines of a multi-machine computing system. Construct a graph of dependencies among the machines. Obtain estimated total administration times and administration priorities for each of the machines. Identify availability of administration resources to assist in administration of one or more of the machines. Select a first set of machines for administration in response to the graph, administration priorities, estimated total administration times, and availability of the first set of administration resources, and administer the first set of machines in parallel using the first set of administration resources. Update the graph in response to administration of the first set of machines. Select a subsequent set of machines for administration in response to the updated graph, administration priorities, estimated total administration times, and availability of a subsequent set of administration resources.

Abstract: Embodiments of the present invention provide systems and methods for the discovery of facets. A search query over sets of data (e.g., a set of documents) leads to search results. The search results are organized by facets. Responsive to receiving new queries, facets are dynamically extracted from the search results. Furthermore, user profiles are dynamically updated. The order of presentation of facets, as displayed in a graphical user interface, can be modified based on the extracted facets.

Abstract: For disaster recovery involving a first site and a disaster recovery site, where at least a portion of management service metadata not isolated within the management service, a failover process is initiated, including creating an initial snapshot of the distributed metadata state. In a failback process, a representation is created of state changes for the management service and a delta description is calculated therefrom. The delta description is transmitted to the first site; and a reverse replica is created, at the first site, of all the workload components from the disaster recovery site. The delta description is played back to restore a distributed metadata state that existed in the disaster recovery site and to re-create it in the first site.

Abstract: Various embodiments for allocating resources in a disaggregated cloud computing environment, by a processor device, are provided. Respective members of a pool of hardware resources are assigned to each one of a plurality of tenants based upon a classification of the respective members of the pool of hardware resources. The respective members of the pool of hardware resources are assigned to each one of the plurality of tenants independently of a hardware enclosure in which the respective members of the pool of hardware resources are physically located.

Abstract: For disaster recovery involving a first site and a disaster recovery site, where at least a portion of management service metadata not isolated within the management service, a failover process is initiated, including creating an initial snapshot of the distributed metadata state. In a failback process, a representation is created of state changes for the management service and a delta description is calculated therefrom. The delta description is transmitted to the first site; and a reverse replica is created, at the first site, of all the workload components from the disaster recovery site. The delta description is played back to restore a distributed metadata state that existed in the disaster recovery site and to re-create it in the first site.

Abstract: Server resources in a data center are disaggregated into shared server resource pools. Servers are constructed dynamically, on-demand and based on workload requirements and a tenant's resiliency requirements (e.g., as specified in an SLA), by allocating from these resource pools. A disaggregated compute system of this type keeps track of resources that are available in the shared server resource pools, and it manages those resources based on that information and the health of the resources. As a workload is processed by the server entity and component resources fail, the server entity composition is changed, e.g. by allocating other resources to the server entity, or by transitioning to other server entities, to ensure that a resiliency requirement is maintained.

Abstract: During normal operation, at a first site, of a disaster recovery management unit, at least one customer workload machine, at least one management service machine, and metadata for the at least one management service machine are replicated to a remote disaster recovery site. After a disaster at the first site, a replicated version of the at least one customer workload machine and a replicated version of the at least one management service machine are brought up at the remote disaster recovery site. A replicated version of the metadata for the at least one management service machine is reconfigured by executing, on the replicated version of the at least one management service machine, a failover script, to obtain reconfigured replicated metadata for the replicated version of the at least one management service machine. When the first site comes back up, failback is carried out, essentially in the reverse order.

Abstract: Various embodiments for elastic resource provisioning in a disaggregated cloud computing environment, by a processor device, are provided. Respective members of pools of hardware resources within the disaggregated cloud computing environment are provisioned to a tenant according to an application-level service level agreement (SLA). Upon detecting a potential violation of the application-level SLA, additional respective members of the pools of hardware resources are provisioned on a component level to the tenant to avoid a violation of the SLA by one of a scale-up process and a scale-out process.

Abstract: Embodiments of the present invention provide systems and methods for the discovery of facets. A search query over sets of data (e.g., a set of documents) leads to search results. The search results are organized by facets. Responsive to receiving new queries, facets are dynamically extracted from the search results. Furthermore, user profiles are dynamically updated. The order of presentation of facets, as displayed in a graphical user interface, can be modified based on the extracted facets.

Abstract: Embodiments of the present invention provide systems and methods for the discovery of facets. A search query over sets of data (e.g., a set of documents) leads to search results. The search results are organized by facets. Responsive to receiving new queries, facets are dynamically extracted from the search results. Furthermore, user profiles are dynamically updated. The order of presentation of facets, as displayed in a graphical user interface, can be modified based on the extracted facets.

Abstract: Various embodiments for performing hardware upgrades in a disaggregated computing environment. A workload is run on a disaggregated computing system while providing a new component to at least one of a plurality of component pools used by the disaggregated computing system. Point-to-point circuit wire level switching is used to switch the disaggregated system from an assigned component residing in a first of the plurality of component pools to the new component residing in a second of the plurality of component pools without interrupting the running workload.

Abstract: Embodiments for performing rolling software upgrades in a disaggregated computing environment. A rolling upgrade manager is provided for upgrading one or more disaggregated servers. A designated memory area is used for storing an updated software component, and a disaggregated server is switched to the designated memory area from a currently assigned memory area when performing the software upgrade.

Abstract: Input data are received from a source environment comprising a plurality of servers and one or more applications running on at least one of the servers. One or more patterns are discovered from the received data comprising information regarding the plurality of servers running applications that collectively perform a service. The patterns are analyzed to learn a recurring pattern. A security policy is designed for the recurring pattern. The recurring pattern and the security policy designed for the recurring pattern is stored in a database.

Abstract: A base query having a plurality of base query terms is obtained. A plurality of problem log files are accessed. Words, contained in a corpus vocabulary, are extracted from the plurality of problem log files. Based on the words extracted from the plurality of problem log files, a first expanded query is generated from the base query. The corpus is queried, via a query engine and a corpus index, with a second expanded query related to the first expanded query.

Abstract: Identify individual machines of a multi-machine computing system. Construct a graph of dependencies among the machines. Obtain estimated total administration times and administration priorities for each of the machines. Identify availability of administration resources to assist in administration of one or more of the machines. Select a first set of machines for administration in response to the graph, administration priorities, estimated total administration times, and availability of the first set of administration resources, and administer the first set of machines in parallel using the first set of administration resources. Update the graph in response to administration of the first set of machines. Select a subsequent set of machines for administration in response to the updated graph, administration priorities, estimated total administration times, and availability of a subsequent set of administration resources.

Abstract: For power management in a disaggregated computing system, upon detecting an electrical power reduction to the disaggregated computing system, respective workloads being performed by respective processors within a set of processors are prioritized according to a service level agreement (SLA) of the respective workloads. Backup electrical power is dynamically allocated to the respective processors performing the respective workloads based upon a priority of the SLA of the respective workloads.

Abstract: For power management in a computing system, component utilization is dynamically managed within the computing system according to a calculated aggregate energy consumed by each one of a set of processors. Each of a plurality of energy factors are measured individually between each one of the set of processors to accumulate the calculated aggregate energy in real time.

Abstract: For measuring component utilization in a computing system, a server energy utilization reading of a statistical significant number of servers out of a total number of servers located in the datacenter is obtained by measuring, at predetermined intervals, a collective energy consumed by all processing components within each server. The collective energy is measured by virtually probing thereby monitoring an energy consumption of individual ones of all the processing components to each collect an individual energy utilization reading, where the individual energy utilization reading is aggregated over a predetermined time period to collect an energy consumption pattern associated with the server utilization reading.